图 书 馆
利用蛋白质相互作用信息中公开的生物学专家知识Employing Publicly Available Biological Expert Knowledge from Protein-Protein Interaction Information |
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| 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）现在使研究人员能够探究常见的复杂人类疾病的深度，但很少有人发现赋予疾病易感性的单序列变异体。如所假设的，这是由于多个相互作用因素影响临床终点这一事实。鉴于单核苷酸多态性（SNP）组合的数量随所分析的SNP数量呈指数增长，因此设计用于检测较小数据集中这些相互作用的计算方法不适用。提供统计专家知识已显示出其性能的提高，我们相信生物学专家知识同样具有能力。由于基因之间功能关系的最强证明之一是蛋白质蛋白质相互作用，因此我们提出了一种在遗传分析中利用此信息的方法。这项研究为利用公共生物学来源的专家知识来协助计算智能算法寻找上位性迈出了一步。 |
| 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: | 蛋白质; 人类疾病; 遗传分析 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2021-03-07：zyk |
| 最后编审: | 2021-03-10：zyk |
| 阅读次数: | 36 |