Julyan H. E. Cartwright;Jitka Čejková;Elena Fimmel;Simone Giannerini;Diego Luis Gonzalez;Greta Goracci;Clara Grácio;Jeanine Houwing-Duistermaat;Dragan Matić;Nataša Mišić;Frans A. A. Mulder;Oreste Piro
{"title":"Information, Coding, and Biological Function: The Dynamics of Life","authors":"Julyan H. E. Cartwright;Jitka Čejková;Elena Fimmel;Simone Giannerini;Diego Luis Gonzalez;Greta Goracci;Clara Grácio;Jeanine Houwing-Duistermaat;Dragan Matić;Nataša Mišić;Frans A. A. Mulder;Oreste Piro","doi":"10.1162/artl_a_00432","DOIUrl":null,"url":null,"abstract":"In the mid-20th century, two new scientific disciplines emerged forcefully: molecular biology and information-communication theory. At the beginning, cross-fertilization was so deep that the term genetic code was universally accepted for describing the meaning of triplets of mRNA (codons) as amino acids. However, today, such synergy has not taken advantage of the vertiginous advances in the two disciplines and presents more challenges than answers. These challenges not only are of great theoretical relevance but also represent unavoidable milestones for next-generation biology: from personalized genetic therapy and diagnosis to Artificial Life to the production of biologically active proteins. Moreover, the matter is intimately connected to a paradigm shift needed in theoretical biology, pioneered a long time ago, that requires combined contributions from disciplines well beyond the biological realm. The use of information as a conceptual metaphor needs to be turned into quantitative and predictive models that can be tested empirically and integrated in a unified view. Successfully achieving these tasks requires a wide multidisciplinary approach, including Artificial Life researchers, to address such an endeavour.","PeriodicalId":55574,"journal":{"name":"Artificial Life","volume":"30 1","pages":"16-27"},"PeriodicalIF":1.6000,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Artificial Life","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10541955/","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
In the mid-20th century, two new scientific disciplines emerged forcefully: molecular biology and information-communication theory. At the beginning, cross-fertilization was so deep that the term genetic code was universally accepted for describing the meaning of triplets of mRNA (codons) as amino acids. However, today, such synergy has not taken advantage of the vertiginous advances in the two disciplines and presents more challenges than answers. These challenges not only are of great theoretical relevance but also represent unavoidable milestones for next-generation biology: from personalized genetic therapy and diagnosis to Artificial Life to the production of biologically active proteins. Moreover, the matter is intimately connected to a paradigm shift needed in theoretical biology, pioneered a long time ago, that requires combined contributions from disciplines well beyond the biological realm. The use of information as a conceptual metaphor needs to be turned into quantitative and predictive models that can be tested empirically and integrated in a unified view. Successfully achieving these tasks requires a wide multidisciplinary approach, including Artificial Life researchers, to address such an endeavour.
期刊介绍:
Artificial Life, launched in the fall of 1993, has become the unifying forum for the exchange of scientific information on the study of artificial systems that exhibit the behavioral characteristics of natural living systems, through the synthesis or simulation using computational (software), robotic (hardware), and/or physicochemical (wetware) means. Each issue features cutting-edge research on artificial life that advances the state-of-the-art of our knowledge about various aspects of living systems such as:
Artificial chemistry and the origins of life
Self-assembly, growth, and development
Self-replication and self-repair
Systems and synthetic biology
Perception, cognition, and behavior
Embodiment and enactivism
Collective behaviors of swarms
Evolutionary and ecological dynamics
Open-endedness and creativity
Social organization and cultural evolution
Societal and technological implications
Philosophy and aesthetics
Applications to biology, medicine, business, education, or entertainment.