A NLP based Generative AI Model for Genomic Sequence Generation: A Bioinformatics Approach

DNA sequence generation is now turning into this kind of more recent research space, sort of mixing
Natural Language Processing, Generative AI , and Bioinformatics together. It feels a bit like how human
language works , because DNA is basically built from sequential symbols that keep biological knowledge,
or at least that’s the usual story. Transformer based language models like GPT, BERT , and T5 have
really shown they can learn genomic representations and afterwards produce DNA sequences that seem
biologically reasonable. Here, a full study is laid out about DNA sequence generation, using NLP plus
generative AI techniques, and there’s also a lot of attention to the full pipeline. The method includes
genomic data preprocessing, k-mer tokenization, transformer style sequence modeling, an autoregressive
way to generate DNA, and then biological validation to check what came out.