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Database Commons - Harmonizome

Harmonizome

Citations: 5

z-index 2.28

Short name Harmonizome
Full name
Description a collection of processed datasets gathered to serve and mine knowledge about genes and proteins from over 70 major online resources.
URL http://amp.pharm.mssm.edu/Harmonizome
Year founded 2016
Last update & version 2017-07-02    
Availability Free to all users
University/Institution hosted Icahn School of Medicine at Mount Sinai
Address Department of Pharmacology and Systems Therapeutics, Department of Genetics and Genomic Sciences, BD2K-LINCS Data Coordination and Integration Center (DCIC), Mount Sinai's Knowledge Management Center for Illuminating the Druggable Genome (KMC-IDG)
City New York
Province/State New York
Country/Region United States
Contact name Avi Ma’ayan
Contact email avi.maayan@mssm.edu
Data type(s)
Major organism(s)
Keyword(s)
  • functional annotation
  • network
Publication(s)
  • The harmonizome: a collection of processed datasets gathered to serve and mine knowledge about genes and proteins. [PMID: 27374120]

    Andrew D Rouillard, Gregory W Gundersen, Nicolas F Fernandez, Zichen Wang, Caroline D Monteiro, Michael G McDermott, Avi Ma'ayan
    Database : the journal of biological databases and curation 2016:2016
    5 Citations (Google Scholar as of 2017-03-28)

    Abstract: Genomics, epigenomics, transcriptomics, proteomics and metabolomics efforts rapidly generate a plethora of data on the activity and levels of biomolecules within mammalian cells. At the same time, curation projects that organize knowledge from the biomedical literature into online databases are expanding. Hence, there is a wealth of information about genes, proteins and their associations, with an urgent need for data integration to achieve better knowledge extraction and data reuse. For this purpose, we developed the Harmonizome: a collection of processed datasets gathered to serve and mine knowledge about genes and proteins from over 70 major online resources. We extracted, abstracted and organized data into ∼72 million functional associations between genes/proteins and their attributes. Such attributes could be physical relationships with other biomolecules, expression in cell lines and tissues, genetic associations with knockout mouse or human phenotypes, or changes in expression after drug treatment. We stored these associations in a relational database along with rich metadata for the genes/proteins, their attributes and the original resources. The freely available Harmonizome web portal provides a graphical user interface, a web service and a mobile app for querying, browsing and downloading all of the collected data. To demonstrate the utility of the Harmonizome, we computed and visualized gene-gene and attribute-attribute similarity networks, and through unsupervised clustering, identified many unexpected relationships by combining pairs of datasets such as the association between kinase perturbations and disease signatures. We also applied supervised machine learning methods to predict novel substrates for kinases, endogenous ligands for G-protein coupled receptors, mouse phenotypes for knockout genes, and classified unannotated transmembrane proteins for likelihood of being ion channels. The Harmonizome is a comprehensive resource of knowledge about genes and proteins, and as such, it enables researchers to discover novel relationships between biological entities, as well as form novel data-driven hypotheses for experimental validation.Database URL: http://amp.pharm.mssm.edu/Harmonizome. © The Author(s) 2016. Published by Oxford University Press.

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Accessibility

Rate of accessibility:
HTTP status codeDate requested
200 OK2018-11-16
200 OK2018-11-13
200 OK2018-11-09
200 OK2018-11-06
200 OK2018-11-02
200 OK2018-10-30
200 OK2018-10-26
200 OK2018-10-23
200 OK2018-10-19
200 OK2018-10-16
200 OK2018-10-12
200 OK2018-10-09
200 OK2018-10-05
200 OK2018-10-02
200 OK2018-09-28
200 OK2018-09-25
200 OK2018-09-21
200 OK2018-09-18
200 OK2018-09-14
200 OK2018-09-11
200 OK2018-09-07
200 OK2018-09-04
200 OK2018-08-31
200 OK2018-08-28
200 OK2018-08-24
200 OK2018-08-21
200 OK2018-08-17
200 OK2018-08-14
200 OK2018-08-10
200 OK2018-08-07
200 OK2018-08-03
200 OK2018-07-31
200 OK2018-07-27
200 OK2018-07-24
200 OK2018-07-20
200 OK2018-07-17
200 OK2018-07-13
200 OK2018-07-10
200 OK2018-07-06
200 OK2018-07-03
200 OK2018-06-29
200 OK2018-06-26
200 OK2018-06-22
200 OK2018-06-19
200 OK2018-06-15
200 OK2018-06-12
200 OK2018-06-08
200 OK2018-06-05
200 OK2018-06-01
200 OK2018-05-29
200 OK2018-05-25
200 OK2018-05-22
200 OK2018-05-18
200 OK2018-05-15
200 OK2018-05-11
200 OK2018-05-08
200 OK2018-05-04
200 OK2018-05-01
200 OK2018-04-27
200 OK2018-04-24
200 OK2018-04-20
200 OK2018-04-17
200 OK2018-04-13
200 OK2018-04-10
200 OK2018-04-06
200 OK2018-04-03
200 OK2018-02-27
200 OK2018-02-23
200 OK2018-02-20
200 OK2018-02-16
200 OK2018-02-13
-1 Failed2018-02-09
200 OK2018-02-06
200 OK2018-02-02
200 OK2018-01-30
-1 Failed2018-01-26
200 OK2018-01-23
200 OK2018-01-19
-1 Failed2018-01-16
200 OK2018-01-12
-1 Failed2018-01-09
200 OK2018-01-05
-1 Failed2018-01-02
200 OK2017-12-29
200 OK2017-12-26
200 OK2017-12-22
200 OK2017-12-19
-1 Failed2017-12-15
200 OK2017-12-12
200 OK2017-12-08
200 OK2017-12-05
200 OK2017-12-01
200 OK2017-11-28
-1 Failed2017-11-24
200 OK2017-11-21
-1 Failed2017-11-17
200 OK2017-11-14
200 OK2017-11-10
200 OK2017-11-07
200 OK2017-11-03
200 OK2017-10-31
200 OK2017-10-27
200 OK2017-10-24
200 OK2017-10-20
-1 Failed2017-10-17
200 OK2017-10-13
-1 Failed2017-10-10
200 OK2017-10-06
200 OK2017-10-03
200 OK2017-09-29
200 OK2017-09-26
200 OK2017-09-22
200 OK2017-09-19
200 OK2017-09-15
200 OK2017-09-12
-1 Failed2017-09-08
200 OK2017-09-05
200 OK2017-09-01
200 OK2017-08-29
200 OK2017-08-25
200 OK2017-08-22
200 OK2017-08-18
200 OK2017-08-15
200 OK2017-08-11
200 OK2017-08-08
200 OK2017-08-04
200 OK2017-08-01
200 OK2017-07-28
200 OK2017-07-25
503 Failed2017-07-21
200 OK2017-07-18
200 OK2017-07-14
-1 Failed2017-07-04
200 OK2017-06-30
200 OK2017-06-27
200 OK2017-06-23
200 OK2017-06-20
200 OK2017-06-16
200 OK2017-06-13
200 OK2017-06-09
200 OK2017-06-06
200 OK2017-06-02
-1 Failed2017-05-30
200 OK2017-05-26
200 OK2017-05-23
200 OK2017-05-19
200 OK2017-05-16
200 OK2017-05-12
200 OK2017-05-09
200 OK2017-05-05
200 OK2017-05-02
200 OK2017-04-28
200 OK2017-04-25
200 OK2017-04-21
200 OK2017-04-18
200 OK2017-04-14
200 OK2017-04-11
200 OK2017-04-07
200 OK2017-04-04
200 OK2017-03-31
200 OK2017-03-28

Tags

Metadata
Homo sapiens Mus musculus
functional annotation network

Record metadata

  • Created on: 2017-03-28
  • Curated by:
    • Lina Ma [2017-06-01]
    • Shixiang Sun [2017-03-28]
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