从基因组序列预测医学靶标:将不同的序列分析算法与专家知识和人工智能方法的输入相结合

Thomas Dandekar , Fuli Du , R.Heiner Schirmer , Steffen Schmidt
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引用次数: 9

摘要

利用现有序列数据的迅速增加,通过以下结合改进了医学相关蛋白质靶点的定义:(i)差异基因组分析(靶点列表);(ii)单个蛋白质的分析(靶分析)。快速序列比较、数据挖掘和遗传算法进一步促进了这些过程。以结核分枝杆菌蛋白为应用实例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Medical target prediction from genome sequence: combining different sequence analysis algorithms with expert knowledge and input from artificial intelligence approaches

By exploiting the rapid increase in available sequence data, the definition of medically relevant protein targets has been improved by a combination of: (i) differential genome analysis (target list); and (ii) analysis of individual proteins (target analysis). Fast sequence comparisons, data mining, and genetic algorithms further promote these procedures. Mycobacterium tuberculosis proteins were chosen as applied examples.

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