Comprehensive Prediction of Protein Folding Class Based on Global Description of Amino Acid Sequence

基于氨基酸序列全局描述的蛋白质折叠类别综合预测

• 批准号: 9723352
• 负责人: Sung-Hou Kim
• 金额: $ 35.2万
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-10-01 至 2001-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9723352&HistoricalAwards=false
• 关键词: Comprehensive; Prediction; Protein; Folding; Class

Kim, Sung-Hou 9723352 The goal of this research is to develop a computational method for predicting the folding class for any protein sequence without a clearly identified function or significant homology to known sequences. This approach would provide an alternative and complementary scheme to sequence homology based methods for a solution to the inverse protein folding problem. This computational method will be used on a large scale as automatic software of high accuracy for the prediction of the folding class for new genomic sequences, generated by human and microbial genome projects.

Kim, Sung-Hou 9723352 这项研究的目标是开发一种计算方法，用于预测任何没有明确识别功能或与已知序列具有显着同源性的蛋白质序列的折叠类别。 这种方法将为基于序列同源性的方法提供替代和补充方案，以解决反向蛋白质折叠问题。 这种计算方法将作为高精度自动软件大规模使用，用于预测人类和微生物基因组项目生成的新基因组序列的折叠类别。