0


利用公开获得的生物专家知识从蛋白质-蛋白质相互作用信息

Employing Publicly Available Biological Expert Knowledge from Protein-Protein Interaction Information
课程网址: http://videolectures.net/prib2010_pattin_epab/  
主讲教师: Kristine A. Pattin
开课单位: 达特茅斯医学院
开课时间: 2010-10-14
课程语种: 英语
中文简介:
全基因组关联研究(GWAS)现在允许研究人员探索常见的复杂人类疾病的深度,但很少有人确定了赋予疾病易感性的单一序列变异。正如假设的那样,这是由于多个相互作用因素影响临床终点。鉴于单核苷酸多态性(SNP)组合的数量随着被分析的SNP的数量呈指数增长,因此设计用于在较小数据集中检测这些相互作用的计算方法不适用。提供统计专家知识已经表现出他们的表现有所改善,我们相信生物学专业知识也是有能力的。由于基因之间功能关系的最强烈证明之一是蛋白质 - 蛋白质相互作用,我们提出了一种在遗传分析中利用这些信息的方法。该研究为利用源自公共生物学来源的专家知识提供了一个步骤,以帮助计算智能算法搜索上位性。
课程简介: Genome wide association studies (GWAS) are now allowing researchers to probe the depths of common complex human diseases, yet few have identified single sequence variants that confer disease susceptibility. As hypothesized, this is due the fact that multiple interacting factors influence clinical endpoint. Given the number of single nucleotide polymorphisms (SNPs) combinations grows exponentially with the number of SNPs being analyzed, computational methods designed to detect these interactions in smaller datasets are thus not applicable. Providing statistical expert knowledge has exhibited an improvement in their performance, and we believe biological expert knowledge to be as capable. Since one of the strongest demonstrations of the functional relationship between genes is protein-protein interactions, we present a method that exploits this information in genetic analyses. This study provides a step towards utilizing expert knowledge derived from public biological sources to assist computational intelligence algorithms in the search for epistasis.
关 键 词: 生物信息学; 计算智能算法; 遗传分析
课程来源: 视频讲座网
最后编审: 2020-06-27:zyk
阅读次数: 47