IV. Ecosmomics: Independent Complex Network Systems, Computational Programs, Genetic Ecode Scripts

C. Our Own HumanVerse (Epi) Genomic Heredity

Gorlich, Dennis. The Relational Basis of Molecular Codes. Biosemiotics. Online December, 2013. A University of Muenster and Jena School for Microbial Communication researcher proposes that illuminating insights for genomic and cellular studies could be gained by way of their semantic aspects. See also by Gorlich and Peter Dittrich “Molecular Codes in Biological and Chemical Reaction Networks” in PLoS One (8/1, 2013).

In this paper I reviewed the network based definition of molecular codes. While code nest can be used to define new measures of semantic capacity, i.e., a system’s capacity to realize semantic relationships between molecular species, code linkage can be used to formalize the notion of systems of codes. This, in general, can lead to a system based understanding of cells, especially in genome scale models. Both concepts, since they are applicable algorithmically, allow to base research in biosemiotics on data (and) network models. (Conclusion)

Greenbury, Sam, et al. The Effect of Scale-free Topology on the Robustness and Evolvability of Genetic Regulatory Networks. Journal of Theoretical Biology. 267/48, 2010. As the wholescale revision of genomes by way of nonlinear complex dynamics proceeds apace, Oxford and CalTech biophysicists and biochemists further illume and confirm how these native geometries indeed grace genomes.

We investigate how scale-free (SF) and Erdős–Rényi (ER) topologies affect the interplay between evolvability and robustness of model gene regulatory networks with Boolean threshold dynamics. In agreement with Oikonomou and Cluzel (2006) we find that networks with SFin topologies, that is SF topology for incoming nodes and ER topology for outgoing nodes, are significantly more evolvable towards specific oscillatory targets than networks with ER topology for both incoming and outgoing nodes. Similar results are found for networks with SFboth and SFout topologies. The functionality of the SFout topology, which most closely resembles the structure of biological gene networks is compared to the ER topology in further detail through an extension to multiple target outputs, with either an oscillatory or a non-oscillatory nature. (Abstract, 48)

Greenspan, Ralph. Selection, Gene Interaction, and Flexible Gene Networks. Stillman, Bruce, et al, eds. Evolution: The Molecular Landscape. Cold Spring Harbor, NY: Cold Spring Harbor Laboratory Press, 2009. In a review for this Darwin festschrift, a Kavli Institute for Brain and Mind (San Diego) geneticist advises that the “single-gene mutation” paradigm from the 1950s to c. 2000, is set aside for a 21st century view of arrays of dynamical interrelationships in such local and genomic topologies. But one may add this revolution goes beyond a theoretical revision. Rather it implies that these qualities spring from and exemplify an independent creative source. (See also papers by Dundr, and Del Bianco, in Cold Spring Harbor Perspectives in Biology (herein) which consider self-organizing agencies.)

Griffiths, Paul and Karola Stotz. Genetics and Philosophy: An Introduction. Cambridge: Cambridge University Press, 2013. University of Sydney philosophers of biology who have long been immersed in this discourse and debate provide a thorough coverage of the field and issues. As a general chronology, chapters flow from Mendel’s Gene and The Material Gene to The Reactive Genome, Outside the Genome, Gene as Information, Behavioral Gene, and The Evolving Gene. The last post-sequence decade is a necessary shift from reduction methods that found all the pieces to their subsequent whole systems integration. In regard, the newly dynamic genome now extends and opens beyond nucleotides to external environmental influences. But the work remains couched in “neo-mechanist” terms, while definitions vie as to what a gene might or might not be, again in abstractions. So in fairness, we quote from an abstract to Karola Stotz’s 2008 online paper “How (not) to be a Reductionist in a Complex Universe” (search Google).

This paper understands reductionism as a relation between explanations, not theories. It argues that knowledge of the micro-level behavior of the components of systems is necessary, but only combined with a full specification of the contingent context sufficient for a full explanation of systems phenomena. The paper takes seriously fundamental principles independent and transcendent of the laws of quantum mechanics that govern most of real-world phenomena. It will conclude in showing how the recent postgenomic srevolution, taking seriously the physical principle of organization and collective behavior, can be understood as attempting to complement a reductionist investigative strategy with an antireductionist explanatory strategy. (Stotz Paper)

Gu, Xun. An Evolutionary Model for the Origin of Modularity in a Complex Gene Network. Journal of Experimental Zoology. 312B/2, 2009. An Iowa State University geneticist further explicates how genome systems are distinguished by universal dynamical geometries.

Scale-free cellular networks are organized into a complex topology by massive interactions (links) between nodes, which can be typically characterized by a power-law degree. In contrast, almost all cellular networks show the feature of modularity. The popular BA model (Barabasi and Albert) demonstrated the origin of scale-free property by the attachment preference, but not for the origin of modularity. We propose a BBA model (Biological BA) by introducing the random link-loss mechanism under the original BA model, showing that scale-free and modularity can emerge as a derived property of the BBA model. (Abstract)

Harmon, Amy. That Wild Streak? Maybe It Runs in the Family. New York Times. June 15, 2006. A report on the latest appreciations of a genetic, familial basis for risky behavior, obesity, homosexuality, and so on.

Hebert, Paul, et al. Introduction: From Writing to Reading the Encyclopedia of Life. Philosophical Transactions of the Royal Society B. 371/20150321, 2016. University of Guelph, Canada, and Royal Botanic Garden, Edinburgh biologists open a theme issue entitled From DNA Barcodes to Biomes. A DNA barcode, in its simplest definition, is one or few relatively short gene sequences taken from a standardized portion of the genome and used to identify species. This device which can easily curate and record the vast fauna and flora biodiversity was conceived by Hebert a decade ago and now has become a global project. Typical entries are Telling Plant Species Apart with DNA, Biodiversity Analysis in the Digital Era, Bioinventories with DNA Barcodes, and DNA Barcoding and Taxonomy. For more info see International Barcode of Life: Evolution of a Global Research Community by Sarah Adamowicz in Genome (58/5, 2015), which issue also has Abstracts from the 6th International Barcode of Life Conference. Further articles are DNA Barcodes for Ecology, Evolution, and Conservation by John Kress, et al in Trends in Ecology and Evolution (30/1, 2015), and From Barcodes to Genomes: Extending the Concept of DNA Barcoding by Eric Coissac, et al in Molecular Ecology (25/1423, 2016). This tagging method employs fast sequencing techniques, and is coming into use to catalog creatures, along with agricultural pests, invasive species, wildlife forensics, disease vectors, biomonitoring of ecosystem health, and so on.

The use of DNA barcodes, which are short gene sequences taken from a standardized portion of the genome and used to identify species, is entering a new phase of application as more and more investigations employ these genetic markers to address questions relating to the ecology and evolution of natural systems. The suite of DNA barcode markers now applied to specific taxonomic groups of organisms are proving invaluable for understanding species boundaries, community ecology, functional trait evolution, trophic interactions, and the conservation of biodiversity. The application of next-generation sequencing (NGS) technology will greatly expand the versatility of DNA barcodes across the Tree of Life, habitats, and geographies as new methodologies are explored and developed. (Kress Abstract)

Heng, H. Q. Henry. The Genome-Centric Concept: Resynthesis of Evolutionary Theory. BioEssays. 31/5, 2009. An historic shift is much along, as this section and elsewhere reports, from an initial 20th century focus on nucleotides to a wholesale rethinking in terms of dynamical systems which suffuse and activate genomes. In this paper, a Wayne State University School of Medicine geneticist provides one of the most succinct contrasts and outlines so far. Such epigenetic, modular interrelations are then found to similarly carry and convey proscriptive information. These results are seen to imply a novel evolutionary synthesis in process beyond selection alone. One may also surmise that such universal nonlinear networks could themselves be seen as quite “genetic” in kind.

Self-organization refers to a process in which a higher-level pattern emerges spontaneously from the assembly of lower level components of the system. Diverse biological phenomena have been described as self-organizing (from the spontaneous folding of biomacromolecules to morphogenesis to the formation of ecosystems). Establishing the logical relationship between natural selection and self-organization presents a challenge for evolutionary theory. The genome-centric concept nicely incorporates these two concepts. Since self-organization is a diverse term spanning the fields of physics to social science, it is necessary to divide content of nature into distinct levels in order to understand multiple levels of interactive relationships between self-organization and selection. (521)

Hopkin, Karen. The Evolving Definition of a Gene. BioScience. December, 2009. A science writer reports on its constant revision as particulate DNA biomolecules become increasingly involved in epigenetic transcription processes.

Hosseini, Sayed-Rzgar and Andreas Wagner. Genomic Organization Underlying Deletional Robustness in Bacterial Metabolic Systems. Proceedings of the National Academy of Sciences. 115/7075, 2018. University of Zurich, Institute of Evolutionary Biology and Environmental Studies biologists continue with perceptions, in so many words, of a missing generative source for life’s evolutionary development and organic viability. See also herein The Architecture of an Empirical Genotype-Phenotype Map by Jose Aguilar-Rodriguez, et al for another angle by this central European collaboration.

From the organismal and the anatomical levels down to the molecular level, all complex biological systems manifest astonishing organization and order that are counterintuitive and challenging to explain by evolutionary mechanisms. In this study, we focus specifically on one aspect of this biological organization: the arrangement of metabolic genes in bacterial genomes. We show that this organization ensures a substantially higher robustness to large-scale gene deletions than expected from random genomic ordering. We systematically investigate the possible evolutionary mechanisms behind the emergence of such robust organizations. Our analysis provides several lines of evidence indicating that bacteria may have gained a robust genome organization through pervasive gene loss events. (Significance)

Houle, David, et al. Phenomics: The Next Challenge. Nature Reviews Genetics. 12/12, 2010. Another ‘-omics’ word as genetic studies continues to burst beyond the 20th century DNA helix. In this case, with various web definitions, it generally considers systems transferences between genotypes and phenotypes. And with other epigenetic turns, within a major-multi-level expansion, an evolutionary tandem trajectory of program and organism may be quite revealed.

Ideker, Trey, et al. A New Approach to Decoding Life: Systems Biology. Annual Review of Genomics and Human Genetics. 2/343, 2001. After bioinformatic sequencing of the human genome, the next research phase is to appreciate the complementary network properties of gene expression. By this approach a multilevel informational hierarchy of complex processes from DNA and protein interactions to organisms and ecologies can be constructed.

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