Insights in computational genomics: 2022

The goal of this Research Topic is to shed light on the progress made in the past decade in the Computational Genomics field, to gauge its future challenges, and to provide a thorough overview of the field's current status. We hope that this article Research Topic will inform, inspire and provide guidance to researchers in the field. Foundational Research Topic ranging from still unsolved evolutionary mechanisms at the genomic level and the challenges posed by human genomic variation are powerful drivers of current and future research in Computational Genomics. The challenge that genomics poses to computational theory is to be highlighted, ranging from the role of Artificial Intelligence and Deep Learning (DL) in this context to the likely impact of emerging Single Cell RNA Sequencing (scRNA-Seq) methodologies in transcriptomics. Steady progress in tools for automated managing of large heterogeneous genomic and biological data is likely to bring good dividends in the near future. Specific applications of computational genomics support cancer studies for tasks such as drug repositioning and finding the role of immune system genes in cancer. Also, computational genomics is a key helper to plant science in the effort to cope with the effects of climate changes in the long run, with global food security as a goal.