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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

Kaneko, Kunihiko. Life: An Introduction to Complex Systems Biology. Berlin: Springer, 2006. Published in August, a new volume by the Toyko University computational biologist is a basic text for this integrative approach.

What is life? Has molecular biology given us a satisfactory answer to this question? And if not, why, and how to carry on from there? This book examines life not from the reductionist point of view, but rather asks the question: what are the universal properties of living systems and how can one construct from there a phenomenological theory of life that leads naturally to complex processes such as reproductive cellular systems, evolution and differentiation? The presentation has been deliberately kept fairly non-technical so as to address a broad spectrum of students and researchers from the natural sciences and informatics.

Kitano, Hiroaki. Computational Systems Biology. Nature. 420/206, 2002. An introductory article to a special section about the application of sophisticated mathematical concepts and computer software which is able to discern universal principles across biomolecular, genetic, cellular and organismic levels.

Kohl, Peter and Denis Noble. Systems Biology and the Virtual Physiological Human. Molecular Systems Biology. 5/392, 2009. Oxford University philosophical physicians provide a synopsis of the current necessity to simply put back together and integrate all the reduced parts and pieces that a prior century of biological research has found. Indeed, each field from chemistry (Lehn) to child psychology (Overton) is engaged in making this obvious turn and course adjustment. The article was reprinted to lead off a special issue of EMBO Reports (10/S1, 2009) for more overviews of the Systems reunion, see e.g. Moya below

Systems biology may ne interpreted as a scientific approach (rather than a subject or destination) that consciously combines ‘reductionist’ (identification and description of parts) and ‘integrationist’ (internal and external interactions) research, to foster our understanding of the nature and maintenance of biological entities. (5)

Kolata, Gina. Bits of Mystery DNA, Far From ‘Junk,’ Play Crucial Role. New York Times. September 5, 2012. After the Human Genome Project, in 2003 the National Human Genome Research Institute began a next phase named ENCODE: Encyclopedia of DNA Elements. Pilot stage results were reported in June 2007 in Nature and Genome Research. This U.S. endeavor has since joined with the European Molecular Biology Laboratory, Hinxton, UK, and is further carried out across worldwide sites such as Cold Spring Harbor Biological Laboratory, Yale University, University of Massachusetts Medical School, onto, for example, the Center for Genomic Regulation, Barcelona, University of Geneva, and the Genome Institute of Singapore, altogether employing thousands of scientists. This news item reports its July 2012 major finding that supposed ‘dark matter’ or extraneous DNA in genomes, actually found plays a vital interconnective, regulatory role. The discoveries were announced via an array of six papers in Nature, and some 24 in Genome Research and Genome Biology. Google each journal name and ENCODE to access.

Among the many mysteries of human biology is why complex diseases like diabetes, high blood pressure and psychiatric disorders are so difficult to predict and, often, to treat. An equally perplexing puzzle is why one individual gets a disease like cancer or depression, while an identical twin remains perfectly healthy. Now scientists have discovered a vital clue to unraveling these riddles. The human genome is packed with at least four million gene switches that reside in bits of DNA that once were dismissed as “junk” but that turn out to play critical roles in controlling how cells, organs and other tissues behave. The discovery, considered a major medical and scientific breakthrough, has enormous implications for human health because many complex diseases appear to be caused by tiny changes in hundreds of gene switches.

As scientists delved into the “junk” — parts of the DNA that are not actual genes containing instructions for proteins — they discovered a complex system that controls genes. At least 80 percent of this DNA is active and needed. The result of the work is an annotated road map of much of this DNA, noting what it is doing and how. It includes the system of switches that, acting like dimmer switches for lights, control which genes are used in a cell and when they are used, and determine, for instance, whether a cell becomes a liver cell or a neuron.

Koonin, Eugene and Yuri Wolf. Evolutionary Systems Biology. Pagel, Mark and Andrew Pomiankowski, eds. Evolutionary Genomics and Proteomics. Sunderland, MA: Sineaur, 2008. Scientists at the National Center for Biotechnology Information, NIH, survey the many new “omics” approaches such as transcriptomics and metabolomics as biological research lately moves on to the equally real relational, dynamic nature of life at every domain. We note also in this volume dubbed “The Organismal Project,” a paper by Andreas Wagner on Gene Networks and Natural Selection which proposes an inherent “network biology” actively in place prior to selective effects.

Kulkarni, Vishwesh, et al, eds. A Systems Theoretic Approach to Systems and Synthetic Biology. Berlin: Springer, 2014. This is Volume I: Models and System Characterizations, Volume II is Analysis and Design of Cellular Systems. Its main subjects are Mathematical Analysis, and Biological Network Modelling.

Kumar, Suresh, et al. Deep Learning in Computational Biology: Advancements, Challenges, and Future Outlook. arXiv:2310.03086. Here is a good example of the pervasive Artificial Intelligence frontier becoming an accessible global faculty. This 30 page, 180 reference contribution by Faculty of Health and Life Sciences, Management and Science University, Malayasia scholars provides a unique, thorough, latest survey of the entire endeavor from neural net algorithms to a wide array of practical usages. So maybe our Earthificial name is a better identity so to foster shared Earthality benefits.

Deep learning has become a powerful tool in computational biology for the rapid analysis and interpretation of biological data over time. Here we review and evaluate its history, advantages, and challenges. Our focus is on two primary applications: DNA sequence classification and prediction, as well as protein structure prediction from relevant data. The use of deep learning in the analysis of DNA sequences has brought about a significant transformation in the detection of genomic variants and gene expression, which has enhanced to personalised medicine and drug discovery. (Excerpt)

Kutschera, Ulrich. Systems Biology of Eukaryotic Superorganisms and the Holobiont Concept. Theory in Biosciences. Online June, 2018. An evolutionary botanist (search) with postings at the University of Kassel, Germany and Stanford University writes a succinct tutorial of the past, present and future of this holistic shift and approach. Its origins are traced to Aristotle, Claude Bernard and Julius Sachs in the 19th century and in the mid 20th century to Ludwig von Bertalanffy and Mihajlo Mesarović, along with other contributors. The paper goes on about unicellular prokaryotes, animal and plant genomes, primate-microbe coevolution, and onto human health in this view. Looking ahead, a holobiont symbiosis between bacteria and an organism is once more advocated and explained.

The founders of modern biology were organismic life scientists who attempted to understand the morphology and evolution of living beings as a whole. However, with the emergence of animal and plant physiology in the nineteenth century, this “holistic view” of the living world was replaced by a reductionistic perspective. Here, I summarize the history of systems biology, i.e., the modern approach to understand living beings as integrative organisms, from genotype to phenotype. Definitions of systems biology are presented with reference to metabolic or cell signaling networks, via genomics, proteomics, and other methods, combined with computer simulations/mathematical modeling. Based on the microbe—Homo sapiens—symbiosis, it is concluded that human biology and health should be based on the holobiont concept. (Abstract excerpt)

Lander, Eric and Robert Weinberg. Genomics: Journey to the Center of Biology. Science. 287/1777, 2000. A congratulatory essay on sequencing the human genome along with a recognition of the need for a systems biology to appreciate whole living organisms.

Twentieth century biology triumphed because of its intensive analysis of the individual components of complex biological systems. The 21st century discipline will focus increasingly on the study of entire biological systems, by attempting to understand how component parts collaborate to create a whole. For the first time in a century, reductionists have yielded ground to those trying to gain a holistic view of cells and tissues. (1781)

Levine, Arnold. The Future of Systems Biology. Current Opinion in Systems Biology. 1/1, 2017. For an inaugural issue of this online journal, the Institute for Advanced Study, Princeton virologist and co-founder of this field two decades ago advises that its historic turn to join the organismic components with equally real dynamic interconnections, so as to form a whole entity, has reached a new level of mature advance. We collect salient entries from the first nine issues to June 2018 such as Physical Constraints in Biological Collective Behavior (search Cavagna).

Lucocq, John, et al. Systems Biology in 3D Space – Enter the Morphome. Trends in Cell Biology. 25/2, 2015. Aided by advanced nanoimaging techniques such as electron tomography and cryomicroscopy, University of St. Andrews, University of Nottingham, and European Molecular Biology Laboratory researchers advise that cellular studies is poised to enter a new integral, three dimensional phase of complete comprehension. Search Tim Mercer for similar work from Australia.

Systems-based understanding of living organisms depends on acquiring huge datasets from arrays of genes, transcripts, proteins, and lipids. These data, referred to as ‘omes’, are assembled using ‘omics’ methodologies. Currently a comprehensive, quantitative view of cellular and organellar systems in 3D space at nanoscale/molecular resolution is missing. We introduce here the term ‘morphome’ for the distribution of living matter within a 3D biological system, and ‘morphomics’ for methods of collecting 3D data systematically and quantitatively. A sampling-based approach termed stereology currently provides rapid, precise, and minimally biased morphomics. We propose that stereology solves the ‘big data’ problem posed by emerging wide-scale electron microscopy (EM) and can establish quantitative links between the newer nanoimaging platforms such as electron tomography, cryo-EM, and correlative microscopy. (Abstract)

Malod-Dognin, Noel and Natasa Przulj. Functional Geometry of Protein Interactomes. Bioinformatics. 35/19, 2019. Barcelona Supercomputing Center life scientists show how these metabolic processes can similarly be found to exhibit common network topologies, which can then be modeled by simplical complexes just like the brain. See also Centralities in Simplical Complexes: Applications to Protein Interaction Networks by Ernesto Estrada and Grant Ross in the Journal of Theoretical Biology (438/46, 2018).

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