(logo) Natural Genesis (logo text)
A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
Table of Contents
Introduction
Genesis Vision
Learning Planet
Organic Universe
Earth Life Emerge
Genesis Future
Glossary
Recent Additions
Search
Submit

IV. Ecosmomics: Independent, UniVersal, Complex Network Systems and a Genetic Code-Script Source

2. The Innate Affinity of Genomes, Proteomes and Language

Hackenberg, Michael, et al. Clustering of DNA Words and Biological Function: A Proof of Principle. Journal of Theoretical Biology. 297/127, 2012. University of Granada and University of Malaga, Spain system biologists including Pedro Carpena contribute to historic 2010s verifications that the molecular nucleotide version and human cultural literature are one and the same, that they are formed and suffused by the same informative nonlinear complex network systems. View articles of this kind, for example, in the journal Complexity over recent years.

Relevant words in literary texts (key words) are known to be clustered, while common words are randomly distributed. Given the clustered distribution of many functional genome elements, we hypothesize that the biological text per excellence, the DNA sequence, might behave in the same way: k-length words (k-mers) with a clear function may be spatially clustered along the one-dimensional chromosome sequence, while less-important, non-functional words may be randomly distributed. To explore this linguistic analogy, we calculate a clustering coefficient for each k-mer (k=2–9 bp) in human and mouse chromosome sequences, then checking if clustered words are enriched in the functional part of the genome. The clustering of DNA words thus appears as a novel principle to detect functionality in genome sequences. As evolutionary conservation is not a prerequisite, the proof of principle described here may open new ways to detect species-specific functional DNA sequences and the improvement of gene and promoter predictions, thus contributing to the quest for function in the genome. (Abstract excerpt)

Heckmeier, Philipp, et al.. A billion years of evolution manifest in nanosecond protein dynamics. PNAS. 121/10, 2024. We cite this paper by University of Zurich and Columbia University biochemists as an example of how far the scope and range of these current techniques can reach. And again who are we peoples with an Earthomo sapience to be able to look down and back and reconstruct and re-present how it all came to occur?

Protein dynamics forms a broad bridge between structure and function, yet the impact of evolution on ultrafast protein processes remains enigmatic. This study delves into the nanosecond-scale phenomena of a conserved protein across species separated by almost a billion years as a way to investigate ten complex homologs. In so doing, we found a cascade of rearrangements which manifest in discrete time points over hundreds of millions of years. Our work poses a novel scientific inquiry within molecular paleontology compared by the rapid pace of protein processes which can connect the shortest time scale in living matter (10^-9 s) with the largest ones (10^16 s). (Abstract)

Holzer, Jacqueline. Genomes & Language. http://www.liu.se/isk/research/doc/Birgitta_forum.pdf. An extensive summary from a Birgitta Forum held in August 2002 in Vadstena, Sweden, reviewed more in Emergent Genetic Information.

Holzer, Jacqueline. Genomes & Language. http://www.liu.se/isk/research/doc/Birgitta_forum.pdf. A website for the conference program and lengthy Concluding Reflections from a Birgitta Forum held in August 2002 in Vadstena, Sweden. Geneticists and linguists are finding much commonality between these archetypal formative modes upon which our life and world is founded. A main resource is the work of the German philosopher Wolfgang Raible, who also spoke, Google for his 2001 paper “Linguistic and Genetics. Systematic Parallels”.

Geneticists, when presenting the structure of the human genome, seem to find the metaphor of the genome as a book, or a text, useful. Genomes and texts are both multiply articulated structures, where purely contrastive units – phonemes, letters, bases – combine to form meaningful units at several levels of increasing complexity – words, sentences, texts; codons, genes, chromosomes. (4) In a very profound way he (Raible) shows the structural similarities between linguistics and genetics and sees herein a “deeper relationship between the ‘grammar of biology’ and the grammar of natural languages.” In both systems, the principles allowing the reconstruction of multi-dimensional wholes from linear sequences of basic elements are identical: double articulation, different classes of ‘signs,’ hierarchy, combinatorial rules: wholes are always more that the sum of their parts. (Holzer, 5)

Hwang, Yunha, et al. Genomic language model predicts protein co-regulation and function. Nature Communications.. 15/2880, 2024. We enter this work by Cornell, Harvard, Johns Hopkins, and MIT biologists including Sergey Ovchinnikov as another literate version of the textual affinity of nucleotides and narratives. See also ProteinEngine: Empower LLM with Domain Knowledge for Protein Engineering at arXiv:2405.06658.


Deciphering the relationship between a gene and its genomic context is vital to understand and modify biological systems. Machine learning can study the sequence-structure-function paradigm but higher order genomic information remains elusive. Evolutionary processes dictate genomic contexts in which a gene occurs across phylogenetic distances, and these emergent patterns can be leveraged to uncover functional relationships. Here, we train a genomic language model (gLM) on metagenomic scaffolds to uncover regulatory relationships between genes. Our findings illustrate that gLM’s deep learning of metagenomes is an effective approach to encode the semantics and syntax of genes and uncover complex relationships in a genomic region. (Abstract)

The unprecedented amount and diversity of metagenomic data presents opportunities to learn hidden patterns and structures of biological systems. With larger amounts of data, these models can disentangle the complexity of organismal genomes and their encoded functions. The work presented here validates the concept of genomic language modeling. Our implementation of the masked genomic language modeling illustrates the feasibility of training such a model, and provides evidence that biologically meaningful information is being captured in learned contextualized embeddings. (9)

Igamberdiev, Abir and Nikita Shklovskiy-Kordi. Computational Power and Generative Capacity of Genetic Systems. BioSystems. 142-143/1, 2016. A Memorial University of Newfoundland theoretical biologist and a National Research Center for Hematology, Moscow research physician contribute to the intent of this journal (second quote) to achieve a natural philosophy of life’s evolution as an oriented ascent from an innately conducive cosmos. In this encompassing genesis, a “generative” agency is a textual essence which rises in kind from a physical matrix to genomic and linguistic manifestations. Once again, after decades of study, it is strongly put that these two prime codes are one and the same.

In his many writings, AI cites Aristotelian, Greek, and Renaissance roots to provide a historical heritage for this 21st century resolve. In this paper it is said that Heraclitus’ “self-growing Logos” can now be confirmed. See his website at www.mun.ca/biology/igamberdiev/index.php for a publications page, such as Relational Universe of Leibniz (2105), and Semiotic Autopoiesis of the Universe (2001). A “quantum measurement” theory is broached here, explained more elsewhere, which means that biological systems survive, evolve, and prosper by recursively comparing new experience with prior experiential representations.

Semiotic characteristics of genetic sequences are based on the general principles of linguistics formulated by Ferdinand de Saussure, such as the arbitrariness of sign and the linear nature of the signifier. Besides these semiotic features that are attributable to the basic structure of the genetic code, the principle of generativity of genetic language is important for understanding biological transformations. The problem of generativity in genetic systems arises to a possibility of different interpretations of genetic texts, and corresponds to what Alexander von Humboldt called “the infinite use of finite means”. These interpretations appear in the individual development as the spatiotemporal sequences of realizations of different textual meanings, as well as the emergence of hyper-textual statements about the text itself, which underlies the process of biological evolution. These interpretations are accomplished at the level of the readout of genetic texts by the structures, which includes DNA, RNA and the corresponding enzymes operating with molecular addresses. The molecular computer performs physically manifested mathematical operations and possesses both reading and writing capacities. Generativity paradoxically resides in the biological computational system as a possibility to incorporate meta-statements about the system, and thus establishes the internal capacity for its evolution. (Abstract)

Life is a self-organizing and self-generating activity of open non-equilibrium systems determined by their internal semiotic structure. My vision of life in the Universe is based on the principles of the quantum measurement theory, which can be considered as a mirrored image of theoretical biology. Life by its existence in self-reflecting loops establishes basic physical parameters of the Universe. The philosophical background of this approach is in Greek philosophy, in monadology of Leibniz, and in the organism philosophy of A. N. Whitehead. The field of theoretical biology is a description of systems that possess their own embedded description. Life always maintains and solves these paradoxes since living organisms possess their internal description. The structure of the Universe includes a self-reflective loop to be observable, i.e. existing. (AI site Theoretical Biology)

BioSystems encourages experimental, computational, and theoretical articles that link biology, evolutionary thinking, and the information processing sciences. The link areas form a circle that encompasses the fundamental nature of biological information processing, computational modeling of complex biological systems, evolutionary models of computation, the application of biological principles to the design of novel computing systems, and the use of biomolecular materials to synthesize artificial systems that capture essential principles of natural biological information processing.

Jolma, Arttu, et al. DNA-dependent Formation of Transcription Factor Pairs Alters Their Binding Specificity. Nature. 527/384, 2015. A Karolinska Institute, Sweden group and colleagues, led by Jussi Talpale, report a unique parsing of nucleotide genetics by treating them much as a linguistic script. The achievement was noted in a Science Daily item for November 15, 2015 (Google SD and article keywords) entitled Complex Grammar of the Genomic Language. A gene regulatory code is thus composed by “DNA words,” which can be seen to combine and compound just as lexicons and sentences.

Kay, Lily. A Book of Life?: How the Genome Became an Information System and DNA a Language. Perspectives in Biology and Medicine. 41/4, 1998. The late philosopher of science discerns intrinsic congruities between the verbal and genetic codes.

Kay, Lily. Who Wrote the Book of Life? Stanford, CA: Stanford University Press, 2000. A premier history of science study of how a linguistic metaphor came to represent the genetic code. The author goes on to note a correspondence between molecular genetics, language and the Chinese divination system, the I Ching.

As with (linguist Roman) Jakobson, the answer was affirmative (to the question of one basic code) and pointed to a universe fundamentally different from that portrayed in Jacques Monod’s Chance and Necessity. Rather than viewing DNA-based life as a product of chance, it would be chance subject to the structures and patterns of the I Ching. And rather than being a gypsy living on the edge of an alien world, as Monod decried, a human being would enjoy a deep sense of security that emerged from being planted physically and spiritually in an internal natural order. (318)

Lackova, Ludmila, et al. Arbitrariness is not Enough: Towards a Functional Approach to the Genetic Code. Theory in Biosciences. Online May, 2017. Palacky University, Olomouc, Czech Republic linguists Lackova, Vladimir Matlach, and Dan Faltynek build a case for a semiotic definition of genomic conveyance. By this view, similar to written and oral communications, nucleotides and proteins are all about signs, symbols, interpretation and transcription. Apropos, from our home page a slide presentation, Cosmic Genesis in the 21st Century, that I gave at Palacky University in 2005 can be accessed.

Arbitrariness in the genetic code is one of the main reasons for a linguistic approach to molecular biology: the genetic code is usually understood as an arbitrary relation between amino acids and nucleobases. However, from a semiotic point of view, arbitrariness should not be the only condition for definition of a code, consequently it is not completely correct to talk about “code” in this case. Semiotically, a code should be always associated with a function and we propose to define the genetic code not only relationally (in basis of relation between nucleobases and amino acids) but also in terms of function (function of a protein as meaning of the code). In fact, if the function of a protein represents the meaning of the genetic code (the sign’s object), then it is crucial to reconsider the notion of its expression (the sign) as well. In our contribution, we will show that the actual model of the genetic code is not the only possible and we will propose a more appropriate model from a semiotic point of view. (Abstract)

Lackova, Ludmilla. Folding of a Peptide Continuum: Semiotic Approach to Protein Folding. Semiotica. 233/77, 2020. The Palacky University, Olomouc, CR linguist continues her studies of innate affinities across genetic, metabolic and onto communicative codes, which each seem to have a common textual nature. What then might be their phenomenal message as we first grade readers try to interpret, translate and understand?

In this paper I attempt to study the notion of “folding of a semiotic continuum” in a direction of a possible application to the biological processes (protein folding). The process of obtaining protein structures is compared to the folding of a semiotic continuum. Consequently, peptide chain is presented as a continuous line potential to be formed (folded) in order to create functional units. The functional units are protein structures having a certain usage in the cell or organism (semiotic agents). Moreover, protein folding is analyzed in terms of tension between syntax and semantics. (Abstract)

Lee, Ji-Hoon, et al. A DNA Assembly Model of Sentence Generation. BioSystems. Online, June, 2011. Seoul National University, Kyungpook National University, and University of Arkansas, bioinformatic scientists add to the evidence that these widely separated generative sources of life and culture share deep affinities with regard to their grammatical structures. Since the inklings of Roman Jakobson and Jean Piaget in the 1970s and earlier that genome and “languagome” (just coined) are deeply similar, this emergent evolutionary correspondence has been steadily proven, which this whole section seeks to document.

Recent results of corpus-based linguistics demonstrate that context-appropriate sentences can be generated by a stochastic constraint satisfaction process. Exploiting the similarity of constraint satisfaction and DNA self-assembly, we explore a DNA assembly model of sentence generation. The words and phrases in a language corpus are encoded as DNA molecules to build a language model of the corpus. Given a seed word, the new sentences are constructed by a parallel DNA assembly process based on the probability distribution of the word and phrase molecules. Here, we present our DNA code word design and report on successful demonstration of their feasibility in wet DNA experiments of a small scale. (Abstract)

Previous   1 | 2 | 3 | 4 | 5 | 6 | 7  Next