HINT: High-quality protein interactomes and their applications in understanding human disease

By Jishnu Das, Haiyuan Yu. 2012

451 citations recorded by the source corpus.

BackgroundA global map of protein-protein interactions in cellular systems provides key insights into the workings of an organism. A repository of well-validated high-quality protein-protein interactions can be used in both large- and small-scale studies to generate and validate a wide range of functional hypotheses.ResultsWe develop HINT (http://hint.yulab.org) - a database of high-quality protein-protein interactomes for human, Saccharomyces cerevisiae, Schizosaccharomyces pombe, and Oryza sativa. These were collected from several databases and filtered both systematically and manually to remove low-quality/erroneous interactions. The resulting datasets are classified by type (binary physical interactions vs. co-complex associations) and data source (high-throughput systematic setups vs. literature-curated small-scale experiments). We find strong sociological sampling biases in literature-curated datasets of small-scale interactions. An interactome without such sampling biases was used to understand network properties of human disease-genes - hubs are unlikely to cause disease, but if they do, they usually cause multiple disorders.ConclusionsHINT is of significant interest to researchers in all fields of biology as it addresses the ubiquitous need of having a repository of high-quality protein-protein interactions. These datasets can be utilized to generate specific hypotheses about specific proteins and/or pathways, as well as analyzing global properties of cellular networks. HINT will be regularly updated and all versions will be tracked.

Subfields: Computational Theory and Mathematics, Molecular Biology

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Citations in the corpus

EgoNet: identification of human disease ego-network modules (2014, methodology): “The PPI network was obtained from HINT database [32], which collected data from several databases and filtered both systematically and manually to remove low-quality/erroneous interactions.”
Structure and dynamics of molecular networks: A novel paradigm of drug discovery: A comprehensive review (2012, background): “…interaction data http://discern.uits.iu.edu:8340/HAPPI Chen et al., 2009c HINT High quality human protein–protein interaction data http://hint.yulab.org Das & Yu, 2012 HPRD Human protein–protein interaction data http://www.hprd.org Goel et al., 2012 Hubba Identification of hubs (potentially…”
A proteome-wide fission yeast interactome reveals network evolution principles from yeasts to human (2016, result): “%) have not been previously reported in S. pombe (Figure 1A) (Das and Yu, 2012).”
The STRING database in 2017: quality-controlled protein–protein association networks, made broadly accessible (2016, background): “Second, a number of databases assemble larger, genome-wide protein networks that are nevertheless still restricted to experimentally observed interactions only; examples include BioGRID (23), HINT (24), iRefWeb (25) and APID (26).”
FunSeq2: a framework for prioritizing noncoding regulatory variants in cancer (2014, methodology): “Binary protein-protein interaction network is from InWeb [50] and HINT [51].”
A data-driven approach to predicting successes and failures of clinical trials (2016, methodology): “Network Features We constructed the aggregated biological network by taking the union across multiple databases of gene-gene interactions (Aksoy et al., 2013; Das and Yu, 2012; Khurana et al., 2013).”
Detecting subnetwork-level dynamic correlations (2017, methodology): “For the network, we used the protein-protein interaction (PPI) network from the HINT database (Das and Yu, 2012), which combines data from several databases and filters the interactions manually to remove erroneous interactions.”
Integrative Annotation of Variants from 1092 Humans: Application to Cancer Genomics (2013, methodology): “1 Source of interaction data and relationship with network connectivity Binary protein-protein interactions were obtained from InWeb (69) and HINT (70).”