国际标准期刊号: 2329-9053

分子药剂学与有机过程研究杂志

开放获取

我们集团组织了 3000 多个全球系列会议 每年在美国、欧洲和美国举办的活动亚洲得到 1000 多个科学协会的支持 并出版了 700+ 开放获取期刊包含超过50000名知名人士、知名科学家担任编委会成员。

开放获取期刊获得更多读者和引用
700 种期刊 15,000,000 名读者 每份期刊 获得 25,000 多名读者

索引于
  • CAS 来源索引 (CASSI)
  • 哥白尼索引
  • 谷歌学术
  • 夏尔巴·罗密欧
  • 打开 J 门
  • 学术钥匙
  • 参考搜索
  • 哈姆达大学
  • 亚利桑那州EBSCO
  • OCLC-世界猫
  • 普布隆斯
  • 欧洲酒吧
  • ICMJE
分享此页面

抽象的

Using a Domain to Predict Protein-Protein Interactions

Karasev Fortier

The interactions between proteins are essential for many biological processes. It is vital to learn the specifics of these interactions in order to better understand the pathophysiology and therapies for different diseases. However, there are still a lot of false-positive and false-negative issues with the existing experimental methodology. A more significant prediction technique that can get over the limitations of the experimental method is computational prediction of protein-protein interaction. In this study, we suggested a brand-new computational domain-based approach for PPI prediction, and we developed an SVM model for the prediction based on the physicochemical characteristic of the domain. The results of SVM and the domain-domain score were utilized to build the protein-protein interaction prediction model.

免责声明: 此摘要通过人工智能工具翻译,尚未经过审核或验证。