In this paper, I discuss how information theory has been used in the study of animal communication, as well as how these uses are justified. Biologists justify their use of Shannon’s information measures by the work they do in allowing for comparisons between different organisms and because they measure a quantity that is purported to be important for natural selection. I argue that there are problems with both sorts of justification. To make these difficulties clear, I focus (...) on the use of Shannon’s information measures to quantify the amount of information transmitted by the fire ant’s odor trail and the honeybee’s waggle dance. Both of these systems are relatively simple and well understood, and the application of Shannon’s information measure to these systems initially seemed very promising and relatively straightforward. They are therefore particularly suitable for revealing the benefits and difficulties of applying Shannon’s information measures to biological systems in general, and animal communication systems in particular. (shrink)

Progress has become a suspect concept in evolutionary biology, not the least because the core concepts of neo-Darwinism do not support the idea that evolution is progressive. There have been a number of attempts to account for directionality in evolution through additions to the core hypotheses of neo-Darwinism, but they do not establish progressiveness, and they are somewhat of an ad hoc collection. The standard account of fitness and adaptation can be rephrased in terms of information theory. (...) From this, an information of adaptation can be defined in terms of a fitness function. The information of adaptation is a measure of the mutual information between biota and their environment. If the actual state of adaptation lags behind the state of optimal adaptation, then it is possible for the information of adaptation to increase indefinitely. Since adaptations are functional, this suggests the possibility of progressive evolution in the sense of increasing adaptation. Keywords: evolution, information, adaptation, fitness, entropy, progress.. (shrink)

Since the beginning of the XX-th century, it became increasingly evident that information, besides matter and energy, is a major actor in the life processes. Moreover, communication of information has been recognized as differentiating living things from inanimate ones, hence as specific to the life processes. Therefore the sciences of matter and energy, chemistry and physics, do not suffice to deal with life processes. Biology should also rely on sciences of information. A majority of biologists, however, (...) did not change their mind and continued to describe life in terms of chemistry and physics. They merely borrowed some vocabulary from the information sciences. The first science of information available to biological applications, semiotics, appeared at the end of the XIX-th century. It is a qualitative and descriptive science which stemmed from efforts of linguists and philosophers to understand the human language and is thus mainly concerned with semantics. Applying semiotics to biology resulted in today’s Biosemiotics. Independently, an explosive expansion of communication engineering began in the second half of the XX-th century. Besides tremendous progresses in hardware technology, it was made possible by the onset of a science of literal communication: Information Theory (Shannon, Bell Syst Tech J 27:379–457, 623–656, 1948). Literal communication consists of faithfully transporting a message from a place to another, or from an instant to another. Because the meaning of a message does not matter for its transportation, information theory ignores semantics. This restriction enables defining information as a measurable quantity on which a mathematical theory of communication is founded. Although lacking implementation means at its beginning, information theory became later very successful for designing communication means. Modern ones, like mobile phones, can be thought of as experimentally proving the relevance and accuracy of information theory since their design and operation heavily rely on it. Information theory is plainly relevant to biological functions which involve literal communication, especially heredity. This paper is intended to compare the two approaches. It shows that, besides obvious differences, they have some points in common: for instance, the quantitative measurement of information obeys Peirce’s triadic paradigm. They also can mutually enlighten each other. Using information theory, which is closer to the basic communication mechanisms, may appear as a preliminary step prior to more elaborated investigations. Criticizing genetics from outside, information theory furthermore reveals that the ability of the template-replication paradigm to faithfully conserve genomes is but a prejudice. Heredity actually demands error-correcting means which impose severe constraints to the living world and must be recognized as biological facts. (shrink)

The concept of information has acquired a strikingly prominent role in contemporary biology. This trend is especially marked within genetics, but it has also become important in other areas, such as evolutionary theory and developmental biology, particularly where these fields border on genetics. The most distinctive biological role for informational concepts, and the one that has generated the most discussion, is in the description of the relations between genes and the various structures and processes that genes (...) play a role in causing. For many biologists, the causal role of genes should be understood in terms of their carrying information about their various products. That information might require the cooperation of various environmental factors before it can be "expressed," but the same can be said of other kinds of message. An initial response might be to think that this mode of description is entirely anchored in a set of well-established facts about the role of DNA and RNA within protein synthesis, summarized in the familiar chart representing the "genetic code," mapping DNA base triplets to amino acids. However, informational enthusiasm in biology predates even a rudimentary understanding of these mechanisms (Schrodinger 1944). And more importantly, current applications of informational concepts extend far beyond anything that can receive an obvious justification in terms of the familiar facts about the specification of protein molecules by DNA. This includes: 1 (i) The description of whole-organism phenotypic traits (including complex behavioral traits) as specified or coded for by information contained in the genes, (ii) The treatment of many causal processes within cells, and perhaps of the wholeorganism developmental sequence, in terms of the execution of a program stored in the genes, (iii) The idea that genes themselves, for the purpose of evolutionary theorizing, should be seen as, in some sense, "made" of information.. (shrink)

Communication is an important feature of the living world that mainstream biology fails to adequately deal with. Applying two main disciplines can be contemplated to fill in this gap: semiotics and information theory. Semiotics is a philosophical discipline mainly concerned with meaning; applying it to life already originated in biosemiotics. Information theory is a mathematical discipline coming from engineering which has literal communication as purpose. Biosemiotics and information theory are thus concerned with distinct (...) and complementary possible meanings of the word ‘communication’. Since literal communication needs to be secured so as to enable semantics being communicated, information theory is a necessary prerequisite to biosemiotics. Moreover, heredity is a purely literal communication process of capital importance fully relevant to literal communication, hence to information theory. A short introduction to discrete information theory is proposed, which is centred on the concept of redundancy and its use in order to make sequences resilient to errors. Information theory has been an extremely active and fruitful domain of researches and the motor of the tremendous progress of communication engineering in the last decades. Its possible connections with semantics and linguistics are briefly considered. Its applications to biology are suggested especially as regards error-correcting codes which are mandatory for securing the conservation of genomes. Biology needs information theory so biologists and communication engineers should closely collaborate. (shrink)

The notion of information has figured prominently in much modern evolutionary theorizing. But while theorists usually concede the importance of distinguishing between our ordinary use of this notion and its special acceptation in information theory, some biological theorizing requires "information" to serve a double duty. Lorenz's ethological theorizing is a case in point, and this paper challenges its conceptual underpinnings. Special attention is paid to Lorenz's contention that adaptation to an environment is akin to representation, and (...) it is urged that many purportedly (phylogenetically) adapted behaviors might well instead be better interpreted as non-information-laden (ontogenetically) adaptive behaviors. (shrink)

Whether “information” exists in biology, and in what sense, has been a topic of much recent discussion. I explore Shannon, Dretskean, and teleosemantic theories, and analyze whether or not they are able to give a successful naturalistic account of information—specifically accounts of meaning and error—in biological systems. I argue that the Shannon and Dretskean theories are unable to account for either, but that the teleosemantic theory is able to account for meaning. However, I argue that it (...) is unable to account for error. Thus I conclude that while talk of informational meaning is justifiable within a naturalistic framework, talk of informational error is not, and must be used in a metaphorical sense only. (shrink)

In this article, we provide a case study examining how integrative systems biologists build simulation models in the absence of a theoretical base. Lacking theoretical starting points, integrative systems biology researchers rely cognitively on the model-building process to disentangle and understand complex biochemical systems. They build simulations from the ground up in a nest-like fashion, by pulling together information and techniques from a variety of possible sources and experimenting with different structures in order to discover a stable, robust (...) result. Finally, we analyze the alternative role and meaning theory has in systems biology expressed as canonical template theories like Biochemical Systems Theory. (shrink)

The notion of the value of information is discussed. The value one attributes to information is determined by the result of its reception by an open nonequilibrium system. Qualitative reasoning shows that the concept of value of information makes sense only in nonequilibrium situations, and is directly connected with the nonredundancy of information. In biology it is the value and not the amount of information that is important. The value of information is especially (...) high if there are instabilities in the system; these are connected with the notions of purpose and of freedom of will. The notion of selective value, introduced by Eigen in the theory of the prebiological evolution of macromolecules, is discussed. The amount of information in various codons is calculated and the conventional definition of its value is given based on the determination of the danger of the replacement of one amino acid by another with a different value of hydrophobicity. It is shown that the relative probability of transversion is considerably lower than that of transition. As most nonsense mutations are transversions, the genetic code provides decreased probability for the most dangerous mutations. It is shown that the information of the codonUGG(Trp) is highest in both amount and value. (shrink)

Function refers to a broad family of concepts of varying abstractness and range of application, from a many-one mathematical relation of great generality to, for example, highly specialized roles of designed elements in complex machines such as degaussing in a television set, or contributory processes to control mechanisms in complex metabolic pathways, such as the inhibitory function of the appropriate part of the lac-operon on the production of lactase through its action on the genome in the absence of lactose. We (...) would like a language broad enough, neutral enough, but yet powerful enough to cover all such cases, and at the same time to give a framework form explanation both of the family resemblances and differences. General logic and mathematics are too abstract, but more importantly, too broad, whereas other discourses of function, such as the biological and teleological contexts, are too narrow. Information is especially suited since it is mathematically grounded, but also has a wellknown physical interpretation through the Schr dinger/Brillouin Negentropy Principle of Information, and an engineering or design interpretation through Shannon's communication theory. My main focus will be on the functions of autonomous anticipatory systems, but I will try to demonstrate both the connections between this notion of function and the others, especially to dynamical systems with a physical interpretation on the one side and intentional systems on the other. The former are based in concepts like force, energy and work, while the latter involve notions like representation, control and purpose, traditionally, at least in Modern times, on opposite sides of the Cartesian divide. In principle, information can be reduced to energy, but it has the advantage of being more flexible, and easier to apply to higher level phenomena. (shrink)

Theoretical frames for analyzing information in biological and molecular multicomponent structures are proposed. The mathematical foundations of the proposal are presented. Both the information encoded in structures is defined and the method of calculating the amount of this information is introduced. The proposed approach is applied to the operation of a molecular multicomponent machine.

This book presents new insights into the nature of the human mind as a product of the brain. It does so by discussing how biological and technological information systems differ from their counterparts with physical functions, presenting Emergent Information Theory as a solution to the mind-body problem and overarching framework for all biological and technological information systems. This fascinating text will be of interest to any researcher of consciousness, the mind-body problem, or AI, as well as (...) those working in related areas such as physical neuroscience and systems theory. (shrink)

Providing a new conceptual scaffold for further research in biology and cognition, this book introduces the new field of cognitive biology, a systems biology approach showing that further progress in this field will depend on a deep recognition of developmental processes, as well as on the consideration of the developed organism as an agent able to modify and control its surrounding environment. The role of cognition, the means through which the organism is able to cope with its (...) environment, cannot be underestimated. In particular, it is shown that this activity is grounded on a theory of information based on Bayesian probabilities. The organism is considered as a cybernetic system able to integrate a processor as a source of variety (the genetic system), a regulator of its own homeostasis (the metabolic system), and a selecting system separating the self from the non-self (the membrane in unicellular organisms). Any organism is a complex system that can survive only if it is able to maintain its internal order against the spontaneous tendency towards disruption. Therefore, it is forced to monitor and control its environment and so to establish feedback circuits resulting in co-adaptation. Cognitive and biological processes are shown to be inseparable. (shrink)

John Maynard Smith has defended against philosophical criticism the view that developmental biology is the study of the expression of information encoded in the genes by natural selection. However, like other naturalistic concepts of information, this ‘teleosemantic’ information applies to many non-genetic factors in development. Maynard Smith also fails to show that developmental biology is concerned with teleosemantic information. Some other ways to support Maynard Smith’s conclusion are considered. It is argued that on any (...) definition of information the view that development is the expression of genetic information is misleading. Some reasons for the popularity of that view are suggested. (shrink)

A brief personal history is given about how information theory can be applied to binding sites of genetic control molecules on nucleic acids. The primary example used is ribosome binding sites in Escherichia coli. Once the sites are aligned, the information needed to describe the sites can be computed using Claude Shannon’s method. This is displayed by a computer graphic called a sequence logo. The logo represents an average binding site, and the mathematics easily allows one to (...) determine the components of this average. That is, given a set of binding sites, the information for individual binding sites can also be computed. One can go further and predict the information of sites that are not in the original data set. Information theory also allows one to model the flexibility of ribosome binding sites, and this led us to a simple model for ribosome translational initiation in which the molecular components fit together only when the ribosome is at a good ribosome binding site. Since information theory is general, the same mathematics applies to human splice junctions, where we can predict the effect of sequence changes that cause human genetic diseases and cancer. The second example given is the Pribnow “box,” which, when viewed by the information theory method, reveals a mechanism for initiation of both transcription and DNA replication. Replication, transcription, splicing, and translation into protein represent the central dogma, so these examples show how molecular information theory is contributing to our knowledge of basic biology. (shrink)

We discuss foundational issues of quantum information biology —one of the most successful applications of the quantum formalism outside of physics. QIB provides a multi-scale model of information processing in bio-systems: from proteins and cells to cognitive and social systems. This theory has to be sharply distinguished from “traditional quantum biophysics”. The latter is about quantum bio-physical processes, e.g., in cells or brains. QIB models the dynamics of information states of bio-systems. We argue that the (...) information interpretation of quantum mechanics is the most natural interpretation of QIB. Biologically QIB is based on two principles: adaptivity; openness. These principles are mathematically represented in the framework of a novel formalism— quantum adaptive dynamics which, in particular, contains the standard theory of open quantum systems. (shrink)

The question that probably emerges when the title of this work is read is if it is possible to establish any relation between philosophy and a scientific discipline such as molecular biology. The common opinion, shared even by many renowned biologists and philosophers, is that each of these disciplines has got its own without taking into account the results of the other. However, the relation between science and philosophy is nowadays one of the most challenging topics, where philosophers and (...) biologists meet and each other to better understand what life is and how it works. Philosophical concepts such as information, causality, semiotics and function can be seen as instruments for a philosophical approach to biological topics. The aim of this work is to see if, studying a biological example in depth, there are elements that fit with the informational paradigm that is proposed as a philosophical framework. Biology has been considered as a discipline in which objects can be reduced to the laws of physics and chemistry. A different approach can be seen in this work. The philosophy of Charles Sanders Peirce can help us to see biological systems as informational systems, where molecules are more than their chemical structure, indeed, the cell can deal with them from a semiotic point of view; that is, treating them as signs that stand for other molecules or processes, allowing the system to canalize all this information to its own benefit. (shrink)

In conclusion, then, we have tried to show that Drug actions can be predicted and described best on a probabilistic basis and information theory offers a suitable framework for such predictions. Drug actions are fundamentally of the all-or-none type involving the choice between two alternatives and these choises are therefore measurable by binary digits. Drug actions are not absolutely but only relatively specific and such specificity can be measured on the basis of information theory by an (...) array of suitable correlation data. Synergisms and antagonisms can best be explained and measured by considering them as intersymbol influences in communications. A theory of drug action based on information theory is more comprehensive and simpler than any theory based on the principles of classical physics and chemistry.However, these conclusions provide only the general basis for future detailed studies of various drug groups which will probably require the collaboration of chemists and pharmacologists as well as biological mathematicians to produce practical results.Der Verfasser bespricht die verschiedenen Probleme der Drogenwirkung und der Reizwirkung im allgemeinen und kommt zu den folgenden Schlussfolgerungen: Die Wirkung der Drogen kann am besten auf Grundlage der Wahrscheinlichkeitstheorie vorhergesagt und beschrieben werden und die mathematische Informationstheorie bietet einen befriedigenden Rahmen für solche Voraussagungen. Drogenwirkungen beruhen im Grunde genommen auf dem „Alles oder Nichts Prinzip”, d.h. sie beruhen auf einer Wahl zwischen zwei Alternativen und diese Wahlen sind als Logarithmen mit der Basis 2 messbar. Drogenwirkungen sind nicht absolut sondern nur relativ spezifisch und diese SpezifizitÄt kann auf Grundlage der Informationstheorie durch eine Matrize gernessen werden die eine Anordnung passender Korrelationsdaten enthÄlt. Synergismen und Antagonismen zwischen verschiedenen Substanzen können am besten dadurch erklÄrt und gemessen werden, dass man sie als gegenseitige Beeinflussung zwischen den eine Mitteilung bildenden Symbolen auffasst. Eine Theorie der Drogenwirkung auf der Informationstheorie basiert, ist umfassender und einfacher als irgend eine andere der die Prinzipien der klassischen Physik und Chemie zugrunde liegen.Jedoch bieten diese Schlussfolgerungen nur die allgemeine Grundlage für zukünftige detaillierte Studien der verschiedenen Drogenklassen und diese Studien werden die Mitarbeit der Chemiker, der Pharmakologen und der mathematisch eingestellten Biologen erfordern.L'auteur discute les divers aspects de l'action des drogues et des stimulus en général et arrive aux conclusions suivantes: La meilleure manière de prédire et de décrire l'action des drogues est celle qui se base sur la théorie des probabilités, et la théorie mathématique des informations et communications offre un cadre satisfaisant pour de telles prédictions. L'action des drogues est essentiellement du type „tout ou rien”, c'es-à-dire qu'un choix entre deux alternatives prend place et ces choix peuvent Être mesurés par des digits binaires. L'action des drogues est charactérisée non pas par une specificité absolue mais seulement relative et cette specificité peut Être mesurée sur base de la théorie des informations par une matrice contenant des données corrélatives convenables. Les synergismes et les antagonismes des substances agissant simultanément peuvent Être expliqués et mesurés en les considérant comme des influences, existantes entre les symboles constituant une communication. Une théorie pharmacodynamique basée sur la théorie des informations est plus compréhensive et plus simple qu'une théorie basée sur les principes de la physique et de la chimie classiques.Toutefois, ces conclusions ne fournissent que la base générale pour des études futures détaillées des diverses classes de substances pharmacologiques, et ces études demanderont la collaboration des chimistes, des pharmacologistes ainsi que des biologistes mathématiciens. (shrink)

BackgroundCurrent advances in biomedical research have introduced new ethical challenges in obtaining informed consent in low and middle-income settings. For example, there are controversies about the use of broad consent in the collection of biological samples for use in future biomedical research. However, few studies have explored preferred informed consent models for future use of biological samples in Malawi and South Africa. Therefore, we conducted an empirical study to understand preferred consent models among key stakeholders in biomedical studies that involve (...) collection of biological samples in Malawi and South Africa. The main objective of the study was to explore views of key stakeholders on current policies on informed consent in Malawi and South Africa. MethodsThis was a qualitative study involving in-depth interviews and focus group discussions. Thirty-four in-depth interviews and 6 focus group discussions were conducted with REC members, Funders, Policymakers, CAB members and Research Participants in Malawi and South Africa to gather their views on models of informed consent. The study was conducted in Cape Town, South Africa, and Blantyre and Lilongwe in Malawi.ResultsMost key stakeholders preferred broad consent and tiered consent to specific consent. Some participants expressed a strong preference for specific consent to other models of informed consent in biomedical research. Few participants did not have any preference for a consent model, opting for any consent model which provides adequate information about the proposed research and what their national consent regulations require. Finally, very few participants preferred blanket consent to other informed consent models.ConclusionsThis study aimed to help fill the gap in the scientific literature on key stakeholder views on consent models for future use of biological samples in Malawi and South Africa. The findings of the study have provided some evidence that may support policies on permissible consent models for future use of biological samples in sub-Saharan Africa considering the differences in informed consent regulations and guidelines. Finally, the findings can inform ongoing discussions on permissible consent models to be used for future use of biological samples. (shrink)

Cognition in living entities—and their social groupings or institutional artifacts—is necessarily as complicated as their embedding environments, which, for humans, includes a particularly rich cultural milieu. The asymptotic limit theorems of information and control theories permit construction of a new class of empirical ‘regression-like’ statistical models for cognitive developmental processes, their dynamics, and modes of dysfunction. Such models may, as have their simpler analogs, prove useful in the study and re-mediation of cognitive failure at and across the scales and (...) levels of organization that constitute and drive the phenomena of life. These new models particularly focus on the roles of sociocultural environment and stress, in a large sense, as both trigger for the failure of the regulation of bio-cognition and as ‘riverbanks’ determining the channels of pathology, with implications across life-course developmental trajectories. We examine the effects of an embedding cultural milieu and its socioeconomic implementations using the ‘lenses’ of metabolic optimization, control system theory, and an extension of symmetry-breaking appropriate to information systems. A central implication is that most, if not all, human developmental disorders are fundamentally culture-bound syndromes. This has deep implications for both individual treatment and public health policy. (shrink)

Integrating concepts of maintenance and of origins is essential to explaining biological diversity. The unified theory of evolution attempts to find a common theme linking production rules inherent in biological systems, explaining the origin of biological order as a manifestation of the flow of energy and the flow of information on various spatial and temporal scales, with the recognition that natural selection is an evolutionarily relevant process. Biological systems persist in space and time by transfor ming energy from (...) one state to another in a manner that generates structures which allows the system to continue to persist. Two classes of energetic transformations allow this; heat-generating transformations, resulting in a net loss of energy from the system, and conservative transformations, changing unusable energy into states that can be stored and used subsequently. All conservative transformations in biological systems are coupled with heat-generating transformations; hence, inherent biological production, or genealogical proesses, is positively entropic. There is a self-organizing phenomenology common to genealogical phenomena, which imparts an arrow of time to biological systems. Natural selection, which by itself is time-reversible, contributes to the organization of the self-organized genealogical trajectories. The interplay of genealogical (diversity-promoting) and selective (diversity-limiting) processes produces biological order to which the primary contribution is genealogical history. Dynamic changes occuring on times scales shorter than speciation rates are microevolutionary; those occuring on time scales longer than speciation rates are macroevolutionary. Macroevolutionary processes are neither redicible to, nor autonomous from, microevolutionary processes. (shrink)

The Shannon information function (H) has been extensively used in ecology as a statistic of species diversity. Yet, the use of Shannon diversity index has also been criticized, mainly because of its ambiguous ecological interpretation and because of its relatively great sensitivity to the relative abundances of species in the community. In my opinion, the major shortcoming of the traditional perspective (on the possible relation of species diversity with information theory) is that species need for an external (...) receiver (the scientist or ecologist) to exist and transmit information. Because organisms are self-catalized replicating structures that can transmit genotypic information to offspring, it should be evident that any single species has two possible states or alternatives: to be or not to be. In other words, species have no need for an external receiver since they are their own receivers. Therefore, the amount of biological information (at the species scale) in a community with one only species would be species, and not bits as in the traditional perspective. Moreover, species diversity appears to be a monotonic increasing function of (or S) when all species are equally probable (S being species richness), and not a function of as in the traditional perspective. To avoid the noted shortcoming, we could use 2H (instead of H) for calculating species diversity and species evenness (= 2H/S). However, owing to the relatively great sensitivity of H to the relative abundances of species in the community, the value of species dominance (= 1 − 2H/S) is unreasonably high when differences between dominant and subordinate species are considerable, thereby lowering the value of species evenness and diversity. This unsatisfactory behaviour is even more evident for Simpson index and related algorithms. I propose the use of other statistics for a better analysis of community structure, their relationship being: species evenness + species dominance = 1; species diversity × species uniformity = 1; and species diversity = species richness × species evenness. (shrink)

Information Theory, Evolution and The Origin ofLife: The Origin and Evolution of Life as a Digital Message: How Life Resembles a Computer, Second Edition. Hu- bert P. Yockey, 2005, Cambridge University Press, Cambridge: 400 pages, index; hardcover, US $60.00; ISBN: 0-521-80293-8. The reason that there are principles of biology that cannot be derived from the laws of physics and chemistry lies simply in the fact that the genetic information content of the genome for constructing even the (...) simplest organisms is much larger than the information content of these laws. Yockey in his previous book (1992, 335) In this new book, Information Theory, Evolution and The Origin ofLife, Hubert Yockey points out that the digital, segregated, and linear character of the genetic information system has a fundamental significance. If inheritance would blend and not segregate, Darwinian evolution would not occur. If inheritance would be analog, instead of digital, evolution would be also impossible, because it would be impossible to remove the effect of noise. In this way, life is guided by information, and so information is a central concept in molecular biology. The author presents a picture of how the main concepts of the genetic code were developed. He was able to show that despite Francis Crick's belief that the Central Dogma is only a hypothesis, the Central Dogma of Francis Crick is a mathematical consequence of the redundant nature of the genetic code. The redundancy arises from the fact that the DNA and mRNA alphabet is formed by triplets of 4 nucleotides, and so the number of letters (triplets) is 64, whereas the proteome alphabet has only 20 letters (20 amino acids), and so the translation from the larger alphabet to the smaller one is necessarily redundant. Except for Tryptohan and Methionine, all amino acids are coded by more than one triplet, therefore, it is undecidable which source code letter was actually sent from mRNA. This proof has a corollary telling that there are no such mathematical constraints for protein-protein communication. With this clarification, Yockey contributes to diminishing the widespread confusion related to such a central concept like the Central Dogma. Thus the Central Dogma prohibits the origin of life "proteins first." Proteins can not be generated by "self-organization." Understanding this property of the Central Dogma will have a serious impact on research on the origin of life. (shrink)

This paper provides an overview of developments in a dual processing theory of automatic and controlled processing that began with the empirical and theoretical work described by Schneider and Shiffrin (1977) and Shiffrin and Schneider (1977) over a quarter century ago. A review of relevant empirical findings suggests that there is a set of core behavioral phenomena reflecting differences between controlled and automatic processing that must be addressed by a successful theory. These phenomena relate to: consistency in training, (...) serial versus parallel processing, level of effort, robustness to stressors, degree of control, effects on long‐term memory, and priority encoding. We detail a computational model of controlled processing, CAP2, that accounts for these phenomena as emergent properties of an underlying hybrid computational architecture. The model employs a large network of distributed data modules that can categorize, buffer, associate, and prioritize information. Each module is a connectionist network with input and output layers, and each module communicates with a central Control System by outputting priority and activity report signals, and by receiving control signals. The Control System is composed of five processors including a Goal Processor, an Attention Controller, an Activity Monitor, an Episodic Store, and a Gating & Report Relay. The transition from controlled to automatic processing occurs in this model as the data modules become capable of transmitting their output without mediation by the Control System. We describe recent progress in mapping the components of this model onto specific neuroanatomical substrates, briefly discuss the potential for applying functional neuroimaging techniques to test the model's predictions, and its relation to other models. (shrink)

In 1958, Francis Crick distinguished the flow of information from the flow of matter and the flow of energy in the mechanism of protein synthesis. Crick’s claims about information flow and coding in molecular biology are viewed from the perspective of a new characterization of mechanisms and from the perspective of information as holding a key to distinguishing work in molecular biology from that of biochemistry in the 1950s–1970s . Flow of matter from beginning to (...) end does not occur in the protein synthesis mechanism; flow of information does. The flow of information and coding in molecular biological mechanisms are distinguished, on the one hand, from formal information theory, and, on the other, from information as used in cognitive neuroscience, where information and representation are often coupled. (shrink)

The partner choice approach to understanding the evolution of cooperation builds on approaches that focus on partner control by considering processes that occur prior to pair or group formation. Proponents of the partner choice approach rightly note that competition to be chosen as a partner can help solve the puzzle of cooperation. I aim to build on the partner choice approach by considering the role of signalling in partner choice. Partnership formation often requires reliable information. Signalling is thus important (...) in the context of partner choice. However, the issue of signal reliability has been understudied in the partner choice literature. The issue deserves attention because – despite what proponents of the partner choice approach sometimes claim – that approach does face a cheater problem, which we might call the problem of false advertising in biological markets. Both theoretical and empirical work is needed to address this problem. I will draw on signalling theory to provide a theoretical framework within which to organise the scattered discussions of the false advertising problem extant in the partner choice literature. I will end by discussing some empirical work on cooperation, partner choice, and punishment among humans. (shrink)

Living organisms are exposed to numerous influencing factors. This holds also true for their infrastructures that are processing and transducing information like endocrine networks or nerval channels. Therefore, the ability to compensate for noise is crucial for survival. An efficient mechanism to neutralise disturbances is instantiated in form of parallel complementary communication channels exerting antagonistic effects at their common receivers. Different signal processing types share the ability to suppress noise, to widen the system’s regulation capacity, and to provide for (...) variable gains while leaving the transferred signal to a large extent unchanged. (shrink)

The INBIOSA project brings together a group of experts across many disciplines who believe that science requires a revolutionary transformative step in order to address many of the vexing challenges presented by the world. It is INBIOSA’s purpose to enable the focused collaboration of an interdisciplinary community of original thinkers. This paper sets out the case for support for this effort. The focus of the transformative research program proposal is biology-centric. We admit that biology to date has been (...) more fact-oriented and less theoretical than physics. However, the key leverageable idea is that careful extension of the science of living systems can be more effectively applied to some of our most vexing modern problems than the prevailing scheme, derived from abstractions in physics. While these have some universal application and demonstrate computational advantages, they are not theoretically mandated for the living. A new set of mathematical abstractions derived from biology can now be similarly extended. This is made possible by leveraging new formal tools to understand abstraction and enable computability. [The latter has a much expanded meaning in our context from the one known and used in computer science and biology today, that is "by rote algorithmic means", since it is not known if a living system is computable in this sense (Mossio et al., 2009).] Two major challenges constitute the effort. The first challenge is to design an original general system of abstractions within the biological domain. The initial issue is descriptive leading to the explanatory. There has not yet been a serious formal examination of the abstractions of the biological domain. What is used today is an amalgam; much is inherited from physics (via the bridging abstractions of chemistry) and there are many new abstractions from advances in mathematics (incentivized by the need for more capable computational analyses). Interspersed are abstractions, concepts and underlying assumptions “native” to biology and distinct from the mechanical language of physics and computation as we know them. A pressing agenda should be to single out the most concrete and at the same time the most fundamental process-units in biology and to recruit them into the descriptive domain. Therefore, the first challenge is to build a coherent formal system of abstractions and operations that is truly native to living systems. Nothing will be thrown away, but many common methods will be philosophically recast, just as in physics relativity subsumed and reinterpreted Newtonian mechanics. -/- This step is required because we need a comprehensible, formal system to apply in many domains. Emphasis should be placed on the distinction between multi-perspective analysis and synthesis and on what could be the basic terms or tools needed. The second challenge is relatively simple: the actual application of this set of biology-centric ways and means to cross-disciplinary problems. In its early stages, this will seem to be a “new science”. This White Paper sets out the case of continuing support of Information and Communication Technology (ICT) for transformative research in biology and information processing centered on paradigm changes in the epistemological, ontological, mathematical and computational bases of the science of living systems. Today, curiously, living systems cannot be said to be anything more than dissipative structures organized internally by genetic information. There is not anything substantially different from abiotic systems other than the empirical nature of their robustness. We believe that there are other new and unique properties and patterns comprehensible at this bio-logical level. The report lays out a fundamental set of approaches to articulate these properties and patterns, and is composed as follows. -/- Sections 1 through 4 (preamble, introduction, motivation and major biomathematical problems) are incipient. Section 5 describes the issues affecting Integral Biomathics and Section 6 -- the aspects of the Grand Challenge we face with this project. Section 7 contemplates the effort to formalize a General Theory of Living Systems (GTLS) from what we have today. The goal is to have a formal system, equivalent to that which exists in the physics community. Here we define how to perceive the role of time in biology. Section 8 describes the initial efforts to apply this general theory of living systems in many domains, with special emphasis on crossdisciplinary problems and multiple domains spanning both “hard” and “soft” sciences. The expected result is a coherent collection of integrated mathematical techniques. Section 9 discusses the first two test cases, project proposals, of our approach. They are designed to demonstrate the ability of our approach to address “wicked problems” which span across physics, chemistry, biology, societies and societal dynamics. The solutions require integrated measurable results at multiple levels known as “grand challenges” to existing methods. Finally, Section 10 adheres to an appeal for action, advocating the necessity for further long-term support of the INBIOSA program. -/- The report is concluded with preliminary non-exclusive list of challenging research themes to address, as well as required administrative actions. The efforts described in the ten sections of this White Paper will proceed concurrently. Collectively, they describe a program that can be managed and measured as it progresses. (shrink)

Information about the environment is captured in human biological systems on a variety of interacting levels – in distributions of genes, linguistic particulars, concepts, methods, theories, preferences, and overt behaviors. I investigate some of the basic principles which govern such a hierarchy by constructing a comparatively simple three-level selection model of bee foraging preferences and behaviors. The information-theoretic notion of ''''mutual information'''' is employed as a measure of efficiency in tracking a changing environment, and its appropriateness in (...) epistemological applications is discussed at some length. In particular, information accumulated in mid-level preference distributions exhibits suggestive properties for the purposes of naturalistic epistemology. It also appears that the novelty of scientific objects and representations and the rapidity of scientific change relative to genetic change need present no obstacle to the use of such models in explanations of scientific progress and the reliability of scientific judgement. (shrink)

A cluster of similar trends emerging in separate fields of science and philosophy points to new opportunities to apply biosemiotic ideas as tools for conceptual integration in theoretical biology. I characterize these developments as the outcome of a “relational turn” in these disciplines. They signal a shift of attention away from objects and things and towards relational structures and processes. Increasingly sophisticated research technologies of molecular biology have generated an enormous quantity of experimental data, sparking a need for (...) relational approaches that could help to find recurrent patterns in the mass of data. Earlier conceptions of relational biology and cybernetics, once deemed too abstract and speculative, are now resurrected and applied by means of new computational and simulation tools. I think this receptivity should be extended to incorporate nets of semiotic relations as heuristic guides for discerning global patterns of interactions in living systems. In this article I review aspects of systems biology and new directions in evolutionary theory, focusing on the role of circular and downward causation in relational structures and dynamical networks. I also indicate promising avenues of integration of some ideas of biosemiotics with those emerging from these new currents in biology. Relational developments in biology bear a telling similarity to a parallel relational turn presently manifest in the philosophy of science, rooted in the philosophy of physics and mathematics and in different varieties of structural and informational realism. The recognition of the relational nature of reality within these disciplines entails a tacit repudiation of nominalistic biases in science that have hindered the reception of semitiotic conceptions in biology. In previous investigations I explored connections between two kinds of relational structures: the networks of self-referential circular loops that appear pervasively in living systems, and the triadic relational structures that Peircean semiotics places at the basis of all semiotic transactions. Current relational views in the sciences seem oblivious to the difference between dyadic and triadic relations. Incorporating this essential distinction from biosemiotics into other fields could be a first step in seizing the opportunities opened by the relational turn for a renewal of biology and of natural philosophy in general, across disciplinary boundaries. (shrink)

Marjorie Grene (1910-2009) and David Hull (1935-2010) were among the most influential voices in late twentieth-century philosophy of biology. But, as Grene and Hull pointed out in published discussions of one another’s work over the course of nearly forty years, they disagreed strongly on fundamental issues. Among these contested issues is the role of what is sometimes called “typology” and “typological thinking” in biology. In regard to taxonomy and the species problem, Hull joined Ernst Mayr’s construal of typological (...) thinking as a backward relic of pre-Darwinian science that should be overcome. Grene, however, treated the suspicion of typological thinking that characterized Hull’s views, as well as those of other architects of the New Evolutionary Synthesis, as itself suspicious and even unsustainable. In this paper I review three debates between Grene and Hull bearing on the question of the validity of so-called typological thinking in biology: (1) a debate about the dispensability of concepts of “type” within evolutionary theory, paleontology, and taxonomy; (2) a debate about whether species can be adequately understood as individuals, and thereby independently of those forms of thinking Hull and Mayr had construed as “typological”; and (3) a debate about the prospects of a biologically informed theory of human nature. (shrink)

The carbon emissions of global health care activities make up 4–5% of total world emissions, placing it on par with the food sector. Carbon emissions are particularly relevant for health care because of climate change health hazards. Doctors and health care professionals must connect their health care delivery with carbon emissions and minimize resource use when possible as a part of their obligation to do no harm. Given that reducing carbon is a global ethical priority, the informed consent process in (...) health care delivery must change. I argue that the expanded role of bioethicists in this climate crisis is to promote and support “green informed consent:” the sharing of climate information with patients, offering options for lower-carbon health care, and accepting the patient’s right to decline treatments which are deemed too carbon intensive for their values. (shrink)

Besides mechanistic explanations of phenomena, which have been seriously investigated in the last decade, biology and ecology also include explanations that pinpoint specific mathematical properties as explanatory of the explanandum under focus. Among these structural explanations, one finds topological explanations, and recent science pervasively relies on them. This reliance is especially due to the necessity to model large sets of data with no practical possibility to track the proper activities of all the numerous entities. The paper first defines topological (...) explanations and then explains why topological explanations and mechanisms are different in principle. Then it shows that they are pervasive both in the study of networks—whose importance has been increasingly acknowledged at each level of the biological hierarchy—and in contexts where the notion of selective neutrality is crucial; this allows me to capture the difference between mechanisms and topological explanations in terms of practical modelling practices. The rest of the paper investigates how in practice mechanisms and topologies are combined. They may be articulated in theoretical structures and explanatory strategies, first through a relation of constraint, second in interlevel theories, or they may condition each other. Finally, I explore how a particular model can integrate mechanistic informations, by focusing on the recent practice of merging networks in ecology and its consequences upon multiscale modelling. (shrink)

Metaphor influences the construction of biological models and theories and the analysis of its use can reveal important tools of thought. Some aspects of biological organisation are investigated through the analysis of metaphors associated with treating biosystems as a kind of text. In particular, the use of glue and verbs is considered. Some of the reasons why glue is important in the construction of hierarchies are pursued in the light of specific examples, and some of the conceptual links between glue (...) in biology and other domains is discussed. Verbs are shown to be important in the construction of networks. Some of the relations between glue, verb and text are considered and the text metaphor is placed within a much broader context of ideas associated with form, relation and system. The paper concludes with comments on the nature of biological information and the need for extending or better understanding the verbal vocabulary. (shrink)

Traditional approaches in philosophy of biology focus attention on biological concepts, explanations, and theories, on evidential support and inter-theoretical relations. Newer approaches shift attention from concepts to conceptual practices, from theories to practices of theorizing, and from theoretical reduction to reductive retooling. In this article, I describe the shift from theory-focused to practice-centered philosophy of science and explain how it is leading philosophers to abandon fundamentalist assumptions associated with traditional approaches in philosophy of science and to embrace scientific (...) pluralism. This article comes in three parts, each illustrating the shift from theory-focused to practice-centered epistemology. The first illustration shows how shifting philosophical attention to conceptual practice reveals how molecular biologists succeed in identifying coherent causal strands within systems of bewildering complexity. The second illustration suggests that analyzing how a multiplicity of alternative models function in practice provides an illuminating approach for understanding the nature of theoretical knowledge in evolutionary biology. The third illustration demonstrates how framing reductionism in terms of the reductive retooling of practice offers an informative perspective for understanding why putting DNA at the center of biological research has been incredibly productive throughout much of biology. Each illustration begins by describing how traditional theory-focused philosophical approaches are laden with fundamentalist assumptions and then proceeds to show that shifting attention to practice undermines these assumptions and motivates a philosophy of scientific pluralism. (shrink)

The philosophy of biology should move to the center of the philosophy of science - a place it has not been accorded since the time of Mach. Physics was the paradigm of science, and its shadow falls across con temporary philosophy of biology as well, in a variety of contexts: reduction, organization and system, biochemical mechanism, and the models of law and explanation which derive from the Duhem-Popper Hempel tradition. This volume, we think, offers ample evidence of how (...) good contempo rary work in the philosophical understanding of biology has become. Marjorie Grene and Everett Mendelsohn aptly combine a deep philo sophical appreciation of conceptual issues in biology with an historical understanding of the radical changes in the science of biology since the 19th century. In this book, they present essays which probe such historical and methodological questions as reducibility, levels of organization, function and teleology, and the range of issues emerging from evolution ary theory and the species problem. In conjunction with Professor Grene's collection of essays on the philosophy of biology, The Under standing of Nature (Boston Studies in the Philosophy of Science, Vol. XXIII) and the occasional essays on these topics which we have published in other volumes (listed below), this volume contributes to bringing biology to the center of philosophical attention. Everett Mendelsohn, 'Explanation in Nineteenth Century Biology' (Boston Studies, Vol. II, 1965). David Hawkins, 'Taxonomy and Information', (Boston Studies, Vol. III, 1967). (shrink)

Based on a conference on the nature and origin of biological information held at Cornell University in 2011, this edited volume presents new research by experts in information theory, computer science, numerical simulation, thermodynamics, evolutionary theory, whole organism biology, developmental biology, molecular biology, genetics, physics, biophysics, mathematics, and linguistics.

The INBIOSA project brings together a group of experts across many disciplines who believe that science requires a revolutionary transformative step in order to address many of the vexing challenges presented by the world. It is INBIOSA’s purpose to enable the focused collaboration of an interdisciplinary community of original thinkers. This paper sets out the case for support for this effort. The focus of the transformative research program proposal is biology-centric. We admit that biology to date has been (...) more fact-oriented and less theoretical than physics. However, the key leverageable idea is that careful extension of the science of living systems can be more effectively applied to some of our most vexing modern problems than the prevailing scheme, derived from abstractions in physics. While these have some universal application and demonstrate computational advantages, they are not theoretically mandated for the living. A new set of mathematical abstractions derived from biology can now be similarly extended. This is made possible by leveraging new formal tools to understand abstraction and enable computability. [The latter has a much expanded meaning in our context from the one known and used in computer science and biology today, that is "by rote algorithmic means", since it is not known if a living system is computable in this sense (Mossio et al., 2009).] Two major challenges constitute the effort. The first challenge is to design an original general system of abstractions within the biological domain. The initial issue is descriptive leading to the explanatory. There has not yet been a serious formal examination of the abstractions of the biological domain. What is used today is an amalgam; much is inherited from physics (via the bridging abstractions of chemistry) and there are many new abstractions from advances in mathematics (incentivized by the need for more capable computational analyses). Interspersed are abstractions, concepts and underlying assumptions “native” to biology and distinct from the mechanical language of physics and computation as we know them. A pressing agenda should be to single out the most concrete and at the same time the most fundamental process-units in biology and to recruit them into the descriptive domain. Therefore, the first challenge is to build a coherent formal system of abstractions and operations that is truly native to living systems. Nothing will be thrown away, but many common methods will be philosophically recast, just as in physics relativity subsumed and reinterpreted Newtonian mechanics. -/- This step is required because we need a comprehensible, formal system to apply in many domains. Emphasis should be placed on the distinction between multi-perspective analysis and synthesis and on what could be the basic terms or tools needed. The second challenge is relatively simple: the actual application of this set of biology-centric ways and means to cross-disciplinary problems. In its early stages, this will seem to be a “new science”. This White Paper sets out the case of continuing support of Information and Communication Technology (ICT) for transformative research in biology and information processing centered on paradigm changes in the epistemological, ontological, mathematical and computational bases of the science of living systems. Today, curiously, living systems cannot be said to be anything more than dissipative structures organized internally by genetic information. There is not anything substantially different from abiotic systems other than the empirical nature of their robustness. We believe that there are other new and unique properties and patterns comprehensible at this bio-logical level. The report lays out a fundamental set of approaches to articulate these properties and patterns, and is composed as follows. -/- Sections 1 through 4 (preamble, introduction, motivation and major biomathematical problems) are incipient. Section 5 describes the issues affecting Integral Biomathics and Section 6 -- the aspects of the Grand Challenge we face with this project. Section 7 contemplates the effort to formalize a General Theory of Living Systems (GTLS) from what we have today. The goal is to have a formal system, equivalent to that which exists in the physics community. Here we define how to perceive the role of time in biology. Section 8 describes the initial efforts to apply this general theory of living systems in many domains, with special emphasis on crossdisciplinary problems and multiple domains spanning both “hard” and “soft” sciences. The expected result is a coherent collection of integrated mathematical techniques. Section 9 discusses the first two test cases, project proposals, of our approach. They are designed to demonstrate the ability of our approach to address “wicked problems” which span across physics, chemistry, biology, societies and societal dynamics. The solutions require integrated measurable results at multiple levels known as “grand challenges” to existing methods. Finally, Section 10 adheres to an appeal for action, advocating the necessity for further long-term support of the INBIOSA program. -/- The report is concluded with preliminary non-exclusive list of challenging research themes to address, as well as required administrative actions. The efforts described in the ten sections of this White Paper will proceed concurrently. Collectively, they describe a program that can be managed and measured as it progresses. (shrink)

It is generally agreed that organisms are Complex Adaptive Systems. Since the rise of Cybernetics in the middle of the last century ideas from information theory and control theory have been applied to the adaptations of biological organisms in order to explain how they work. This does not, however, explain functionality, which is widely but not universally attributed to biological systems. There are two approaches to functionality, one based on etiology (what a trait was selected for), and (...) the other based in autonomy. I argue that the etiological approach, as understood in terms of control theory, suffers from a problem of symmetry, by which function can equally well be placed in the environment as in the organism. Focusing on the autonomy view, I note that it can be understood to some degree in terms of control theory in its version called second order cybernetics. I present an approach to second order cybernetics that seems plausible for organisms with limited computational power, due to Hooker, Penfold and Evans. They hold that this approach gives something like concepts, certainly abstractions from specific situations, a trait required for functionality in its system adaptive form (i.e., control of the system by itself). Using this cue, I argue that biosemiotics provides the methodology to incorporate these quasi concepts into an account of functionality. (shrink)

Waters’s (2007) actual difference making and Weber’s (2013, 2017) biological normality approaches to causal selection have received many criticisms, some of which miss their target. Disagreement about whether Waters’s and Weber’s views succeed in providing criteria that uniquely singles out the gene as explanatorily significant in biology has led philosophers to overlook a prior problem. Before one can address whether Waters’s and Weber’s views successfully account for the explanatory significance of genes, one must ask whether either view satisfactorily meets (...) the necessary conditions for causal selection in the first place. An adequate defense of causal selection must meet two desiderata. First, there must be an explanatory property that sets some causes apart from others. Second, the property identified must be one that is recognized by biologists as relevant to their domain(s) of inquiry. I argue that both fall short of meeting the second condition. I demonstrate this by showing how many of the biological technologies crucial to experimentation do not fit either view very well. I offer a more adequate proposal that accommodates non-actual and artificial causal variables. A consequence of my view is the following: When analyzing the causal selection practices of biologists, philosophers should consider the explanatory targets relevant to a research program – including ones whose explanans must appeal to biological technologies. I then explain how this proposal can inform the existing debate between Weber (2017) and Griffiths et al. (2015). (shrink)

To explain their role in discovery and contrast them with theory-driven research, philosophers of science have characterized exploratory experiments in terms of what they lack: namely, that they lack direction from what have been called “local theories” of the target system or object under investigation. I argue that this is incorrect: it’s not whether or not there is direction from a local theory that matters, but instead how such a theory is used to direct an experiment that (...) matters. Appealing to contemporary exploratory experiments that involve the use of experimental techniques—specifically, examples where scientists explore the interaction of neural activity and human behavior by magnetically stimulating brains—I argue that local theories of a target system can inform auxiliary hypotheses in exploratory experiments, which direct these experiments. These examples illustrate how local theories can direct the exploration of target systems where researchers do not aim to evaluate these theories. (shrink)

Causal selection is the task of picking out, from a field of known causally relevant factors, some factors as elements of an explanation. The Causal Parity Thesis in the philosophy of biology challenges the usual ways of making such selections among different causes operating in a developing organism. The main target of this thesis is usually gene centrism, the doctrine that genes play some special role in ontogeny, which is often described in terms of information-bearing or programming. This (...) paper is concerned with the attempt of confronting the challenge coming from the Causal Parity Thesis by offering principles of causal selection that are spelled out in terms of an explicit philosophical account of causation, namely an interventionist account. I show that two such accounts that have been developed, although they contain important insights about causation in biology, nonetheless fail to provide an adequate reply to the Causal Parity challenge: Ken Waters's account of actual-difference making and Jim Woodward's account of causal specificity. A combination of the two also doesn't do the trick, nor does Laura Franklin-Hall's account of explanation (in this volume). We need additional conceptual resources. I argue that the resources we need consist in a special class of counterfactual conditionals, namely counterfactuals the antecedents of which describe biologically normal interventions. (shrink)

RESUMEN Con el objetivo de fundamentar la importancia de la teoría biológica del conocimiento de Humberto Maturana, Francisco Varela y sus seguidores para comprender la articulación entre los fenómenos biológicos y sociales, se aplicaron los métodos del nivel teórico analítico-sintético, inductivo-deductivo, histórico-lógico y ascensión de lo abstracto a lo concreto, con la intención de sistematizar información proveniente de la bibliografía consultada y de la experiencia profesional del autor, con énfasis en la formación de masters y doctores en pedagogía. Desde esta (...) posición teórica, se explica la aparición de las formas básicas de la cognición en el operar de sistemas autopoiéticos y la su importancia que, en la evolución hacia formas más complejas como la conciencia reflexiva, tuvo la coordinación del comportamiento para un acoplamiento estructural conjunto al entorno. Se realizan valoraciones sobre el posicionamiento de esta teoría en el contexto de la filosofía, sociología, psicología y de las ciencias de la educación contemporáneas. ABSTRACT The importance of the biological theory of the knowledge, for understanding the existent articulation between the biological and social phenomena, are explained. Methods of the theoretic level to systematize information obtained from the bibliography and from the vocational experience of the author, with emphasis in doctors' and masters' formation in pedagogy were used. From this theoretic position, the appearing of the elemental forms of the cognition in the operation of the autopoietic systems and the importance of the coordination of the behaviour for a join structural connection with the environment, for the evolution toward more complexes forms like the reflexive conscience are explained. Some valuations about the positioning of this theory in the contemporary context of the philosophy, sociology, psychology and the sciences of the education are presented. (shrink)

Modern life sciences research is increasingly relying on artificial intelligence (AI) approaches to model biological systems, primarily centered around the use of machine learning (ML) models. Although ML is undeniably useful for identifying patterns in large, complex data sets, its widespread application in biological sciences represents a significant deviation from traditional methods of scientific inquiry. As such, the interplay between these models and scientific understanding in biology is a topic with important implications for the future of scientific research, yet (...) it is a subject that has received little attention. Here, we draw from an epistemological toolkit to contextualize recent applications of ML in biological sciences under modern philosophical theories of understanding, identifying general principles that can guide the design and application of ML systems to model biological phenomena and advance scientific knowledge. We propose that conceptions of scientific understanding as information compression, qualitative intelligibility, and dependency relation modelling provide a useful framework for interpreting ML-mediated understanding of biological systems. Through a detailed analysis of two key application areas of ML in modern biological research – protein structure prediction and single cell RNA-sequencing – we explore how these features have thus far enabled ML systems to advance scientific understanding of their target phenomena, how they may guide the development of future ML models, and the key obstacles that remain in preventing ML from achieving its potential as a tool for biological discovery. Consideration of the epistemological features of ML applications in biology will improve the prospects of these methods to solve important problems and advance scientific understanding of living systems. (shrink)

Developing models of biological mechanisms, such as those involved in respiration in cells, often requires collaborative effort drawing upon techniques developed and information generated in different disciplines. Biochemists in the early decades of the 20th century uncovered all but the most elusive chemical operations involved in cellular respiration, but were unable to align the reaction pathways with particular structures in the cell. During the period 1940-1965 cell biology was emerging as a new discipline and made distinctive contributions to (...) understanding the role of the mitochondrion and its component parts in cellular respiration. In particular, by developing techniques for localizing enzymes or enzyme systems in specific cellular components, cell biologists provided crucial information about the organized structures in which the biochemical reactions occurred. Although the idea that biochemical operations are intimately related to and depend on cell structures was at odds with the then-dominant emphasis on systems of soluble enzymes in biochemistry, a reconceptualization of energetic processes in the 1960s and 1970s made it clear why cell structure was critical to the biochemical account. This paper examines how numerous excursions between biochemistry and cell biology contributed a new understanding of the mechanism of cellular respiration. (shrink)

Biologists rely heavily on the language of information, coding, and transmission that is commonplace in the field of information theory developed by Claude Shannon, but there is open debate about whether such language is anything more than facile metaphor. Philosophers of biology have argued that when biologists talk about information in genes and in evolution, they are not talking about the sort of information that Shannon’s theory addresses. First, philosophers have suggested that Shannon’s (...) theory is only useful for developing a shallow notion of correlation, the so-called causal sense of information. Second, they typically argue that in genetics and evolutionary biology, information language is used in a semantic sense, whereas semantics are deliberately omitted from Shannon’s theory. Neither critique is well-founded. Here we propose an alternative to the causal and semantic senses of information: a transmission sense of information, in which an object X conveys information if the function of X is to reduce, by virtue of its sequence properties, uncertainty on the part of an agent who observes X. The transmission sense not only captures much of what biologists intend when they talk about information in genes, but also brings Shannon’s theory back to the fore. By taking the viewpoint of a communications engineer and focusing on the decision problem of how information is to be packaged for transport, this approach resolves several problems that have plagued the information concept in biology, and highlights a number of important features of the way that information is encoded, stored, and transmitted as genetic sequence. (shrink)

Although contemporary metaphysics has recently undergone a neo-Aristotelian revival wherein dispositions, or capacities are now commonplace in empirically grounded ontologies, being routinely utilised in theories of causality and modality, a central Aristotelian concept has yet to be given serious attention – the doctrine of hylomorphism. The reason for this is clear: while the Aristotelian ontological distinction between actuality and potentiality has proven to be a fruitful conceptual framework with which to model the operation of the natural world, the distinction between (...) form and matter has yet to similarly earn its keep. In this chapter, I offer a first step toward showing that the hylomorphic framework is up to that task. To do so, I return to the birthplace of that doctrine - the biological realm. Utilising recent advances in developmental biology, I argue that the hylomorphic framework is an empirically adequate and conceptually rich explanatory schema with which to model the nature of organisms. (shrink)