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.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
1U54CA189201-01
Application #
8934411
Study Section
Special Emphasis Panel (ZRG1-BST-M (50))
Program Officer
Zenklusen, Jean C
Project Start
2014-08-01
Project End
2016-07-31
Budget Start
2014-08-01
Budget End
2015-07-31
Support Year
1
Fiscal Year
2014
Total Cost
$72,103
Indirect Cost
Name
Icahn School of Medicine at Mount Sinai
Department
Type
DUNS #
078861598
City
New York
State
NY
Country
United States
Zip Code
10029
Ma'ayan, Avi; Rouillard, Andrew D; Clark, Neil R et al. (2014) Lean Big Data integration in systems biology and systems pharmacology. Trends Pharmacol Sci 35:450-60
Ma'ayan, Avi; Duan, Qiaonan (2014) A blueprint of cell identity. Nat Biotechnol 32:1007-8
Duan, Qiaonan; Flynn, Corey; Niepel, Mario et al. (2014) LINCS Canvas Browser: interactive web app to query, browse and interrogate LINCS L1000 gene expression signatures. Nucleic Acids Res 42:W449-60
Duan, Qiaonan; Wang, Zichen; Fernandez, Nicolas F et al. (2014) Drug/Cell-line Browser: interactive canvas visualization of cancer drug/cell-line viability assay datasets. Bioinformatics 30:3289-90