Selfvariants

Selfvariants is a cross-disciplinary term used to describe variants or variant-generating processes that originate from within a system, rather than being introduced by external inputs. The concept is not standardized to a single field, but is employed to discuss endogenous diversity arising from internal mechanisms.

In biology, self-variants typically refer to somatic mutations that occur during cell division. These de novo changes create mosaic patterns in which different cells carry distinct genomes. Somatic mosaicism is relevant to development, aging, and disease, including cancer, where clonal expansion of advantageous variants drives tumor evolution. Distinctions are often made between germline variants, inherited and present in every cell, and somatic selfvariants restricted to certain tissues or lineages.

In textual criticism and literary studies, a self-variant can describe an author’s revision of their own work, producing later versions that differ from the original text. Analyzing self-variants helps scholars trace authorial development, editorial practices, and the historical reception of a work.

In computing and artificial intelligence, self-variants describe outputs or configurations produced by a system through self-modification, evolutionary processes, or generative models. Evolutionary algorithms, self-modifying code, and self-augmenting programs produce populations of self-variants to explore solutions, improve robustness, or adapt to changing tasks and data.

Implications of selfvariants include insights into disease mechanisms and personalized medicine in biology, understanding textual authorship and revision histories, and advancing optimization and creative potential in computational systems. Challenges include distinguishing true endogenous variation from noise and ensuring reproducibility of self-generated results. See also mosaicism, clonal evolution, quines, and evolutionary computation.