The Genome as a Contextual Information Processor: A Systems Biology Framework for Biocomputational Genetics and Artificial Intelligence

This preprint proposes the concept of Contextual Genetic Intelligence, a theoretical perspective suggesting that genomic function may be understood as a form of distributed biological information processing emerging through interactions among genes, regulatory elements, epigenetic modifications and environmental influences. Within this framework, the genome is not interpreted solely as an instructional archive inherited across generations but as an adaptive regulatory ecosystem in which functional outcomes depend upon cellular context and network-level organisation. Consequently, biological meaning is proposed to arise through dynamic relationships rather than through isolated genetic components. Building upon this perspective, the manuscript introduces Biocomputational Genetics as an interdisciplinary conceptual framework situated at the convergence of systems biology, bioinformatics and artificial intelligence. Unlike conventional predictive approaches that prioritise classification and association, biocomputational genetics seeks to investigate how biological systems generate adaptive responses through context-sensitive regulatory interactions. Artificial intelligence is therefore considered not only as an analytical instrument but also as a source of theoretical inspiration for understanding emergent properties within genomic systems.