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A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
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V. Life's Corporeal Evolution Develops, Encodes and Organizes Itself: An EarthWinian Genesis Synthesis

B. Systems Biology Unites: EvoDevo, Genomes, Cells, Networks, Symbiosis, Homology, Inherency

Caetano-Anolles, Kelsey, et al. A Minimal Framework for Describing Living systems: A MultiDimensional View of Life Scales. Integrative & Comparative Biology. 61/6, 2021. Seven senior bioscholars post this Jumpstart Reintegrating Biology Vision Paper based on their 2020 meetings. As a result, a Scale-Invariant ECSI Framework (see Abstract) section spans from molecules, cells and organs to organisms, communities and ecosystems with a tabulated description for the emergent phases. A graphic depiction proceeds to view these evolutionary and metabolic occasions as a common, sewuential recurrence at each stage. Life’s informational quality is then said to be most important. A discussion about Unifying Life-science Research from Genomes to Phenomes to Bionomes wraps up going forward. Let us hope that this EarthWise phase of convergent synthesis with a universal code-like basis can illume a true Discovery Decade that peoples and planet so need.

The intricate complexity of biology has led to two general approaches. One is reductionism whence high-level whole systems emerge from simpler interactions at lower levels. Another is for specialists to investigate a specific hierarchical level. But these methods limit the scope and integration of knowledge and prevent a synoptic view of life. For this purpose, scale-invariant properties need to be identified that are present at all spatiotemporal phases. Here we will propose four resource aspects - energy, conductance, storage, and information (ECSI) – as a way to reintegrate and unify life science. (Abstract excerpt)

Carey, Nessa. The Epigenetics Revolution. New York: Columbia University Press, 2012. A popular entry by a British biologist with equal academic and industrial tenures about the realization, after its 20th century gene to trait basis, that much more is going on between molecular programs, actual organisms, and variegated environments. By a deft use of metaphor, DNA is not a mechanical blueprint, rather more like a play script or musical score. Romeo and Juliet, for example, has been staged and filmed in vastly different venues. DNA indeed acts a lot like a language. Epigenetics is then a two way communicative interaction that ultimately serves to produce life’s diverse phenotypes.

Carroll, Sean B. Evo-Devo and an Expanding Evolutionary Synthesis. Cell. 134/1, 2008. A leading researcher and communicator provides a cogent review, subtitled A Genetic Theory of Morphological Evolution, on the interactive reunion and meld of development and phylogeny. Salient tenets are said to include: mosaic pleiotropy, ancestral genetic complexity, deep homology, heterotopy, vast cis-regulatory modularity and networks, and the conservation of gene tool-kits.

Cavagna, Andrea, et al. Physical Constraints in Biological Collective Behavior. Current Opinion in Systems Biology. 9/49, 2018. Systems scholars AC and Irene Giardina, Sapienza University of Rome, with Thierry Mora and Aleksandra Walczak, Sorbonne University, Paris, each of whom have joined this integrative quest for some years (search) post a Spring 2018 entry which might be its strongest fulfillment to date. As the quotes aver, by way of detailed studies of bird flocks or microbial colonies, along with similar observations across macro societal realms and micro active material depths, an epochal discovery comes into full view. At once, the “same phenomenal, iconic theory and principle” can be seen in generative effect at every instance and scale. This cosmic to culture, universe to us, vista which a worldwise intelligence has well quantified, then implies and requires an independent, universally exemplified, mathematical source. See also Dynamic Scaling in Natural Swarms by this group in Nature Physics (September 2017) for more about a statistical physics of renormalization and self-similarities.

Many biological systems require the coordinated operation of a large number of agents linked together by complex interactions in order to achieve their function reliably. Because of the complex relationship between individual laws and system-level behaviour, theory is needed to assess emergent phenomena which follow from logical or physical constraints. Here we illustrate this crucial role of theory through recent examples from the collective motion of bird flocks. In some cases abstract theoretical laws explain the emergence of some apparently surprising traits, without the need to invoke new assumptions. Conversely, quantitative theoretical predictions sometimes show that general mathematical and physical laws are incompatible with otherwise mundane observations, forcing us to reconsider our assumptions and leading us to discover new principles. (Abstract)

The perspective has inspired the whole field of living active matter and physics-based modeling of biological collectives. Many results on active systems at the micro-scale (cell tissues, bacterial colonies, microtubules) support the value of this approach. It turns out that the same theory can equally well predict the large scale behavior of living assemblies and inanimate active matter, which share the same fundamental properties. Recent findings on bird flocks and insect swarms indicate that these animal groups satisfy static and dynamic scaling laws: the large scale properties of the system under different conditions (number of individuals, density), can be described by a single master function. Laws of this kind are the phenomenological underpinning of universality in condensed matter materials, and suggest that the effective theoretical framework used for inanimate systems is also justified when looking at coherent animal groups at large scales. (50)

Ceska, Milan and David Safranek, eds. Computational Methods in Systems Biology. International: Springer, 2018. The Proceedings of the 16th International Conference on this title subject (CMSB) held in Brno, Czech Republic, in September. Some entries are Deep Abstractions of Chemical Reactions Networks, Synthesis for Vesicle Traffic Systems, and Experimental Biological Protocols with formal Semantics. May one then wonder, what grand phenomena, of we are as yet unawares, is our worldwise sapiensphere coming upon, trying to learn, provide a cosmic self-describe? What is going on, what language is natural genesis written in? Who are we phenomenal human beings to be able to do this, for what purpose? Does a universal procreation want us to intentionally take from here?

The 15 full and 7 short papers presented together with 5 invited talks were selected from 46 submissions. Topics of interest include formalisms for modeling biological processes; models and their biological applications; frameworks for model verification, validation, analysis, and simulation of biological systems; high-performance computational systems biology; parameter and model inference from experimental data; automated parameter and model synthesis; model integration and biological databases; multi-scale modeling and analysis methods; design, analysis, and verification methods for synthetic biology; methods for biomolecular computing and engineered molecular devices.

Chuang, Han-Yu, et al. A Decade of Systems Biology. Annual Review of Cell and Developmental Biology. 26/23.1, 2010. With coauthors Matan Hofree and Trey Ideker, University of California, San Diego scientists provide a chapter survey that reviews the integral bioinformatic approaches and advances that life’s dynamic connectivities, here dubbed the “translational sciences.”

Civelek, Mete and Aidons Lusis. Systems Genetics Approaches to Understand Complex Traits. Nature Reviews Genetics. 15/1, 2014. UCLA geneticists and microbiologists provide a succinct entry to this paradigm shift as separate nucleotides and biomolecules now become interconnected and networked within broadly conceived genomes.

Systems genetics is an approach to understand the flow of biological information that underlies complex traits. It uses a range of experimental and statistical methods to quantitate and integrate intermediate phenotypes, such as transcript, protein or metabolite levels, in populations that vary for traits of interest. Systems genetics studies have provided the first global view of the molecular architecture of complex traits and are useful for the identification of genes, pathways and networks that underlie common human diseases. Given the urgent need to understand how the thousands of loci that have been identified in genome-wide association studies contribute to disease susceptibility, systems genetics is likely to become an increasingly important approach to understanding both biology and disease. (Abstract)

Systems genetics shares with systems biology a holistic, global perspective. The typical strategy in systems biology is to perturb a system, monitor the responses, integrate the date and formulate mathematical models that describe the system. Systems genetics is a particular type of systems biology, in which genetic variation within a populations is used to perturb the system. Ultimately, the goal of systems genetics is to understand the broad molecular underpinnings, such as genetic architecture and intermediate physiological phenotypes, of complex traits, including diseases. (35)

Clarke, Declan, et al. Novel Insights through the Integration of Structural and Functional Genomics Data with Protein Networks. Journal of Structural Biology. 179/3, 2012. With coauthors Nitin Bhardwaj and Mark Gerstein, Yale University systems geneticists, whose laboratory is an ENCODE Project research site, offer another take on the native presence, beyond discrete nucleotide or codons, of interconnective networks composed of elemental “node” and cross-linking “edge” phases. These dual complements, (DNA/AND), then constitute and distinguish a whole genome. The article details a further finesse of network topologies, whereof nodes themselves are often nested nets within encompassing scale-free (epi)genomic hierarchies.

In recent years, major advances in genomics, proteomics, macromolecular structure determination, and the computational resources capable of processing and disseminating the large volumes of data generated by each have played major roles in advancing a more systems-oriented appreciation of biological organization. One product of systems biology has been the delineation of graph models for describing genome-wide protein–protein interaction networks. The network organization and topology which emerges in such models may be used to address fundamental questions in an array of cellular processes, as well as biological features intrinsic to the constituent proteins (or “nodes”) themselves. However, graph models alone constitute an abstraction which neglects the underlying biological and physical reality that the network’s nodes and edges are highly heterogeneous entities. Here, we explore some of the advantages of introducing a protein structural dimension to such models, as the marriage of conventional network representations with macromolecular structural data helps to place static node and edge constructs in a biologically more meaningful context. (Abstract, 320)

Biological networks are conventionally represented as maps of nodes and edges, wherein nodes represent biological entities (such as a gene, protein, or mRNA) and edges represent interactions between these entities (such as regulation or physical association). (320)

Cohen, Irun. Tending Adam’s Garden: Evolving the Cognitive Immune Self. San Diego: Academic Press, 2000. An engaging, erudite entry by the Weizmann Institute of Science immunologist to the present reconception of the immune system as an ecology of nonlinear networks that dynamically organize themselves. By so doing, immune responses become cognitive and decisive in kind, similar in activity to self-organizing brains. Just as our neural capacity creates itself out of on-going experience, so somatic immune reactions arise from its vicarious environment. So then as for Adam, our own self makes up its unique individuality. The quote is from the topical headings for a ‘Self-Organization’ section. (For Cohen’s recent work see Explaining a Complex Living System: Dynamics, Multi-scaling and Emergence, with David Harel in Journal of the Royal Society Interface 4/175, 2007.)

Cognitive systems organize themselves as they evolve; what is self-organization and learning? Biologic evolution is the self-organization of species. Individual and cultural self-organization is somatic. Complexity is progressive. (82)

Cornish-Bowden, Athel. Putting the Systems Back into Systems Biology. Perspectives in Biology and Medicine. 49/4, 2006. Although this phrase is much bandied about today in biological science, in actuality, as researchers admit, the reductive project goes on as usual. To truly conceive and carry out imperative systemic studies of life, we need to recall the earlier contributions of the philosophical biologists Ludwig von Bertalanffy and Robert Rosen.

Cornish-Bowden, Athel, et al. Beyond Reductionism: Metabolic Circularity as a Guiding Vision for a Real Biology of Systems. Proteomics. 7/6, 2007. A typical article from a special issue on Systems Biology which the long quote well conveys.

The definition of life has excited little interest among molecular biologists during the past half-century, and the enormous development in biology during that time has been largely based on an analytical approach in which all biological entities are studied in terms of their components, the process being extended to greater and greater detail without limit. The benefits of this reductionism are so obvious that they need no discussion, but there have been costs as well, and future advances, for example, for creating artificial life or for taking biotechnology beyond the level of tinkering, will need more serious attention to be given to the question of what makes a living organism living. According to Robert Rosen's theory of metabolism-replacement systems, the central idea missing from molecular biology is that of metabolic circularity, most evident from the obvious but commonly ignored fact that proteins are not given from outside but are products of metabolism, and thus metabolites. Among other consequences, this implies that the usual distinction between proteome and metabolome is conceptually artificial - however useful it may be in practice - as the proteome is part of the metabolome. (839)

Coruzzi, Gloria and Rodrigo Gutierrez, eds. Plant Systems Biology. Oxford: Oxford University Press, 2009. Volume 35 of Annual Plant Reviews that dutifully covers the whole range of this budding approach from generic complexity principles by Reka Albert and Sarah Assmann, to their active presence from fauna genomes to the range of epigenomes, proteomes, metabolomes, and so on. Another integrative paper “Perspectives on Ecological and Evolutionary Systems Biology” by Christina Richards, et al continues into bioregional realms.

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