Genes associated with Homo sapiens that interact with the MeSH term 'propionaldehyde' (C005556). Incorporates data from 1 publications curated by the Comparative Toxicogenomics Database (CTD). ODE Gene scores represent number of supporting publications per gene.
Genes associated with Equus caballus that interact with the MeSH term 'Castor Oil' (D002368). Incorporates data from 887 publications curated by the Comparative Toxicogenomics Database (CTD). ODE Gene scores represent number of supporting publications per gene.
Genes associated with Homo sapiens that interact with the MeSH term 'Grape Seed Proanthocyanidins' (C511402). Incorporates data from 3 publications curated by the Comparative Toxicogenomics Database (CTD). ODE Gene scores represent number of supporting publications per gene.
Genes associated with Homo sapiens that interact with the MeSH term 'Catechin' (D002392). Incorporates data from 12 publications curated by the Comparative Toxicogenomics Database (CTD). ODE Gene scores represent number of supporting publications per gene.
"Combining with an odorant and transmitting the signal from one side of the membrane to the other to initiate a change in cell activity in response to detection of smell." [GOC:bf, GOC:dph, GOC:sart, PMID:19135896, PMID:21041441]
The latest version of the dGene database made available here at the request of the dGene creators (04-16-2013). File name dGene_04-16-2013_2257 (http://dgidb.genome.wustl.edu/)
Pathway Commons (PC) Geneset. This geneset contains genes that participate in the "Signaling Pathways" pathway. This set was automatically constructed using the PC API.
The original source of this geneset is Reactome.
gene2pc v. 0.1.0
Last updated 2015.08.31
Gene Ontology (GO) gene set. This set contains genes that have been annotated to the GO term "cell part", which is defined as "Any constituent part of a cell, the basic structural and functional unit of all organisms." This gene set was automatically constructed using annotation and ontology data provided by GO and only includes annotations with experimental and curatorial evidence codes (EXP, IDA, IPI, IMP, IGI, IEP, TAS, IC). The transitive closure of this term is taken into account using is_a and part_of relationships. For more information: The Gene Ontology Consortium (GOC), http://geneontology.org This gene set was generated using the GeneWeaver GO loader v. 0.2.8.
Authors:
M Ashburner, CA Ball, JA Blake, D Botstein, H Butler, JM Cherry, AP Davis, K Dolinski, SS Dwight, JT Eppig, MA Harris, DP Hill, L Issel-Tarver, A Kasarskis, S Lewis, JC Matese, JE Richardson, M Ringwald, GM Rubin, G Sherlock
Genes associated (p < .05) with the genetic predisposition to cocaine dependence in European Americans (n > 3000). All individuals reported using cocaine and analyses utilized a classic case-control design and a MAGMA gene-based test: see Huggett & Stallings, 2019 Addiction Biology for more details.
Gene Ontology (GO) gene set. This set contains genes that have been annotated to the GO term "cellular anatomical entity", which is defined as "A part of a cellular organism that is either an immaterial entity or a material entity with granularity above the level of a protein complex but below that of an anatomical system. Or, a substance produced by a cellular organism with granularity above the level of a protein complex." This gene set was automatically constructed using annotation and ontology data provided by GO and only includes annotations with experimental and curatorial evidence codes (EXP, IDA, IPI, IMP, IGI, IEP, TAS, IC). The transitive closure of this term is taken into account using is_a and part_of relationships. For more information: The Gene Ontology Consortium (GOC), http://geneontology.org This gene set was generated using the GeneWeaver GO loader v. 0.2.12.
Authors:
M Ashburner, CA Ball, JA Blake, D Botstein, H Butler, JM Cherry, AP Davis, K Dolinski, SS Dwight, JT Eppig, MA Harris, DP Hill, L Issel-Tarver, A Kasarskis, S Lewis, JC Matese, JE Richardson, M Ringwald, GM Rubin, G Sherlock
Gene Ontology (GO) gene set. This set contains genes that have been annotated to the GO term "membrane", which is defined as "A lipid bilayer along with all the proteins and protein complexes embedded in it an attached to it." This gene set was automatically constructed using annotation and ontology data provided by GO and only includes annotations with experimental and curatorial evidence codes (EXP, IDA, IPI, IMP, IGI, IEP, TAS, IC). The transitive closure of this term is taken into account using is_a and part_of relationships. For more information: The Gene Ontology Consortium (GOC), http://geneontology.org This gene set was generated using the GeneWeaver GO loader v. 0.2.12.
Authors:
M Ashburner, CA Ball, JA Blake, D Botstein, H Butler, JM Cherry, AP Davis, K Dolinski, SS Dwight, JT Eppig, MA Harris, DP Hill, L Issel-Tarver, A Kasarskis, S Lewis, JC Matese, JE Richardson, M Ringwald, GM Rubin, G Sherlock
Gene Ontology (GO) gene set. This set contains genes that have been annotated to the GO term "cellular_component", which is defined as "A location, relative to cellular compartments and structures, occupied by a macromolecular machine when it carries out a molecular function. There are two ways in which the gene ontology describes locations of gene products: (1) relative to cellular structures (e.g., cytoplasmic side of plasma membrane) or compartments (e.g., mitochondrion), and (2) the stable macromolecular complexes of which they are parts (e.g., the ribosome)." This gene set was automatically constructed using annotation and ontology data provided by GO and only includes annotations with experimental and curatorial evidence codes (EXP, IDA, IPI, IMP, IGI, IEP, TAS, IC). The transitive closure of this term is taken into account using is_a and part_of relationships. For more information: The Gene Ontology Consortium (GOC), http://geneontology.org This gene set was generated using the GeneWeaver GO loader v. 0.2.12.
Authors:
M Ashburner, CA Ball, JA Blake, D Botstein, H Butler, JM Cherry, AP Davis, K Dolinski, SS Dwight, JT Eppig, MA Harris, DP Hill, L Issel-Tarver, A Kasarskis, S Lewis, JC Matese, JE Richardson, M Ringwald, GM Rubin, G Sherlock
Gene Ontology (GO) gene set. This set contains genes that have been annotated to the GO term "plasma membrane", which is defined as "The membrane surrounding a cell that separates the cell from its external environment. It consists of a phospholipid bilayer and associated proteins." This gene set was automatically constructed using annotation and ontology data provided by GO and only includes annotations with experimental and curatorial evidence codes (EXP, IDA, IPI, IMP, IGI, IEP, TAS, IC). The transitive closure of this term is taken into account using is_a and part_of relationships. For more information: The Gene Ontology Consortium (GOC), http://geneontology.org This gene set was generated using the GeneWeaver GO loader v. 0.2.12.
Authors:
M Ashburner, CA Ball, JA Blake, D Botstein, H Butler, JM Cherry, AP Davis, K Dolinski, SS Dwight, JT Eppig, MA Harris, DP Hill, L Issel-Tarver, A Kasarskis, S Lewis, JC Matese, JE Richardson, M Ringwald, GM Rubin, G Sherlock
Gene Ontology (GO) gene set. This set contains genes that have been annotated to the GO term "cell periphery", which is defined as "The part of a cell encompassing the cell cortex, the plasma membrane, and any external encapsulating structures." This gene set was automatically constructed using annotation and ontology data provided by GO and only includes annotations with experimental and curatorial evidence codes (EXP, IDA, IPI, IMP, IGI, IEP, TAS, IC). The transitive closure of this term is taken into account using is_a and part_of relationships. For more information: The Gene Ontology Consortium (GOC), http://geneontology.org This gene set was generated using the GeneWeaver GO loader v. 0.2.12.
Authors:
M Ashburner, CA Ball, JA Blake, D Botstein, H Butler, JM Cherry, AP Davis, K Dolinski, SS Dwight, JT Eppig, MA Harris, DP Hill, L Issel-Tarver, A Kasarskis, S Lewis, JC Matese, JE Richardson, M Ringwald, GM Rubin, G Sherlock
Postmortem human brain tissue from the caudate nucleus region of a total of 48 individuals with Alcohol Use Disorder (AUD) and 51 control individuals were taken and RNA extracted from frozen tissue. Sequencing was carried out using the NovaSeq 6000 (Illumina) platform, and gene expression analysis was carried out with respect to AUD and control samples. Gene symbols from Entrez ids are used and Logbase2 FC as provided by the authors are annotated.
Authors:
Lea Zillich, Eric Poisel, Josef Frank, Jerome C Foo, Marion M Friske, Fabian Streit, Lea Sirignano, Stefanie Heilmann-Heimbach, André Heimbach, Per Hoffmann, Franziska Degenhardt, Anita C Hansson, Georgy Bakalkin, Markus M Nöthen, Marcella Rietschel, Rainer Spanagel, Stephanie H Witt
Postmortem human brain tissue from the putamen region of a total of 48 individuals with Alcohol Use Disorder (AUD) and 51 control individuals were taken and RNA extracted from frozen tissue. Sequencing was carried out using the NovaSeq 6000 (Illumina) platform, and gene expression analysis was carried out with respect to AUD and control samples. Gene symbols from Entrez ids are used and Logbase2 FC as provided by the authors are annotated.
Authors:
Lea Zillich, Eric Poisel, Josef Frank, Jerome C Foo, Marion M Friske, Fabian Streit, Lea Sirignano, Stefanie Heilmann-Heimbach, André Heimbach, Per Hoffmann, Franziska Degenhardt, Anita C Hansson, Georgy Bakalkin, Markus M Nöthen, Marcella Rietschel, Rainer Spanagel, Stephanie H Witt
Postmortem human brain tissue from the ventral striatum from postmortem human brain tissue with Alcohol Use Disorder (AUD) region of a total of 48 individuals with Alcohol Use Disorder (AUD) and 51 control individuals were taken and RNA extracted from frozen tissue. Sequencing was carried out using the NovaSeq 6000 (Illumina) platform, and gene expression analysis was carried out with respect to AUD and control samples. Gene symbols from Entrez ids are used and Logbase2 FC as provided by the authors are annotated.
Authors:
Lea Zillich, Eric Poisel, Josef Frank, Jerome C Foo, Marion M Friske, Fabian Streit, Lea Sirignano, Stefanie Heilmann-Heimbach, André Heimbach, Per Hoffmann, Franziska Degenhardt, Anita C Hansson, Georgy Bakalkin, Markus M Nöthen, Marcella Rietschel, Rainer Spanagel, Stephanie H Witt
Data from GEO GSE194368 and analyzed using GEO2R, only top gene shown. Authors identified transcriptional adaptations of GR signaling in the amygdala of humans with OUD. Thus, GRs, their coregulators and downstream systems may represent viable therapeutic targets to treat the “stress side” of OUD.
Authors:
Stephanie A Carmack, Janaina C M Vendruscolo, M Adrienne McGinn, Jorge Miranda-Barrientos, Vez Repunte-Canonigo, Gabriel D Bosse, Daniele Mercatelli, Federico M Giorgi, Yu Fu, Anthony J Hinrich, Francine M Jodelka, Karen Ling, Robert O Messing, Randall T Peterson, Frank Rigo, Scott Edwards, Pietro P Sanna, Marisela Morales, Michelle L Hastings, George F Koob, Leandro F Vendruscolo
Data from GEO GSE194368 and analyzed using GEO2R, only top gene shown. Authors identified transcriptional adaptations of GR signaling in the amygdala of humans with OUD. Thus, GRs, their coregulators and downstream systems may represent viable therapeutic targets to treat the “stress side” of OUD.
Authors:
Stephanie A Carmack, Janaina C M Vendruscolo, M Adrienne McGinn, Jorge Miranda-Barrientos, Vez Repunte-Canonigo, Gabriel D Bosse, Daniele Mercatelli, Federico M Giorgi, Yu Fu, Anthony J Hinrich, Francine M Jodelka, Karen Ling, Robert O Messing, Randall T Peterson, Frank Rigo, Scott Edwards, Pietro P Sanna, Marisela Morales, Michelle L Hastings, George F Koob, Leandro F Vendruscolo
Transcriptional alterations in dorsolateral prefrontal cortex and nucleus accumbens implicate neuroinflammation and synaptic remodeling in opioid use disorder. Transcriptomic profile of 20 control subjects and 20 OUD subjects in brain region DLPFC and NAC. Analyzed using GEO2R (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE174409) separately for each brain region, comparing OUD and control samples.
Authors:
Xiangning Xue, Wei Zong, Jill R Glausier, Sam-Moon Kim, Micah A Shelton, BaDoi N Phan, Chaitanya Srinivasan, Andreas R Pfenning, George C Tseng, David A Lewis, Marianne L Seney, Ryan W Logan
The complete differential gene expression geneset was made available at NCBI GEO (NAc accession no.: GSE62699) and obtained using the GEO2R tool. Gene expression was assayed using Affymetrix GeneChip Human Genome U133A 2.0 (HG-U133A 2.0) on 22,214 probe sets spanning ~ 18,400 mRNA transcripts, and the Affymetrix GeneChip miRNA 3.0 microarray interrogating the expression of 1733 mature miRNAs as previously described [24]. None of the mRNA or miRNA probes were excluded based on quality control criteria outlined in previous studies [18]. Raw probe data were GCRMA background corrected, log2 transformed, and quantile normalized using Partek Genomics Suite v6.23 (PGS; Partek Inc., St. Louis, MO) to obtain relative gene expression values. A principal component analysis was used to identify potential outlier samples. Only one case sample was removed from the analyses, leaving 18 controls and 17 cases (n = 35) for both brain regions. It has become widely accepted to verify a subset of microarray-generated gene expression changes via an independent platform such as qPCR. Considering limited tissue availability and our extensive use of the Affymetrix platform in the past, we did not include microarray validation in this study which is similar to what other groups have done in the past [25]. We have previously ‘validated’ the same array and platform in independent qPCR experiments with a concordance between microarray and qPCR platforms exceeding 80% in the past [18].
Authors:
Eric Vornholt, John Drake, Mohammed Mamdani, Gowon McMichael, Zachary N. Taylor, Silviu-Alin Bacanu, Michael F. Miles, Vladimir I. Vladimirov
DE PCG from human NAc associated with AD vs control (p<0.10)_pvalue
Description:
At the single gene expression analysis (p ≤ 0.10), we identified a total of 6,469 probes differentially expressed between alcohol dependency (AD) cases and controls, representing 3,645 long non-coding (lncRNA) and 2,725 protein-coding genes (PCG) that compromise 5.9% and 4.4% of the total gene pool assayed, respectively. Among the differentially expressed genes, we also identified 99 pseudogenes. p<0.10
Authors:
John Drake, Gowon O McMichael, Eric Sean Vornholt, Kellen Cresswell, Vernell Williamson, Chris Chatzinakos, Mohammed Mamdani, Siddharth Hariharan, Kenneth S Kendler, Gursharan Kalsi, Brien P Riley, Mikhail Dozmorov, Michael F Miles, Silviu-Alin Bacanu, Vladimir I Vladimirov
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