Systematic comparison of the protein-protein interaction databases from a user's perspective

作者：Akhilesh Kumar Bajpai, Sravanthi Davuluri, Kriti Tiwary, Sithalechumi Narayanan, Sailaja Oguru, Kavyashree Basavaraju, Deena Dayalan, Kavitha Thirumurugan, Kshitish K. Acharya · 发表于：Journal of Biomedical Informatics · 年份：2020 · DOI：10.1016/j.jbi.2020.103380 · 被引用次数：110 · 研究领域：Bioinformatics and Genomic Networks、Microbial Metabolic Engineering and Bioproduction、Gene expression and cancer classification

In absence of periodic systematic comparisons, biologists/bioinformaticians may be forced to make a subjective selection among the many protein-protein interaction (PPI) databases and tools. We conducted a comprehensive compilation and comparison of such resources. We compiled 375 PPI resources, short-listed 125 important ones (both lists are available at startbioinfo.com), and compared the features and coverage of 16 carefully-selected databases related to human PPIs. We quantitatively compared the coverage of 'experimentally verified' as well as 'total' (experimentally verified and predicted) PPIs for these 16 databases. Coverage was compared in two ways: (a) PPIs obtained in response to gene queries using the web interfaces were compared. As a query set, 108 genes expressed differently across tissues (specific to kidney, testis, and uterus, and ubiquitous - i.e., expressed in 43 human normal tissues) or associated with certain diseases (breast cancer, lung cancer, Alzheimer's, cystic fibrosis, diabetes, and cardiomyopathy) were chosen. The coverage was also compared for the well-studied genes versus the less-studied ones. The coverage of the databases for high-quality interactions was separately assessed using a set of literature curated experimentally-proven PPIs (gold standard PPI-set); (b) the back-end-data from 15 PPI databases was downloaded and compared. Combined results from STRING and UniHI covered around 84% of 'experimentally verified' PPIs. Approximately 94% of ...