Abstract

The User Interface Portal (UIP) of the Mount Sinai's KMC-IDG will develop a state-of-the-art web-site that would host the presentation and access to the data collected by the DOC. The web-site will have a dedicated page of each under-studied druggable target with different plug-in tools to explore the various aspects of each target including: protein structure, protein-protein interactions, regulation by transcription factors, mouse phenotypes, expression profiles in different tissues and conditions, mouse knockout phenotypes, gene ontology information, post-translational modification and many more. In addition, the portal will enable interactive visualization of various applications that will place the under-studied targets within networks made of cohorts of patients, cell lines, diseases/side-effects/phenotypes, drugs and other genes and proteins. The UIP will have a powerful search engine that would index all entities in the DOC and will learn from user experience. The UIP will enable users to build their own data analysis pipelines based on the user specific needs. In addition, the UIP will be designed in a plug-in architecture to enable the community to contribute data analysis and visualization tools.

Public Health Relevance

The large amount of data that is accumulating from genome-wide emerging biotechnologies is illuminating new biology about many genes that until recently not much data was available. The most glean knowledge from such large datasets novel web-based visalization tools are required.

  Funding Agency

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
5U54CA189201-02
Application #
8934414
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Zenklusen, Jean C
Project Start
Project End
2017-07-31
Budget Start
2015-08-01
Budget End
2016-07-31
Support Year
2
Fiscal Year
2015
Total Cost
Indirect Cost

  Institution

Name
Icahn School of Medicine at Mount Sinai
Department
Type
DUNS #
078861598
City
New York
State
NY
Country
United States
Zip Code
10029

  Publications

Hodos, Rachel; Zhang, Ping; Lee, Hao-Chih et al. (2018) Cell-specific prediction and application of drug-induced gene expression profiles. Pac Symp Biocomput 23:32-43
Shameer, Khader; Glicksberg, Benjamin S; Hodos, Rachel et al. (2018) Systematic analyses of drugs and disease indications in RepurposeDB reveal pharmacological, biological and epidemiological factors influencing drug repositioning. Brief Bioinform 19:656-678
Torre, Denis; Lachmann, Alexander; Ma'ayan, Avi (2018) BioJupies: Automated Generation of Interactive Notebooks for RNA-Seq Data Analysis in the Cloud. Cell Syst 7:556-561.e3
Torre, Denis; Krawczuk, Patrycja; Jagodnik, Kathleen M et al. (2018) Datasets2Tools, repository and search engine for bioinformatics datasets, tools and canned analyses. Sci Data 5:180023
Oprea, Tudor I; Bologa, Cristian G; Brunak, Søren et al. (2018) Unexplored therapeutic opportunities in the human genome. Nat Rev Drug Discov 17:317-332
Guo, Yiqing; Pace, Jesse; Li, Zhengzhe et al. (2018) Podocyte-Specific Induction of Krüppel-Like Factor 15 Restores Differentiation Markers and Attenuates Kidney Injury in Proteinuric Kidney Disease. J Am Soc Nephrol 29:2529-2545
Wang, Zichen; Lachmann, Alexander; Keenan, Alexandra B et al. (2018) L1000FWD: fireworks visualization of drug-induced transcriptomic signatures. Bioinformatics 34:2150-2152
Koplev, Simon; Lin, Katie; Dohlman, Anders B et al. (2018) Integration of pan-cancer transcriptomics with RPPA proteomics reveals mechanisms of epithelial-mesenchymal transition. PLoS Comput Biol 14:e1005911
Lachmann, Alexander; Torre, Denis; Keenan, Alexandra B et al. (2018) Massive mining of publicly available RNA-seq data from human and mouse. Nat Commun 9:1366
Smith, Milo R; Yevoo, Priscilla; Sadahiro, Masato et al. (2018) Integrative bioinformatics identifies postnatal lead (Pb) exposure disrupts developmental cortical plasticity. Sci Rep 8:16388

Showing the most recent 10 out of 66 publications