The BioGRID interaction database is an open-access resource that curates and archives protein, genetic, and chemical interactions across major model organisms and humans. As of September 2016, BioGRID contains 1,072,173 genetic and protein interactions, representing a 30% increase from the previous update. It also includes 38,559 post-translational modification (PTM) records from 48,114 publications. BioGRID curates biomedical literature for major model organisms, with a focus on central biological processes and human diseases. It now includes 27,501 chemical-protein interactions for human drug targets, drawn from the DrugBank database. A new dynamic interaction network viewer allows users to navigate and filter genetic and protein interaction data, as well as bioactive compounds and their targets. BioGRID data are freely downloadable in various formats and distributed through partner databases. BioGRID's primary focus is the manual curation of experimentally validated genetic and protein interactions from peer-reviewed publications. Text-mining approaches are used to accelerate and prioritize curation. All interactions are annotated with structured evidence codes. BioGRID also captures PTM data, such as phosphorylation and ubiquitination, from both high-throughput and low-throughput studies. It now includes data on drug, metabolite, and other bioactive small molecule interactions. BioGRID's network viewer allows visualization of all search results in an interactive format, and additional views allow interrogation of PTM sites and chemical interaction data. BioGRID's data content has increased by 30% since the 2015 NAR Database report. As of September 2016, it contains 1,072,173 protein and genetic interactions, including 836,212 non-redundant interactions. These correspond to 621,639 protein interactions and 450,534 genetic interactions. BioGRID data are derived from 47,223 manually annotated publications. BioGRID also contains 38,559 PTM records from 4,317 publications, mainly from high-throughput mass spectrometry studies. BioGRID has expanded its data to include PTM data for 66 model organisms, including humans. BioGRID has established themed curation projects on central biological processes and diseases, such as autophagy and glioblastoma. These projects involve collaboration with research teams and aim to curate interactions for key biological processes and diseases. BioGRID also works with the GO consortium to guide curation efforts and help elaborate branches of the GO. BioGRID supports pre-publication deposition of experimental results to facilitate rapid dissemination of high-throughput datasets. BioGRID has implemented text-mining tools to support biocuration tasks, including the development of publication queues for curation. BioGRID has also supported the biomedical text-mining communityThe BioGRID interaction database is an open-access resource that curates and archives protein, genetic, and chemical interactions across major model organisms and humans. As of September 2016, BioGRID contains 1,072,173 genetic and protein interactions, representing a 30% increase from the previous update. It also includes 38,559 post-translational modification (PTM) records from 48,114 publications. BioGRID curates biomedical literature for major model organisms, with a focus on central biological processes and human diseases. It now includes 27,501 chemical-protein interactions for human drug targets, drawn from the DrugBank database. A new dynamic interaction network viewer allows users to navigate and filter genetic and protein interaction data, as well as bioactive compounds and their targets. BioGRID data are freely downloadable in various formats and distributed through partner databases. BioGRID's primary focus is the manual curation of experimentally validated genetic and protein interactions from peer-reviewed publications. Text-mining approaches are used to accelerate and prioritize curation. All interactions are annotated with structured evidence codes. BioGRID also captures PTM data, such as phosphorylation and ubiquitination, from both high-throughput and low-throughput studies. It now includes data on drug, metabolite, and other bioactive small molecule interactions. BioGRID's network viewer allows visualization of all search results in an interactive format, and additional views allow interrogation of PTM sites and chemical interaction data. BioGRID's data content has increased by 30% since the 2015 NAR Database report. As of September 2016, it contains 1,072,173 protein and genetic interactions, including 836,212 non-redundant interactions. These correspond to 621,639 protein interactions and 450,534 genetic interactions. BioGRID data are derived from 47,223 manually annotated publications. BioGRID also contains 38,559 PTM records from 4,317 publications, mainly from high-throughput mass spectrometry studies. BioGRID has expanded its data to include PTM data for 66 model organisms, including humans. BioGRID has established themed curation projects on central biological processes and diseases, such as autophagy and glioblastoma. These projects involve collaboration with research teams and aim to curate interactions for key biological processes and diseases. BioGRID also works with the GO consortium to guide curation efforts and help elaborate branches of the GO. BioGRID supports pre-publication deposition of experimental results to facilitate rapid dissemination of high-throughput datasets. BioGRID has implemented text-mining tools to support biocuration tasks, including the development of publication queues for curation. BioGRID has also supported the biomedical text-mining community