BioSystems encourages theoretical, computational, and experimental articles that link biology, evolutionary concepts, and the information sciences. The journal is dedicated to publishing research on self-organizing information systems—with the goal of obtaining a better understanding of the origins of biochemical, genetic, epigenetic, physiological, cognitive, linguistic, sociocultural, and biological organization and evolution.The scope of the journal encompasses the fundamental nature of biological information and (self)-organization. This includes quantum phenomena in information transfer, natural computing, biological coding systems, biological complexity, theoretical biology, artificial life, computational modeling of complex biological systems, evolutionary models of computation, 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.The journal does not publish purely medical, computational, or ecological research, unless it is clearly linked to the basic and conceptual aspects of biological organization.The editors encourage articles that deal, in particular, with the following topics:Biological computationMolecular recognitionPhysical foundations of biologyQuantum phenomena in biological systemsCellular controlNeuromolecular computingBiological coding systemsMolecular computing processesSelf-organizing and self-replicating systemsOrigin of the genetic codeOrigins and evolution of genomesStochastic evolutionary algorithmsOrigins and evolution of mind and languageEcological evolutionary developmental biologyReticulate evolution (symbiosis, symbiogenesis, lateral gene transfer)Simulation of genetic and ecological systemsApplications (neural nets, machine learning, robotics)History and philosophy of scienceIn addition, the editors encourage the following types of papers for submission: Papers that extract novel biological insights from multidimensional data, using AI-driven language modelsBiological hypothesis papers producing new insights based on a body of pre-existing empirical researchPerspectives papers intended to stimulate scientific discussions and provide guidelines for future directions
Mathematical Biosciences publishes work providing new concepts or new understanding of biological systems using mathematical models, or methodological articles likely to find application to multiple biological systems. Papers are expected to present a major research finding of broad significance for the biological sciences, or mathematical biology. Mathematical Biosciences welcomes original research articles, letters, reviews and perspectives.
