ゲノムインフォーマティクスの数理

概要

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Recent explosion of genomic data has provided us a new field of mathematics in Genome Informatics. Genomic sequence analysis requires flexible and feasible symbolic processing of sequence matching, structure annotation, and function prediction. Once we have got structure or function of genes, we have the opportunity of applying it to new sequences or new genes using sequence similarity. However, since most sequences daily determined will be new, we sometimes can not predict their function only by sequence matching. Thus we must abstract and give bias to some parts in sequences. Here we illustrate how multiple sequence alignment, homology search, extraction of characteristic sequences, gene structure prediction, and gene function prediction provide clues to bring us insight into medical science and biology. We also show how gene expression in each tissue is measured by experiments, e. g. Microarray, what kind of mathematics is required for prediction of gene-network and gene-expression. Finally, we draw what is the promising topics of the new era of Human Genome Project, e. g. SNPs, for both mathematics and medical science.
日本応用数理学会の論文
2000-03-15