gene references into function (generif)  (Biotechnology Information)

Journal: Nucleic Acids Research

Article Title: Geneshot: search engine for ranking genes from arbitrary text queries

doi: 10.1093/nar/gkz393

Figure Lengend Snippet: Geneshot user interface for the PubMed querying tab. ( A ) Search engine input section. ( B ) Scatter plot of all publications that mention both the gene and the search terms against the normalized values (left); gene with and without search terms mentions over time (right). ( C ) Tables providing ranked lists of relevant genes based on GeneRIF (left), and predictions based on AutoRIF co-occurrence (right).

Article Snippet: With some similarity to these previously published tools, Geneshot converts PubMed identifiers (PMIDs) returned for arbitrary search terms to ranked lists of genes using gene-publication associations such as those encoded within Gene References into Function (GeneRIF) , a manually curated resource maintained by the National Center for Biotechnology Information (NCBI).

Techniques:

Journal: Nucleic Acids Research

Article Title: Geneshot: search engine for ranking genes from arbitrary text queries

doi: 10.1093/nar/gkz393

Figure Lengend Snippet: Median area under the receiver operating characteristic curve (AUC) distributions for predicting genes associated with terms from 16 Enrichr gene set libraries. The libraries are labeled as data-driven and manually curated. Predictions were made using four gene–gene similarity matrices created from Tagger, GeneRIF, AutoRIF and ARCHS4.

Article Snippet: With some similarity to these previously published tools, Geneshot converts PubMed identifiers (PMIDs) returned for arbitrary search terms to ranked lists of genes using gene-publication associations such as those encoded within Gene References into Function (GeneRIF) , a manually curated resource maintained by the National Center for Biotechnology Information (NCBI).

Techniques: Labeling

Journal: Nucleic Acids Research

Article Title: DiseaseConnect: a comprehensive web server for mechanism-based disease–disease connections

doi: 10.1093/nar/gku412

Figure Lengend Snippet: Constructing the mechanism-based disease–disease network based on the GWAS/OMIM/DEG records. (A) We combine the disease–gene connections derived from GWAS, OMIM and DEG records to build a comprehensive disease–gene network (D 1 , D 2 , D 3 and D 4 indicate diseases and G 1 , G 2 , G 3 and G 4 indicate genes). For each disease pair, we calculate the hypergeometric P -value to assess the significance of the number of genes involved in both diseases. We also add drug–treatment relations to complement further the database. (B) In the disease–disease network, when users click the edge between disease D 1 and D 2 , the web server generates the detailed network of disease D 1 and D 2 , including DEG/GWAS/OMIM/GeneRIF/GeneWays disease–gene relations and drug treatment/target relations.

Article Snippet: The Disease and Gene Annotation (DGA) database uses the Gene Reference Into Function (GeneRIF) from the National Center for Biotechnology Information (NCBI), Disease Ontology (DO) and molecular interaction networks to construct disease–gene, gene–gene and disease–disease relations ( ).

Techniques: Derivative Assay

Journal: Nucleic Acids Research

Article Title: DiseaseConnect: a comprehensive web server for mechanism-based disease–disease connections

doi: 10.1093/nar/gku412

Figure Lengend Snippet: Diseases pairs sharing more involved genes are more likely to have disease comorbidity. The statistical significance ( P- value) of the connection between two diseases is assessed by a hypergeometric test on shared genes derived from each individual data source of GWAS, OMIM, DEG, GeneRIF and GeneWays. We used various P -value thresholds (x axis) to select significant disease–disease connections for each data source, and then calculated the fraction (y axis) of those disease–disease connections that overlap with the disease comorbidity connections.

Article Snippet: The Disease and Gene Annotation (DGA) database uses the Gene Reference Into Function (GeneRIF) from the National Center for Biotechnology Information (NCBI), Disease Ontology (DO) and molecular interaction networks to construct disease–gene, gene–gene and disease–disease relations ( ).

Techniques: Derivative Assay

Journal: Nucleic Acids Research

Article Title: DiseaseConnect: a comprehensive web server for mechanism-based disease–disease connections

doi: 10.1093/nar/gku412

Figure Lengend Snippet: Disease pairs sharing more genes are more likely to have the same drug treatment. The statistical significance ( P -value) of the connection between two diseases is assessed by a hypergeometric test on shared genes derived from each individual data source of GWAS, OMIM, DEG, GeneRIF and GeneWays. We used various P -value thresholds (x axis) to select significant disease–disease connections for each data source, and then calculated the fraction (y axis) of the disease–disease connections in which both diseases can be treated by the same drug(s).

Article Snippet: The Disease and Gene Annotation (DGA) database uses the Gene Reference Into Function (GeneRIF) from the National Center for Biotechnology Information (NCBI), Disease Ontology (DO) and molecular interaction networks to construct disease–gene, gene–gene and disease–disease relations ( ).

Techniques: Derivative Assay

Journal: Nucleic Acids Research

Article Title: DiseaseConnect: a comprehensive web server for mechanism-based disease–disease connections

doi: 10.1093/nar/gku412

Figure Lengend Snippet: Disease connections with drug treatment implications. (A) PSMB5 is a DEG for both hemorrhagic disorders and multiple myeloma, and PSMB5 also has GeneRIF association with multiple myeloma. (B) Arthritis and Crohn disease are associated with TNF based on the GWAS and GeneRIF records. Thalidomide is an immunomodulatory drug that targets TNF and can treat both arthritis and Crohn diseases. Adalimumab also targets TNF and can treat arthritis, suggesting its potential treatment of Crohn disease.

Article Snippet: The Disease and Gene Annotation (DGA) database uses the Gene Reference Into Function (GeneRIF) from the National Center for Biotechnology Information (NCBI), Disease Ontology (DO) and molecular interaction networks to construct disease–gene, gene–gene and disease–disease relations ( ).

Techniques: