The Basic Ideas of Biology

150 Years of the Mass Action Law

This year we celebrate the 150th anniversary of the law of mass action. This law is often assumed to have been “there” forever, but it has its own history, background, and a definite starting point. The law has had an impact on chemistry, biochemistry, biomathematics, and systems biology that is difficult to overestimate. It is easily recognized that it is the direct basis for computational enzyme kinetics, ecological systems models, and models for the spread of diseases. The article reviews the explicit and implicit role of the law of mass action in systems biology and reveals how the original, more general formulation of the law emerged one hundred years later ab initio as a very general, canonical representation of biological processes.

The biogenic approach to cognition

After half a century of cognitive revolution we remain far from agreement about what cognition is and what cognition does. It was once thought that these questions could wait until the data were in. Today there is a mountain of data, but no way of making sense of it. The time for tackling the fundamental issues has arrived. The biogenic approach to cognition is introduced not as a solution but as a means of approaching the issues. The traditional, and still predominant, methodological stance in cognitive inquiry is what I call the anthropogenic approach: assume human cognition as the paradigm and work ‘down’ to a more general explanatory concept. The biogenic approach, on the other hand, starts with the facts of biology as the basis for theorizing and works ‘up’ to the human case by asking psychological questions as if they were biological questions. Biogenic explanations of cognition are currently clustered around two main frameworks for understanding biology: self-organizing complex systems and autopoiesis. The paper describes the frameworks and infers from them ten empirical principles—the biogenic ‘family traits’—that constitute constraints on biogenic theorizing. Because the anthropogenic approach to cognition is not constrained empirically to the same degree, I argue that the biogenic approach is superior for approaching a general theory of cognition as a natural phenomenon.

Design in The Age of Biology: Shifting From a Mechanical-Object Ethos to an Organic-Systems Ethos

In the early twentieth century, our understanding of physics changed rapidly; now, our understanding of biology is undergoing a similar rapid change.

The lost art of mathematical modelling

We provide a critique of mathematical biology in light of rapid developments in modern machine learning. We argue that out of the three modelling activities – (1) formulating models; (2) analysing models; and (3) fitting or comparing models to data – inherent to mathematical biology, researchers currently focus too much on activity (2) at the cost of (1). This trend, we propose, can be reversed by realising that any given biological phenomenon can be modelled in an infinite number of different ways, through the adoption of a pluralistic approach, where we view a system from multiple, different points of view. We explain this pluralistic approach using fish locomotion as a case study and illustrate some of the pitfalls – universalism, creating models of models, etc. – that hinder mathematical biology. We then ask how we might rediscover a lost art: that of creative mathematical modelling.

How to understand cells, tissues and organisms as agents with agendas | Aeon Essays

Biology’s next great horizon is to understand cells, tissues and organisms as agents with agendas (even if unthinking ones)

b.next: rebuilding biology for engineering

Self-Organization in Biological Systems

The synchronized flashing of fireflies at night. The spiraling patterns of an aggregating slime mold. The anastomosing network of army-ant trails. The coordinated movements of a school of fish. Researchers are finding in such patterns—phenomena that have fascinated naturalists for centuries—a fertile new approach to understanding biological systems: the study of self-organization. This book, a primer on self-organization in biological systems for students and other enthusiasts, introduces readers to the basic concepts and tools for studying self-organization and then examines numerous examples of self-organization in the natural world. Self-organization refers to diverse pattern formation processes in the physical and biological world, from sand grains assembling into rippled dunes to cells combining to create highly structured tissues to individual insects working to create sophisticated societies. What these diverse systems hold in common is the proximate means by which they acquire order and structure. In self-organizing systems, pattern at the global level emerges solely from interactions among lower-level components. Remarkably, even very complex structures result from the iteration of surprisingly simple behaviors performed by individuals relying on only local information. This striking conclusion suggests important lines of inquiry: To what degree is environmental rather than individual complexity responsible for group complexity? To what extent have widely differing organisms adopted similar, convergent strategies of pattern formation? How, specifically, has natural selection determined the rules governing interactions within biological systems? Broad in scope, thorough yet accessible, this book is a self-contained introduction to self-organization and complexity in biology—a field of study at the forefront of life sciences research.

How Life Works: A User’s Guide to the New Biology

“Bold and intriguing.”—Wall Street Journal • “Penetrating. . . . Provocative and profound.”—Publishers Weekly (starred review) • “Offers plenty of food for thought.”—Kirkus Reviews (starred review)  “Ball’s marvelous book is both wide-ranging and deep. . . . I could not put it down.”—Siddhartha Mukherjee, author of The Song of the Cell and the Pulitzer Prize–winning The Emperor of All Maladies A new, cutting-edge vision of biology that revises our understanding of what life itself is, how to enhance it, and what possibilities it offers.   Biology is undergoing a quiet but profound transformation. Several aspects of the standard picture of how life works—the idea of the genome as a blueprint, of genes as instructions for building an organism, of proteins as precisely tailored molecular machines, of cells as entities with fixed identities, and more—have been exposed as incomplete, misleading, or wrong.   In How Life Works, Philip Ball explores the new biology, revealing life to be a far richer, more ingenious affair than we had guessed. Ball explains that there is no unique place to look for an answer to this question: life is a system of many levels—genes, proteins, cells, tissues, and body modules such as the immune system and the nervous system—each with its own rules and principles. How Life Works explains how these levels operate, interface, and work together (most of the time).   With this knowledge come new possibilities. Today we can redesign and reconfigure living systems, tissues, and organisms. We can reprogram cells, for instance, to carry out new tasks and grow into structures not seen in the natural world. As we discover the conditions that dictate the forms into which cells organize themselves, our ability to guide and select the outcomes becomes ever more extraordinary. Some researchers believe that ultimately we will be able to regenerate limbs and organs, and perhaps even create new life forms that evolution has never imagined.   Incorporating the latest research and insights, How Life Works is a sweeping journey into this new frontier of the life sciences, a realm that will reshape our understanding of life as we know it.

The sentient cell: the cellular foundations of consciousness

"All species, extant and extinct, from the simplest unicellular prokaryotes to humans, have an existential consciousness. Without sentience, the first cells that emerged some 4 billion years ago would have been evolutionary dead-ends, unable to survive in the chaotic, dangerous environment in which life first appeared and evolved. In this book, Arthur Reber's theory, the Cellular Basis of Consciousness (CBC), is outlined and distinguished from those models that argue that minds could be instantiated on artificial entities and those that maintain consciousness requires a nervous system. The CBC framework takes a novel approach to classic topics such as the origin-of-life, philosophy of mind, the role of genes, the impact of cognition, and how biological information is processed by all species. It also calls for a rethinking of a variety of issues including the moral implications of the sentient capacities of all species, how welfare concerns need to be expanded beyond where they currently are, and critically, how all life is intertwined in a coordinated cognitive ecology. The Sentient Cell explores this revolutionary model, which updates the standard neo-Darwinian framework within which current approaches operate and examines the underlying biomolecular features that are the likely candidates for the "invention" of consciousness and outline their role in cellular life." --

Are biological systems poised at criticality?

Many of life's most fascinating phenomena emerge from interactions among many elements--many amino acids determine the structure of a single protein, many genes determine the fate of a cell, many neurons are involved in shaping our thoughts and memories. Physicists have long hoped that these collective behaviors could be described using the ideas and methods of statistical mechanics. In the past few years, new, larger scale experiments have made it possible to construct statistical mechanics models of biological systems directly from real data. We review the surprising successes of this "inverse" approach, using examples form families of proteins, networks of neurons, and flocks of birds. Remarkably, in all these cases the models that emerge from the data are poised at a very special point in their parameter space--a critical point. This suggests there may be some deeper theoretical principle behind the behavior of these diverse systems.

Learning Outside the Brain: Integrating Cognitive Science and Systems Biology

Learning is commonplace in organisms such as ourselves and even in organisms as far distant as the bee and the octopus. Such learning is implemented by brains, or neuronal networks, and has been extensively studied within ethology, psychology, cognitive science, and neuroscience. Whether learning also takes place in nonneuronal settings has remained a matter of sustained controversy, too often dominated by ideological views. In this survey, I will explain how learning can be rigorously interpreted as a form of information processing and then explore the evidence for whether learning also takes place in organismal contexts outside the brain, such as physiology, development, and individual cells. I will try to explain why it is important to build bridges in this way between cognitive science and systems biology, why concepts and methods from various branches of engineering may be helpful in this task, and what the eventual impact may be on how we think about the organism.

Gene regulatory networks: from correlative models to causal explanations

Gene regulatory networks (GRNs) explain how the genome controls cellular behaviour and tissue morphogenesis, serving to connect molecular mechanism to functional output. Single-cell technologies now provide descriptions of these networks with unprecedented detail, but this advance has also revealed gene regulatory systems that are too complex for our existing conceptual frameworks. GRNs, which should provide mechanistic explanations, are increasingly reduced to statistical correlations — ‘hairballs’ that fail to capture molecular causation. Here, we explore why this dilemma exists and propose a path forward. We argue that methods in ‘representation learning’ can be used to model GRNs, without needing to capture every molecular detail. For this framework, we advocate three linked principles: models must be inherently mechanistic, with structures grounded in cellular and evolutionary biology; molecular principles and constraints must be used to reduce the solution space for learning GRN models; and more sophisticated forms of experimental perturbation and synthetic biological engineering are needed to train models and test predictions. By reimagining GRNs through these principles, we can bridge the gap from data abundance to new conceptual understanding.

Principles of Minimal Cognition: Casting Cognition as Sensorimotor Coordination

Within the cognitive sciences, cognition tends to be interpreted from an anthropocentric perspective, involving a stringent set of human capabilities. Instead, we suggest that cognition is better explicated as a much more general biological phenomenon, allowing the lower bound of cognition to extend much further down the phylogenetic scale. We argue that elementary forms of cognition can already be witnessed in prokaryotes possessing a functional sensorimotor analogue of the nervous system. Building on a case-study of the Escherichia coli bacterium and its sensorimotor system, the TCST-system, we home in on the characteristics of minimal cognition, and distinguish it from more basic forms of ontogenetic adaptation. In our view, minimal cognition requires an embodiment consisting of a sensorimotor coupling mechanism that subsumes an autopoietic organization; this forms the basis of the growing consensus that the core of cognition revolves around sensorimotor coupling. We discuss the relevance of our interpretation of minimal cognition for the study of cognition in general

Frameworks v0.2

FRAMEWORKS v0.2 Many of the thoughts in this document draw on and synthesize concepts from economics, math, physics, chemistry, biology, and psychology. Here are a handful of core concepts that are often relied on as inputs: Activation energy Behavioral economics Cognitive biases Darwinism En...

Molecular Biology in the Work of Deleuze and Guattari

This article looks at Deleuze and Guattari's understanding of molecular biology, focusing particularly on their reading of two highly influential works by the eminent French molecular biologists François Jacob and Jacques Monod, La logique du vivant (The Logic of Living Systems) and Le hasard et la nécessité (Chance and Necessity). In these two works, Jacob and Monod present the significance of molecular biology in broadly reductionist terms. What is more, the lac operon model of gene regulation that they propose serves to reinforce the so-called Central Dogma of molecular biology, according to which information passes from DNA to RNA to proteins, with no reverse route. However, Deleuze and Guattari discover intensive potentials within the descriptions of molecular biology offered by both writers. It is argued that Jacob's work in particular, as it has developed in the years since the publication of La logique du vivant in 1970, has itself developed these intensive potentials.