Conditions for a theoretical biology: is biology truly an autonomous science?

In a line of a previous paper, the conditions for a theoretical biology were discussed and it was pointed out that the primary condition is that biology is an autonomous science. This statement is connected to the problem of reductionism. A discussion of the autonomy of biology shows that reductionism cannot be maintained, although particularly in physiology often physics and mathematics are used. Development, organization and evolution of biological systems are typical areas of autonomous biological researches and of autonomous theoretical developments. A sort of reduction to history seems today a nonsensical attempt to reduce the area of free theoretical biological activity.     

Ins and Outs of Systems Biology vis-à-vis Molecular Biology: Continuation or Clear Cut?

The comprehension of living organisms in all their complexity poses a major challenge to the biological sciences. Recently, systems biology has been proposed as a new candidate in the development of such a comprehension. The main objective of this paper is to address what systems biology is and how it is practised. To this end, the basic tools of a systems biological approach are explored and illustrated. In addition, it is questioned whether systems biology ‘revolutionizes’ molecular biology and ‘transcends’ its assumed reductionism. The strength of this claim appears to depend on how molecular and systems biology are characterised and on how reductionism is interpreted. Doing credit to molecular biology and to methodological reductionism, it is argued that the distinction between molecular and systems biology is gradual rather than sharp. As such, the classical challenge in biology to manage, interpret and integrate biological data into functional wholes is further intensified by systems biology’s use of modelling and bioinformatics, and by its scale enlargement.     

How to be an anti-reductionist about developmental biology: Response to Laubichler and Wagner

Alexander Rosenberg recently claimed (1997) that developmental biology is currently being reduced to molecular biology. cite several concrete biological examples that are intended to impugn Rosenberg's claim. I first argue that although Laubichler and Wagner's examples would refute a very strong reductionism, a more moderate reductionism would escape their attacks. Next, taking my cue from the antireductionist's perennial stress on the importance of spatial organization, I describe one form an empirical finding that refutes this moderate reductionism would take. Finally, I point out an actual example, anterior-posterior axis determination in the chick, that challenges the reductionist's belief that all developmental regularities can be explained by molecular biology. In short, I argue that Rosenberg's position can be saved from Laubichler and Wagner's criticisms and putative counter-examples, but it would not survive a different kind of counter-example.     

Darwin to DNA, molecules to morphology: the end of classical population genetics and the road ahead.

Molecular reductionism has permeated all of biology and because of successive new technical breakthroughs it has succeeded in unraveling the structural details of genes and genomes. The molecular revolution has reached its reductionist limit, i.e., the study of component parts in isolation, and is ready to come full circle through genomics, proteomics, and gene expression studies back to the phenotype and bring evolutionary biology to confront the Darwinian paradigm, the relationship between gene, organism, and environment. Classical experimental population genetics, dealing with genetic polymorphism and estimation of selection coefficients on a gene-by-gene basis, is coming to an end and a new era of interdisciplinary and interactive biology focusing on dynamic relationships among gene, organism, and environment has begun. In the new population genetics, there will be a shift in focus from single genes to gene networks, from gene-structure to gene-regulation, from additivity to epistasis, and from simple phenotypes to gene-interaction networks and the evolution of complex and modular systems.     

Miniaturized analytical assays in biotechnology

Biotechnology today is a well-established paradigm in many areas of human endeavor, such as the pharmaceutical industry, agriculture, management of the environment and many others. Meanwhile, biology is undergoing a spectacular transition: whereas systematic biology was replaced gradually by molecular biology, the latter is rapidly being transformed into a new systematic era in which entire genomes are being charted by ever more sophisticated analytical techniques.In the wake of this onslaught of data, new fields are germinating, such as bioinformatics in an attempt to find answers to fundamental questions, answers that may be hidden in the massive amounts of data already available today.     

Modularity: a new perspective in biology

Several decades of research in biochemistry and molecular biology have been devoted for studies on isolated enzymes and proteins. Recent high throughput technologies in genomics and proteomics have resulted in avalanche of information about several genes, proteins and enzymes in variety of living systems. Though these efforts have greatly contributed to the detailed understanding of a large number of individual genes and proteins, this explosion of information has simultaneously brought out the limitations of reductionism in understanding complex biological processes. The genes or gene products do not function in isolation in vivo. A delicate and dynamic molecular architecture is required for precision of the chemical reactions associated with "life". In future, a paradigm shift is, therefore, envisaged, in biology leading to exploration of molecular organizations in physical and genomic context, a subtle transition from conventional molecular biology to modular biology. A module can be defined as an organization of macromolecules performing a synchronous function in a given metabolic pathway. In modular biology, the biological processes of interest are explored as complex systems of functionally interacting macromolecules. The present article describes the perceptions of the concept of modularity, in terms of associations among genes and proteins, presenting a link between reductionist approach and system biology.     

Systems biology in animal sciences

Systems biology is a rapidly expanding field of research and is applied in a number of biological disciplines. In animal sciences, omics approaches are increasingly used, yielding vast amounts of data, but systems biology approaches to extract understanding from these data of biological processes and animal traits are not yet frequently used. This paper aims to explain what systems biology is and which areas of animal sciences could benefit from systems biology approaches. Systems biology aims to understand whole biological systems working as a unit, rather than investigating their individual components. Therefore, systems biology can be considered a holistic approach, as opposed to reductionism. The recently developed 'omics' technologies enable biological sciences to characterize the molecular components of life with ever increasing speed, yielding vast amounts of data. However, biological functions do not follow from the simple addition of the properties of system components, but rather arise from the dynamic interactions of these components. Systems biology combines statistics, bioinformatics and mathematical modeling to integrate and analyze large amounts of data in order to extract a better understanding of the biology from these huge data sets and to predict the behavior of biological systems. A 'system' approach and mathematical modeling in biological sciences are not new in itself, as they were used in biochemistry, physiology and genetics long before the name systems biology was coined. However, the present combination of mass biological data and of computational and modeling tools is unprecedented and truly represents a major paradigm shift in biology. Significant advances have been made using systems biology approaches, especially in the field of bacterial and eukaryotic cells and in human medicine. Similarly, progress is being made with 'system approaches' in animal sciences, providing exciting opportunities to predict and modulate animal traits.     

Giant sucking sound: can physiology fill the intellectual void left by the reductionists?

Molecular reductionism has so far failed to deliver the broad-based therapeutic insights that were initially hoped for. This form of reductionism is now being replaced by so-called "systems biology." This is a nebulously defined approach and/or discipline, with some versions of it relying excessively on hypothesis-neutral approaches and only minimally informed by key physiological concepts such as homeostasis and regulation. In this context, physiology is uniquely positioned to continue to provide impressive levels of both biological and therapeutic insight by using hypothesis-driven "classical" approaches and concepts to help frame what might be described as the "pieces of the puzzle" that emerge from molecular reductionism. The strength of physiology as a "bridge" between reductionism and epidemiology, along with its unparalleled ability to generate therapeutic insights and opportunities justifies increased attention and emphasis on our discipline into the future. Arguments relevant to this set of assertions are advanced and this paper, which was based on the 2011 Adolph Lecture, represents an effort to fill the intellectual void left by reductionism and improve scientific progress.     

Systems biology,emergence and antireductionism

This study explores the conceptual history of systems biology and its impact on philosophical and scientific conceptions of reductionism, antireductionism and emergence. Development of systems biology at the beginning of 21st century transformed biological science. Systems biology is a new holistic approach or strategy how to research biological organisms, developed through three phases. The first phase was completed when molecular biology transformed into systems molecular biology. Prior to the second phase, convergence between applied general systems theory and nonlinear dynamics took place, hence allowing the formation of systems mathematical biology. The second phase happened when systems molecular biology and systems mathematical biology, together, were applied for analysis of biological data. Finally, after successful application in science, medicine and biotechnology, the process of the formation of modern systems biology was completed.Systems and molecular reductionist views on organisms were completely opposed to each other. Implications of systems and molecular biology on reductionist–antireductionist debate were quite different. The analysis of reductionism, antireductionism and emergence issues, in the era of systems biology, revealed the hierarchy between methodological, epistemological and ontological antireductionism. Primarily, methodological antireductionism followed from the systems biology. Only after, epistemological and ontological antireductionism could be supported.     

Emergentism as a default: Cancer as a problem of tissue organization

During the last fifty years the dominant stance in experimental biology has been reductionism. For the most part, research programs were based on the notion that genes were in ’the driver’s seat’ controlling the developmental program and determining normalcy and disease (genetic reductionism and genetic determinism). Philosophers were the first to realize that the belief that the Mendelian genes were reduced to DNA molecules was questionable. Soon after these pronouncements, experimental data confirmed their misgivings. The optimism of molecular biologists, fueled by early success in tackling relatively simple problems, has now been tempered by the difficulties found when attempting to understand complex biological problems. Here, we analyse experimental data that illustrate the shortcomings of this sort of reductionism. We also examine the prevailing paradigm in cancer research, the somatic mutation theory (SMT), the premises of which are: (i) cancer is derived from a single somatic cell that has accumulated multiple DNA mutations; (ii) the default state of cell proliferation in metazoa is quiescence; and (iii) cancer is a disease of cell proliferation caused by mutations in genes that control proliferation and the cell cycle. We challenge the notion that cancer is a cellular problem caused by mutated genes by assessing data gathered both from within the reductionist paradigm and from an alternative view that regards carcinogenesis as a developmental process gone awry. This alternative view, explored under the name of the tissue organization field theory (TOFT), is based on premises that place cancer in a different hierarchical level of complexity from that proposed by the SMT, namely: (i) carcinogenesis represents a problem of tissue organization comparable to organogenesis, and (ii) proliferation is the default state of all cells. We propose that the organicist view, in which the TOFT is based, is a good starting point from which to explore emergent phenomena. However, new theoretical concepts are needed in order to grapple with the apparent circular causality of complex biological phenomena in development and carcinogenesis.     

DNA Codes and Information: Formal Structures and Relational Causes

Recently the terms "codes" and "information" as used in the context of molecular biology have been the subject of much discussion. Here I propose that a variety of structural realism can assist us in rethinking the concepts of DNA codes and information apart from semantic criteria. Using the genetic code as a theoretical backdrop, a necessary distinction is made between codes qua symbolic representations and information qua structure that accords with data. Structural attractors are also shown to be entailed by the mapping relation that any DNA code is a part of (as the domain). In this framework, these attractors are higher-order informational structures that obviate any "DNA-centric" reductionism. In addition to the implications that are discussed, this approach validates the array of coding systems now recognized in molecular biology.     

Studying populations without molecular biology: Aster Models and a new argument against reductionism

During the past few decades, philosophers of biology have debated the issue of reductionism versus anti-reductionism, with both sides often claiming a 'pluralist' position. However, both sides also tend to focus on a single research paradigm, which analyzes living things in terms of certain macromolecular components. I offer a case study where biologists pursue other analytic pathways, in a tradition of quantitative genetics that originates with the initially purely mathematical theories of R. A. Fisher, J. B. S. Haldane, and Sewall Wright in the 1930s. Aster Models (developed by Ruth Shaw and Charles Geyer) offers a class of statistical models designed for studying the fitness of plant and animal populations, by integrating the measurements of separate, sequential, non-normally distributed fitness components in novel ways. Their work generates important theoretical and practical results that do not require elaboration by molecular biology, and thus serves as a counterexample to the claims of philosophers whose 'pluralism' still harbors reductionist assumptions.     

Foundations of the new phylogenetics

Evolutionary idea is the core of the modern biology. Due to this, phylogenetics dealing with historical reconstructions in biology takes a priority position among biological disciplines. The second half of the 20th century witnessed growth of a great interest to phylogenetic reconstructions at macrotaxonomic level which replaced microevolutionary studies dominating during the 30s-60s. This meant shift from population thinking to phylogenetic one but it was not revival of the classical phylogenetics; rather, a new approach emerged that was baptized The New Phylogenetics. It arose as a result of merging of three disciplines which were developing independently during 60s-70s, namely cladistics, numerical phyletics, and molecular phylogenetics (now basically genophyletics). Thus, the new phylogenetics could be defined as a branch of evolutionary biology aimed at elaboration of "parsimonious" cladistic hypotheses by means of numerical methods on the basis of mostly molecular data. Classical phylogenetics, as a historical predecessor of the new one, emerged on the basis of the naturphilosophical worldview which included a superorganismal idea of biota. Accordingly to that view, historical development (the phylogeny) was thought an analogy of individual one (the ontogeny) so its most basical features were progressive parallel developments of "parts" (taxa), supplemented with Darwinian concept of monophyly. Two predominating traditions were diverged within classical phylogenetics according to a particular interpretation of relation between these concepts. One of them (Cope, Severtzow) belittled monophyly and paid most attention to progressive parallel developments of morphological traits. Such an attitude turned this kind of phylogenetics to be rather the semogenetics dealing primarily with evolution of structures and not of taxa. Another tradition (Haeckel) considered both monophyletic and parallel origins of taxa jointly: in the middle of 20th century it was split into phylistics (Rasnitsyn's term; close to Simpsonian evolutionary taxonomy) belonging rather to the classical realm, and Hennigian cladistics that pays attention to origin of monophyletic taxa exclusively. In early of the 20th century, microevolutionary doctrine became predominating in evolutionary studies. Its core is the population thinking accompanied by the phenetic one based on equation of kinship to overall similarity. They were connected to positivist philosophy and hence were characterized by reductionism at both ontological and epistemological levels. It led to fall of classical phylogenetics but created the prerequisites for the new phylogenetics which also appeared to be full of reductionism. The new rise of phylogenetic (rather than tree) thinking during the last third of the 20th century was caused by lost of explanatory power of population one and by development of the new worldview and new epistemological premises. That new worldview is based on the synergetic (Prigoginian) model of development of non-equilibrium systems: evolution of the biota, a part of which is phylogeny, is considered as such a development. At epistemological level, the principal premise appeared to be fall of positivism which was replaced by post-positivism argumentation schemes. Input of cladistics into new phylogenetics is twofold. On the one hand, it reduced phylogeny to cladistic history lacking any adaptivist interpretation and presuming minimal evolution model. From this it followed reduction of kinship relation to sister-group relation lacking any reference to real time scale and to ancestor-descendant relation. On the other hand, cladistics elaborated methodology of phylogenetic reconstructions based on the synapomorphy principle, the outgroup concept became its part. The both inputs served as premises of incorporation of both numerical techniques and molecular data into phylogenetic reconstruction. Numerical phyletics provided the new phylogenetics with easily manipulated algorithms of cladogram construing and thus made phylogenetic reconstructions operational and repetitive. The above phenetic formula "kinship = similarity" appeared to be a keystone for development of the genophyletics. Within numerical phyletics, a lot of computer programs were elaborated which allow to manipulate with evolutionary scenario during phylogenetic reconstructions. They make it possible to reconstruct both clado- and semogeneses based on the same formalized methods. Multiplicity of numerical approaches indicates that, just as in the case of numerical phenetics, choice of adequate method(s) should be based on biologically sound theory. The main input of genophyletics (= molecular phylogenetics) into the new phylogenetics was due to completely new factology which makes it possible to compare directly such far distant taxa as prokaryotes and higher eukaryotes. Genophyletics is based on the theory of neutral evolution borrowed from microevolutionary theory and on the molecular clock hypothesis which is now considered largely inadequate. The future developments of genophyletics will be aimed at clarification of such fundamental (and "classical" by origin) problems as application of character and homology concepts to molecular structures. The new phylogenetics itself is differentiated into several schools caused basically by diversity of various approaches existing within each of its "roots". Cladistics makes new phylogenetics splitted into evolutionary and parsimonious ontological viewpoints. Numerical phyletics divides it into statistical and (again) parsimonious methodologies. Molecular phylogenetics is opposite by its factological basis to morphological one. The new phylogenetics has significance impact onto the "newest" systematics. From one side, it gives ontological status back to macrotaxa they have lost due to "new" systematics based on population thinking. From another side, it rejects some basical principles of classical phylogenetic (originally Linnean) taxonomy such as recognitions of fixed taxonomic ranks designated by respective terms and definition of taxic names not by the diagnostic characters but by reference to the ancestor. The latter makes the PhyloCode overburdened ideologically and the "newest" systematics self-controversial, as concept of ancestor has been acknowledged non-operational from the very beginning of cladistics. Relation between classical and new phylogenetics is twofold. At the one hand, general phylogenetic hypothesis (in its classical sense) can be treated as a combination of cladogenetic and semogenetic reconstructions. Such a consideration is bound to pay close attention to the uncertainty relation principle which, in case of the phylogenetics, means that the general phylogenetic hypothesis cannot be more certain than any of initial cladogenetic or semogenetic hypotheses. From this standpoint, the new phylogenetics makes it possible to reconstruct phylogeny following epistemological principle "from simple to complex". It elaborates a kind of null hypotheses about evolutionary history which are more easy to test as compared to classical hypotheses. Afterward, such hypotheses are possible to be completed toward the classical, more content-wise ones by adding anagenetic information to the cladogenetic one. At another hand, reconstructions elaborated within the new phylogenetics could be considered as specific null hypotheses about both clado- and semogeneses. They are to be tested subsequently by mean of various models, including those borrowed from "classical" morphology. The future development of the new phylogenetics is supposed to be connected with getting out of plethora of reductionism inherited by it from population thinking and specification of object domain of the phylogenetics. As the latter is a part of an evolutionary theory, its future developments will be adjusted with the latter. Lately predominating neodarwinism is now being replaced by the epigenetic evolutionary theory to which phylistics (one of the modern versions of classical phylogenetics) seems to be more correspondent.     

Molecular biology in physiology

The aim of this symposium on molecular biology in physiology was to introduce molecular biology to physiologists who had relatively little exposure to the new developments in this field, so that they can become conversant on this topic and contribute to the advancement of physiology by incorporating molecular biological approaches as a part of their research arsenal. After the discussion of the basic concepts, terminology, and methodology used in molecular biology, it was shown how these basic principles have been applied to the study of the genes encoding two membrane proteins that have important transport functions (band 3 and ATPase). The second half of the symposium consisted of papers on the state-of-the-art developments in the application of molecular biology to the studies of the atrial natriuretic factor and renin genes, adenylate cyclase-coupled adrenergic receptors, acetylcholine receptors and sodium channel, and long-term and short-term memories. The ultimate goal is that these examples will provide an impetus for the opening of new frontiers of research in physiology by taking advantage of the tools developed from recent advances in molecular biology.     

Production of useful secondary metabolites in plants: Functional genomics approaches

The paradigm of biological research has been changed by recent developments in genomics, high-throughput biology, and bioinformatics. Conventional biology often was based on empirical, labor-intensive, and time-consuming methods. In the new paradigm, biological research e is driven by a holistic approach on the basis of rational, automatic, and high-throughput methods. New functional compounds can be discovered by using high-throughput screening systems. Secondary metabolite pathways and the genes involved in those pathways are then determined by studying functional genomics in conjunction with the data-mining tools of bioinformatics. In addition, these advances in metabolic engineering enable researchers to confer new secondary metabolic pathways to crops by transferring three to five, or more, heterologous genes taken from various other species. In the future, engineering for the production of useful compounds will be designed by a set of software tools that allows the user to specify a cell’s genes, proteins, and other molecules, as well as their individual interactions.     

Calculating life? Duelling discourses in interdisciplinary systems biology

A high profile context in which physics and biology meet today is in the new field of systems biology. Systems biology is a fascinating subject for sociological investigation because the demands of interdisciplinary collaboration have brought epistemological issues and debates front and centre in discussions amongst systems biologists in conference settings, in publications, and in laboratory coffee rooms. One could argue that systems biologists are conducting their own philosophy of science. This paper explores the epistemic aspirations of the field by drawing on interviews with scientists working in systems biology, attendance at systems biology conferences and workshops, and visits to systems biology laboratories. It examines the discourses of systems biologists, looking at how they position their work in relation to previous types of biological inquiry, particularly molecular biology. For example, they raise the issue of reductionism to distinguish systems biology from molecular biology. This comparison with molecular biology leads to discussions about the goals and aspirations of systems biology, including epistemic commitments to quantification, rigor and predictability. Some systems biologists aspire to make biology more similar to physics and engineering by making living systems calculable, modelable and ultimately predictable-a research programme that is perhaps taken to its most extreme form in systems biology's sister discipline: synthetic biology. Other systems biologists, however, do not think that the standards of the physical sciences are the standards by which we should measure the achievements of systems biology, and doubt whether such standards will ever be applicable to 'dirty, unruly living systems'. This paper explores these epistemic tensions and reflects on their sociological dimensions and their consequences for future work in the life sciences.     

Interview with Sydney Brenner

The following text is an edited version of a recent interview with Sydney Brenner who has been at the forefront of many developments in molecular biology since the 1950s. It provides a participant’s view on current issues in the history and epistemology of molecular biology. The main issue raised by Brenner regards the relation of molecular biology to the new field of systems biology. Brenner defends the original programme of molecular biology—the molecular explanation of living processes—that in his view has yet to be completed. The programme of systems biology in contrast he views as either trivial or as not achievable since it purports to deal with inverse problems that are impossible to solve in complex living systems. Other issues covered in the conversation concern the impact of the human genome sequencing project, the commercial turn in molecular biology and the contested disciplinary status of the science.     

Exploiting evolutionary relationships for predicting protein structures

In the last few years there have been many developments in computational biology, particularly with regard to novel, imaginative exploitation of genomic data. Disappointingly, there has been a lack of progress in the methodology for prediction of protein structures. In the last several years, however, promising new methods have finally begun to emerge. These methods are increasing the power and scope of the methodology, but, most importantly, they are generating new areas of investigation that we believe will accelerate progress in the field. In this review we describe recent developments and highlight the implications of their success as well as areas where efforts should be focused.