An astonishingly diverse biomolecular circuitry orchestrates the functioning machinery underlying every living cell. These biomolecules and their circuits have been engineered not only for various industrial applications but also to perform other atypical functions that they were not evolved for—including computation. Various kinds of computational challenges, such as solving NP‐complete problems with many variables, logical computation, neural network operations, and cryptography, have all been attempted through this unconventional computing paradigm. In this review, we highlight key experiments across three different ‘‘eras’’ (...) of molecular computation, beginning with molecular solutions, transitioning to logic circuits and ultimately, more complex molecular networks. We also discuss a variety of applications of molecular computation, from solving NP‐hard problems to self‐assembled nanostructures for delivering molecules, and provide a glimpse into the exciting potential that molecular computing holds for the future. Also see the video abstract here: https://youtu.be/9Mw0K0vCSQw. (shrink)

It is proposed that the controlling system of the nerve cell is a molecular quantum device with an inner point of view. For the description of such a system it is necessary to create new science.

This paper argues in defense of theanti-reductionist consensus in the philosophy ofbiology. More specifically, it takes issues with AlexRosenberg's recent challenge of this position. Weargue that the results of modern developmentalgenetics rather than eliminating the need forfunctional kinds in explanations of developmentactually reinforce their importance.

Explanation is commonly considered one of the central goals of science. Although computer simulations have become an important tool in many scientific areas, various philosophical concerns indicate that their explanatory power requires further scrutiny. We examine a case study in which atomistic simulations have been used to examine the factors responsible for the transport selectivity of certain channel proteins located at cell membranes. By elucidating how precisely atomistic simulations helped scientists draw inferences about the molecular system under investigation, (...) we respond to some concerns regarding their explanatory power. We argue that atomistic simulations can be tools for managing molecular complexity and for systematically assessing how the occurrence of the explanandum is sensitive to a range of factors. (shrink)

The SARS‐CoV‐2 virus is responsible for the COVID‐19 pandemic the world experience since 2019. The protein responsible for the first steps of cell invasion, the spike protein, has probably received the most attention in light of its central role during infection. Computational approaches are among the tools employed by the scientific community in the enormous effort to study this new affliction. One of these methods, namely molecular dynamics (MD), has been used to characterize the function of the spike protein (...) at the atomic level and unveil its structural features from a dynamic perspective. In this review, we focus on these main findings, including spike protein flexibility, rare S protein conformational changes, cryptic epitopes, the role of glycans, drug repurposing, and the effect of spike protein variants. (shrink)

Molecular biology is a relatively new and very successful branch of science but currently it faces challenges posed by very complex issues that cannot be addressed by a traditional reductionist approach. However, despite its origins in the providential shift of some theoretical physicists to biology, currently molecular biology is immersed in a blind trend in which high-throughput technology, able to generate trillions of data, is becoming the leading edge of a discipline that has traded rational and critical thinking (...) for computer power, data crunching and statistics in hope of finding, once more, its way. However, the complex questions facing MB may only be solved by a paradigm shift in the causal way of thinking, so that complex, emergent, non-linear phenomena may be effectively understood in top-down and not in bottom-up terms. (shrink)

This paper is the result of the research I undertook at Lancaster University with a Marie Curie Fellowship during the academic years 2000‐2002. The objective of this research was to study the limits and the challenges of the analogy between molecular geneticists’ work and hackers’ activities. By focusing on this analogy I aim to explore the different ethical and philosophical issues surrounding new genetics and its IPR regulations. The paper firstly will show the philosophical background lying behind the proposed (...) analogy and analyses the sense in which we can talk of geneticists as “hackers.” It will provide grounds for the analogy by exploring some of the techniques used by geneticists; in particular it will focus on the so‐called Shotgun method for genomic sequencing. After having provided reasons for the proposed analogy I will claim that the open source philosophy used in the computer field would be a good way to regulate research in the genetics and in pharmaceutical field too. The open source philosophy would provide fair distribution of research opportunities around the globe with the shift from patenting to copyright in sensitive fields such as genetics. (shrink)

Molecular systems orchestrating the biology of the cell typically involve a complex web of interactions among various components and span a vast range of spatial and temporal scales. Computational methods have advanced our understanding of the behavior of molecular systems by enabling us to test assumptions and hypotheses, explore the effect of different parameters on the outcome, and eventually guide experiments. While several different mathematical and computational methods are developed to study molecular systems at different spatiotemporal scales, (...) there is still a need for methods that bridge the gap between spatially‐detailed and computationally‐efficient approaches. In this review, we summarize the capabilities of agent‐based modeling (ABM) as an emerging molecular systems biology technique that provides researchers with a new tool in exploring the dynamics of molecular systems/pathways in health and disease. (shrink)

In the last few years, biologists and computer scientists have claimed that the introduction of data science techniques in molecular biology has changed the characteristics and the aims of typical outputs (i.e. models) of such a discipline. In this paper we will critically examine this claim. First, we identify the received view on models and their aims in molecular biology. Models in molecular biology are mechanistic and explanatory. Next, we identify the scope and aims of data (...) science (machine learning in particular). These lie mainly in the creation of predictive models which performances increase as data set increases. Next, we will identify a tradeoff between predictive and explanatory performances by comparing the features of mechanistic and predictive models. Finally, we show how this a priori analysis of machine learning and mechanistic research applies to actual biological practice. This will be done by analyzing the publications of a consortium—The Cancer Genome Atlas—which stands at the forefront in integrating data science and molecular biology. The result will be that biologists have to deal with the tradeoff between explaining and predicting that we have identified, and hence the explanatory force of the ‘new’ biology is substantially diminished if compared to the ‘old’ biology. However, this aspect also emphasizes the existence of other research goals which make predictive force independent from explanation. (shrink)

In the last few years, biologists and computer scientists have claimed that the introduction of data science techniques in molecular biology has changed the characteristics and the aims of typical outputs (i.e. models) of such a discipline. In this paper we will critically examine this claim. First, we identify the received view on models and their aims in molecular biology. Models in molecular biology are mechanistic and explanatory. Next, we identify the scope and aims of data (...) science (machine learning in particular). These lie mainly in the creation of predictive models which performances increase as data set increases. Next, we will identify a tradeoff between predictive and explanatory performances by comparing the features of mechanistic and predictive models. Finally, we show how this a priori analysis of machine learning and mechanistic research applies to actual biological practice. This will be done by analyzing the publications of a consortium—The Cancer Genome Atlas—which stands at the forefront in integrating data science and molecular biology. The result will be that biologists have to deal with the tradeoff between explaining and predicting that we have identified, and hence the explanatory force of the ‘new’ biology is substantially diminished if compared to the ‘old’ biology. However, this aspect also emphasizes the existence of other research goals which make predictive force independent from explanation. (shrink)

Currently, there is widespread skepticism that higher cognitive processes, given their apparent flexibility and globality, could be carried out by specialized computational devices, or modules. This skepticism is largely due to Fodor’s influential definition of modularity. From the rather flexible catalogue of possible modular features that Fodor originally proposed has emerged a widely held notion of modules as rigid, informationally encapsulated devices that accept highly local inputs and whose opera- tions are insensitive to context. It is a mistake, however, to (...) equate such features with computational devices in general and therefore to assume, as Fodor does, that higher cognitive processes must be non-computational. Of the many possible non-Fodorean architectures, one is explored here that offers possible solutions to computational problems faced by conventional modular systems: an ‘enzymatic’ architecture. Enzymes are computational devices that use lock-and-key template matching to iden- tify relevant information (substrates), which is then operated upon and returned to a common pool for possible processing by other devices. Highly specialized enzymes can operate together in a common pool of information that is not pre-sorted by information type. Moreover, enzymes can use molecular ‘tags’ to regulate the operations of other devices and to change how particular substrates are construed and operated upon, allowing for highly interactive, context-specific processing. This model shows how specialized, modular processing can occur in an open system, and suggests that skepti- cism about modularity may largely be due to failure to consider alternatives to the standard model. (shrink)

How to interpret the “molecular gene” concept is discussed in this paper. I argue that the architecture of biological systems is hierarchical and multi-layered, exhibiting striking similarities to that of modern computers. Multiple layers exist between the genotype and system level property, the phenotype. This architectural complexity gives rise to the intrinsic complexity of the genotype-phenotype relationships. The notion of a gene being for a phenotypic trait or traits lacks adequate consideration of this complexity and has limitations in explaining (...) the genotype-phenotype relationships. I explore ways toward an integrative interpretation of the gene in the context of multi-layered biological systems. A gene, I argue, should be interpreted as a functional unit that is responsible for the trans-generation passage of the capacity to dynamically produce a biochemical activity or biochemical activities. At the molecular level, a gene is a genetic unit, a stretch of DNA sequence, which dictates the behavior and the dynamic production of the encoded cellular component(s). Embedded in a gene’s quadruple DNA code are the regulatory signals, such as those for RNA splicing and/or editing, as well as for transcription factor binding. A regulatory signal can be recognized by the gene expression machinery in one state, but not in another. The confusion caused by RNA splicing, editing, and a gene’s selective tissue distribution pattern is addressed. Instead of a context-dependent definition of the gene, I argue for the view that it is the same gene displaying multiple meanings, subject to differential interpretation by the cellular machinery in different states. In other words, the same gene gives rise to different products and expression levels under different conditions. (shrink)

Neurophysiological research suggests our mental life is related to the cellular processes of particular nerves. In the spirit of Occam’s razor, some authors take these connections as reductions of psychological terms and kinds to molecular- biological mechanisms and patterns. Bickle’s ‘intervene cellularly/molecularly and track behaviourally’ reduction is one example of this. Here the mental is being reduced to the physical in two steps. The first is, through genetically altered mammals, to causally alter activity of particular nerve cells, i.e. neurons, (...) at the molecular level and then, under controlled experimental conditions, to use generally-accepted rules of behaviour within psychology to monitor the results of these manipulations. In this article, we argue that Bickle’s case example for molecular reduction, i.e. the reduction of long-term memory to its cellular-molecular mechanisms, cannot support his claims, because it turns out that his chosen molecular pathway is neither a sufficient nor a necessary condition for the memory consolidation switch, and thus, instead of rejecting the multiple realization argument, Bickle’s argument actually speaks in favour of it. Therefore the idea of reductive connections between our mental life and the activity of particular nerves is, at present, still more fiction than reality. (shrink)

The view is presented that extracellular architecture in plant cell walls results from an interplay between molecular self‐assembly and mechanical reorientation due to growth forces. A key initial self‐assembly step may involve hemicelluloses. It is suggested that hemicelluloses may self‐assemble into a helicoid via a cholesteric liquid crystalline phase; the detailed molecular structure of hemicelluloses (stiff backbone, bulky side chains, and the presence of asymmetric carbon atoms) is shown to be consistent with cholesteric requirements for such self‐assembly. Since (...) hemicelluloses are hydrogen‐bonded to the periphery of cellulose microfibrils, the cellulose could then itself become helicoidally arranged. Such ‘universal plywood’ structure is found in the walls of a wide variety of plants, and in several types of cell (including wood). The permanent effects of growth stresses on patterns seen in sections of helicoids are displayed by computer graphics plots, and the expected changes in stiffness are calculated. (shrink)

All epistemic agents physically consist of parts that must somehow comprise an integrated cognitive self. Biological individuals consist of subunits (organs, cells, molecular networks) that are themselves complex and competent in their own context. How do coherent biological Individuals result from the activity of smaller sub-agents? To understand the evolution and function of metazoan bodies and minds, it is essential to conceptually explore the origin of multicellularity and the scaling of the basal cognition of individual cells into a coherent (...) larger organism. In this paper I synthesize ideas in cognitive science, evolutionary biology, and developmental physiology toward a hypothesis about the origin of Individuality: “Scale-Free Cognition”. I propose a fundamental definition of an Individual based on the ability to pursue goals at an appropriate level of scale and organization, and suggest a formalism for defining and comparing the cognitive capacities of highly diverse types of agents. Any Self is demarcated by a computational surface – the spatio-temporal boundary of events that it can measure, model, and try to affect. This surface sets a functional boundary - a cognitive “light cone” which defines the scale and limits of its cognition. I hypothesize that higher-level goal-directed activity and agency, resulting in larger cognitive boundaries, evolve from the primal homeostatic drive of living things to reduce stress – the difference between current conditions and life-optimal conditions. The mechanisms of developmental bioelectricity - the ability of all cells to form electrical networks that process information - suggests a plausible set of gradual evolutionary steps that naturally lead from physiological homeostasis in single cells to memory, prediction, and ultimately complex cognitive agents, via scale-up of the drive of infotaxis. Recent data on the molecular mechanisms of pre-neural bioelectricity suggest a model of how increasingly sophisticated cognitive functions emerge smoothly from cell-cell communication used to guide embryogenesis and regeneration. This set of hypotheses provides a novel perspective on numerous phenomena, such as cancer, and makes several unique, testable predictions for interdisciplinary research that have implications not only for evolutionary developmental biology but also for biomedicine and perhaps artificial intelligence and exobiology. (shrink)

Computational reproducibility possesses its own dynamics and narratives of crisis. Alongside the difficulties of computing as an ubiquitous yet complex scientific activity, computational reproducibility suffers from a naive expectancy of total reproducibility and a moral imperative to embrace the principles of free software as a non-negotiable epistemic virtue. We argue that the epistemic issues at stake in actual practices of computational reproducibility are best unveiled by focusing on software as a pivotal concept, one that is surprisingly often overlooked in accounts (...) of reproducibility issues. Software is not only about designing and coding but also about maintaining, supporting, distributing, licensing, and governance; it is not only about developers but also about users. We focus on openness debates among computational chemists involved in molecular modeling software packages as empirical grounding for our argument. We then identify and analyse four epistemic characteristics as key to the role of software in computational reproducibility. (shrink)

Currently, there is widespread skepticism that higher cognitive processes, given their apparent flexibility and globality, could be carried out by specialized computational devices, or modules. This skepticism is largely due to Fodor's influential definition of modularity. From the rather flexible catalogue of possible modular features that Fodor originally proposed has emerged a widely held notion of modules as rigid, informationally encapsulated devices that accept highly local inputs and whose operations are insensitive to context. It is a mistake, however, to equate (...) such features with computational devices in general and therefore to assume, as Fodor does, that higher cognitive processes must be non‐computational. Of the many possible non‐Fodorean architectures, one is explored here that offers possible solutions to computational problems faced by conventional modular systems: an ‘enzymatic’ architecture. Enzymes are computational devices that use lock‐and‐key template matching to identify relevant information (substrates), which is then operated upon and returned to a common pool for possible processing by other devices. Highly specialized enzymes can operate together in a common pool of information that is not pre‐sorted by information type. Moreover, enzymes can use molecular ‘tags’ to regulate the operations of other devices and to change how particular substrates are construed and operated upon, allowing for highly interactive, context‐specific processing. This model shows how specialized, modular processing can occur in an open system, and suggests that skepticism about modularity may largely be due to failure to consider alternatives to the standard model. (shrink)

Molecular models are typical topics of chemical research depending on the technical standards of observation, computation, and representation. Mathematically, molecular structures have been represented by means of graph theory, topology, differential equations, and numerical procedures. With the increasing capabilities of computer networks, computational models and computer-assisted visualization become an essential part of chemical research. Object-oriented programming languages create a virtual reality of chemical structures opening new avenues of exploration and collaboration in chemistry. From an epistemic point (...) of view, virtual reality is a new computer-assisted tool of human imagination and recognition. (shrink)

Philosophical discussions of systems biology have enriched the notion of mechanistic explanation by pointing to the role of mathematical modeling. However, such accounts still focus on explanation in terms of tracking a mechanism's operation across time (by means of mental or computational simulation). My contention is that there are explanations of molecular systems where the explanatory understanding does not consist in tracking a mechanism's operation and productive continuity. I make this case by a discussion of bifurcation analysis in dynamical (...) systems, articulating the distinctive way in which explanatory understanding is provided, especially about the reversibility or irreversibility of molecular processes. (shrink)

Biology arises from the crowded molecular environment of the cell, rendering it a challenge to understand biological pathways based on the reductionist, low‐concentration in vitro conditions generally employed for mechanistic studies. Recent evidence suggests that low‐affinity interactions between cellular biopolymers abound, with still poorly defined effects on the complex interaction networks that lead to the emergent properties and plasticity of life. Mass‐action considerations are used here to underscore that the sheer number of weak interactions expected from the complex mixture (...) of cellular components significantly shapes biological pathway specificity. In particular, on‐pathway—i.e., “functional”—become those interactions thermodynamically and kinetically stable enough to survive the incessant onslaught of the many off‐pathway (“nonfunctional”) interactions. Consequently, to better understand the molecular biology of the cell a further paradigm shift is needed toward mechanistic experimental and computational approaches that probe intracellular diversity and complexity more directly. Also see the video abstract here https://youtu.be/T19X_zYaBzg. (shrink)

The Medical Research Council Laboratory of Molecular Biology (formerly the Medical Research Council Unit for the Study of Molecular Structure of Biological Systems) in Cambridge (England) played a key role in the postwar history of molecular biology. The paper, focussing on the early history of the institution, aims to show that the creation of the laboratory and the making of molecular biology were part of a new scientific culture set in place after World War II. In (...) five interlinked parts it deals with the institutional creation of the MRC unit dedicated to the crystallographic analysis of biological molecules; the attraction of postwar biophysics, the heading under which the work of the unit initially fell; the people who joined the laboratory and their appropriation of new technologies, in particular the electronic computer for protein crystal structure determination; the cultural appeal of postwar crystallography, as exemplified in the use of crystal structure diagrams for a wide series of consumer goods at the Festival of Britain in 1951 and the display of molecular models at the Brussels World's Fair in 1958, a key site for the presentation of science and its role in the postwar world. (shrink)

The Medical Research Council Laboratory of Molecular Biology in Cambridge played a key role in the postwar history of molecular biology. The paper, focussing on the early history of the institution, aims to show that the creation of the laboratory and the making of molecular biology were part of a new scientific culture set in place after World War II. In five interlinked parts it deals with the institutional creation of the MRC unit dedicated to the crystallographic (...) analysis of biological molecules; the attraction of postwar biophysics, the heading under which the work of the unit initially fell; the people who joined the laboratory and their appropriation of new technologies, in particular the electronic computer for protein crystal structure determination; the cultural appeal of postwar crystallography, as exemplified in the use of crystal structure diagrams for a wide series of consumer goods at the Festival of Britain in 1951 and the display of molecular models at the Brussels World’s Fair in 1958, a key site for the presentation of science and its role in the postwar world. (shrink)

Information is a basic structure of the world, while computation is a process of the dynamic change of information. This book provides a cutting-edge view of world's leading authorities in fields where information and computation play a central role. It sketches the contours of the future landscape for the development of our understanding of information and computation, their mutual relationship and the role in cognition, informatics, biology, artificial intelligence, and information technology. -/- This book is an utterly enjoyable and engaging (...) read which gives readers an opportunity to understand and relate phenomena seemingly unrelated in a completely new light — especially the connections between information, computation, cognition and life. -/- Contents: Cybersemiotics and the Question of Knowledge (Søren Brier) Information Dynamics in a Categorical Setting (Mark Burgin) Mathematics as a Biological Process (G J Chaitin) Information, Causation and Computation (John Collier) From Descartes to Turing: The Computational Content of Supervenience (S Barry Cooper) A Dialogue Concerning Two World Systems: Info-Computational vs Mechanistic (Gordana Dodig-Crnkovic & Vincent C Müller) Does Computing Embrace Self-Organization? (Wolfgang Hofkirchner) Analysis of Information and Computation in Physics Explains Cognitive Paradigms: From Full Cognition to Laplace Determinism to Statistical Determinism to Modern Approach (Vladik Kreinovich, Roberto Araiza & Juan Ferret) Bodies — Both Informed and Transformed Embodied Computation and Information Processing (Bruce J MacLennan) Computation on Information, Meaning and Representations: An Evolutionary Approach (Christophe Menant) Interior Grounding, Reflection, and Self-Consciousness (Marvin Minsky) A Molecular Dynamic Network: Minimal Properties and Evolutionary Implications (Walter Riofrio) Super-recursive Features of Evolutionary Processes and the Models for Computational Evolution (Darko Roglic) Towards a Modeling View of Computing (Oron Shagrir) What's Information, for an Organism or Intelligent Machine? How can a Machine or Organism Mean? (Aaron Sloman) Inconsistent Knowledge as a Natural Phenomenon: The Ranking of Reasonable Inferences as a Computational Approach to Naturally Inconsistent (Legal) Theories (Kees (CNJ) de Vey Mestdagh & Jaap Henk (JH) Hoepman) On the Algorithmic Nature of the World (Hector Zenil & Jean-Paul Delahaye) . (shrink)

In the 1960s molecular population geneticists used Monte Carlo experiments to evaluate particular diffusion equation models. In this paper I examine the nature of this comparative evaluation and argue for three claims: first, Monte Carlo experiments are genuine experiments: second, Monte Carlo experiments can provide an important meansfor evaluating the adequacy of highly idealized theoretical models; and, third, the evaluation of the computational adequacy of a diffusion model with Monte Carlo experiments is significantlydifferent from the evaluation of the emperical (...) adequacy of the same diffusion model. (shrink)

Despite the promises made by molecular evolutionists since the early 1960s that phylogenies would be readily reconstructed using molecular data, the construction of molecular phylogenies has both retained many methodological problems of the past and brought up new ones of considerable epistemic relevance. The field is driven not only by changes in knowledge about the processes of molecular evolution, but also by an ever-present methodological anxiety manifested in the constant search for an increased objectivity—or in its (...) converse, the avoidance of subjectivity.This paper offers an exhaustive account of the methodological and conceptual difficulties embedded in each of the steps required to elaborate molecular phytogenies. The authors adopt a historical perspective on the field in order to follow the development of practices that seek to increase the objectivity of their methods and representations. These include the adoption and development of explicit criteria for evaluation of evidence, and of procedures associated with methods of statistical inference, quantification and automation. All these are linked to an increasing use of computers in research since the mid 1960s. We will show that the practices of objectivity described are highly dependent on the problems and tools of molecular phylogenetics. (shrink)

Collecting, comparing, and computing molecular sequences are among the most prevalent practices in contemporary biological research. They represent a specific way of producing knowledge. This paper explores the historical development of these practices, focusing on the work of Margaret O. Dayhoff, Richard V. Eck, and Robert S. Ledley, who produced the first computer-based collection of protein sequences, published in book format in 1965 as the Atlas of Protein Sequence and Structure. While these practices are generally associated with the (...) rise of molecular evolution in the 1960s, this paper shows that they grew out of research agendas from the previous decade, including the biochemical investigation of the relations between the structures and function of proteins and the theoretical attempt to decipher the genetic code. It also shows how computers became essential for the handling and analysis of sequence data. Finally, this paper reflects on the relationships between experimenting and collecting as two distinct “ways of knowing” that were essential for the transformation of the life sciences in the twentieth century. (shrink)

Collecting, comparing, and computing molecular sequences are among the most prevalent practices in contemporary biological research. They represent a specific way of producing knowledge. This paper explores the historical development of these practices, focusing on the work of Margaret O. Dayhoff, Richard V. Eck, and Robert S. Ledley, who produced the first computer-based collection of protein sequences, published in book format in 1965 as the Atlas of Protein Sequence and Structure. While these practices are generally associated with the (...) rise of molecular evolution in the 1960s, this paper shows that they grew out of research agendas from the previous decade, including the biochemical investigation of the relations between the structures and function of proteins and the theoretical attempt to decipher the genetic code. It also shows how computers became essential for the handling and analysis of sequence data. Finally, this paper reflects on the relationships between experimenting and collecting as two distinct "ways of knowing" that were essential for the transformation of the life sciences in the twentieth century. (shrink)

The concept of molecular structure is fundamental to the practice and understanding of chemistry, but the meaning of this term has evolved and is still evolving. The Born–Oppenheimer separation of electronic and nuclear motions lies at the heart of most modern quantum chemical models of molecular structure. While this separation introduces a great computational and practical simplification, it is neither essential to the conceptual formulation of molecular structure nor universally valid. Going beyond the Born–Oppenheimer approximation introduces new (...) paradigms, bringing fresh insight into the chemistry of fluxional molecules, proteins, superconductors and macroscopic dielectrics, thus opening up new avenues for exploration. But it requires that our ideas of molecular structure need to evolve beyond simple ball-and-stick-type models. (shrink)

Theory of networks serves as a mathematical foundation for the construction and modeling of chemical structures and complicated networks. In particular, chemical networking theory has a wide range of utilizations in the study of chemical structures, where examination and manipulation of chemical structural information are made feasible by utilizing the numerical graph invariants. A network invariant or a topological index is a numerical measure of a chemical compound which is capable to describe the chemical structural properties such as melting point, (...) freezing point, density, pressure, tension, and temperature of chemical compounds. Wiener initiated the first distance-based TI which is considered to be the most important TI to preserve the chemical and physical properties of chemical structures. Later on, degree-based TI was introduced to find the π -electron energy of molecules. Recently, connection number-based TIs are studied which are more efficient than degree and distance-based TIs. In this paper, we compute the connection number-based TIs of the structure of crystal cubic carbons which are one of the most significant and interesting composites in modern resources of science due to the involvement of carbon atoms. (shrink)

A new theoretical model of oncogenesis that incorporates a systemic view of biodynamics was developed and analyzed. According to our model, the emergent behavior at the cell population level is the result of nonlinear interactions between the neoplastic and immune subsystems. Our approach allows subsequent extensions of the model to span multiple levels of biological organization. The model opens the possibility of a flexible connection between the molecular and tissue level descriptions of oncogenesis.

Jablonka & Lamb (J&L) refer only implicitly to aspects of cognitive competence that preceded both evolution of human language and language learning in children. These aspects are important for evolution and development but need to be understood using the design-stance, which the book adopts only for molecular and genetic processes, not for behavioural and symbolic processes. Design-based analyses reveal more routes from genome to behaviour than J&L seem to have considered. This both points to gaps in our understanding of (...) evolution and epigenetic processes and may lead to possible ways of filling the gaps. (shrink)

After observing that the truth conditions of connectives of non–classical logics are generally defined in terms of formulas of first–order logic, we introduce ‘protologics’, a class of logics whose connectives are defined by arbitrary first–order formulas. Then, we introduce atomic and molecular logics, which are two subclasses of protologics that generalize our gaggle logics and which behave particularly well from a theoretical point of view. We also study and introduce a notion of equi-expressivity between two logics based on different (...) classes of models. We prove that, according to that notion, every pure predicate logic with \ variables and constants is as expressive as a predicate atomic logic, some sort of atomic logic. Then, we prove that the class of protologics is equally expressive as the class of molecular logics. That formally supports our claim that atomic and molecular logics are somehow ‘universal’. Finally, we identify a subclass of molecular logics that we call predicate molecular logics and which constitutes its representative core: every molecular logic is as expressive as a predicate molecular logic. (shrink)

This paper argues that the consensus physicalist antireductionism in the philosophy of biology cannot accommodate the research strategy or indeed the recent findings of molecular developmental biology. After describing Wolperts programmatic claims on its behalf, and recent work by Gehring and others to identify the molecular determinants of development, the paper attempts to identify the relationship between evolutionary and developmental biology by reconciling two apparently conflicting accounts of bio-function – Wrights and Nagels (as elaborated by Cummins). Finally, the (...) paper seeks a way of defending the two central theses of physicalist antireductionism in the light of the research program of molecular developmental biology, by sharply reducing their metaphysical force. (shrink)

I propose that a sociological and historical examination of nanotechnologists can contribute more to an understanding of nanotechnology than an ontological definition. Nanotechnology emerged from the convergent evolution of numerous "technical knowledge communities"-networks of tightly-interconnected people who operate between disciplines and individual research groups. I demonstrate this proposition by sketching the co-evolution of computational chemistry and computational nanotechnology. Computational chemistry arose in the 1950s but eventually segregated into an ab initio, basic research, physics-oriented flavor and an industry-oriented, molecular modeling (...) and visualization, biochemical flavor. Computational nanotechnology arose in the 1990s as a synthesis of these two subgroups, infused by people and practices from computational materials science, engineering, computer science, and elsewhere. I show that to understand the aims and outcomes of computational nanotechnology-and nanotechnology more generally-we need to understand relationships between different, but related, nano knowledge communities and their dependence on particular practices, artifacts, and theories. (shrink)

In this paper we will examine some ethical aspects of the role that computers and computing increasingly play in new genetics. Our claim is that there is no new genetics without computer science. Computer science is important for the new genetics on two levels: from a theoretical perspective, and from the point of view of geneticists practice. With respect to , the new genetics is fully impregnate with concepts that are basic for computer science. Regarding , recent (...) developments in the Human Genome Project have shown that computers shape the practices of molecular genetics; an important example is the Shotgun Method's contribution to accelerating the mapping of the human genome. A new challenge to the HGP is provided by the Open Source Philosophy , which is another way computer technologies now influence the shaping of public policy debates involving genomics. (shrink)

The ArgumentThis paper focuses on the opening of a discursive space: the emergence of informational and scriptural representations of life and their self-negating consequences for the construction of biological meaning. It probes the notion of writing and the book of life and shows how molecular biology's claims to a status of language and texuality undermines its own objective of control. These textual significations were historically contingent. The informational representations of heredity and life were not an outcome of the internal (...) cognitive momentum of molecular biology; they were not a logical necessity of the unravelling of the base-pairing of the DNA double-helix. They were transported into molecular biology still within the protein paradigm of the gene in the 1940s and permeated nearly every discipline in the life and social sciences. These information-based models, metaphors, linguistic, and semiotic tools which were central to the formulation of the genetic code were transported into molecular biology from cybernetics, information theory, electronic computing, and control and communication systems — technosciences that were deeply embedded with the military experiences of world war II and the Cold War. The information discourse thus became fixed in molecular biology not because it worked in the narrow epistemic sense (it did not), but because it positioned molecular biology within postwar discourse and culture, perhaps within the transition to a post-modern information-based society. (shrink)

The “DNA is a program” metaphor is still widely used in Molecular Biology and its popularization. There are good historical reasons for the use of such a metaphor or theoretical model. Yet we argue that both the metaphor and the model are essentially inadequate also from the point of view of Physics and Computer Science. Relevant work has already been done, in Biology, criticizing the programming paradigm. We will refer to empirical evidence and theoretical writings in Biology, although (...) our arguments will be mostly based on a comparison with the use of differential methods (in Molecular Biology: a mutation or alike is observed or induced and its phenotypic consequences are observed) as applied in Computer Science and in Physics, where this fundamental tool for empirical investigation originated and acquired a well-justified status. In particular, as we will argue, the programming paradigm is not theoretically sound as a causal(as in Physics) or deductive(as in Programming) framework for relating the genome to the phenotype, in contrast to the physicalist and computational grounds that this paradigm claims to propose. (shrink)

In this paper I aim to defend a twofold thesis. On one hand, I will sup-port, against Perini [7], the indispensability of diagrams when structurally complex biomolecules are concerned, since it is not possible to satisfactorily use linguistic-sentential representations at that domain. On the other hand, even when diagrams are dispensable I will defend than they will generally be more effective than other representations in encoding biomolecular knowledge, relying on Kulvicki-Shimojima’s diagrammatic effectiveness thesis. Finally, I will ground many epistemic virtues (...) of biomolecular diagrams (understandability, explanatory power, prediction and hypothesis evaluation) on their cognitive-computational indispensability and their semantic-epistemic effectiveness. (shrink)