Approach 1. Network Analysis and Visualization: We will support the four research themes by developing data analysis tools and databases, as well as by participating in data analysis for projects with external collaborators. We will provide ongoing support for analysis of genomic and proteomic data. Initial analysis of the genomic and proteomic data to identify statistical differences caused by the various perturbations will be done within these facilities. Once the changes are identified, the differentially modulated gene/proteins will be used to develop networks, and classifiers in Theme 1 and the data from these analyses will be transferred to the Core for visualization and distribution to the research community. We will continue the development of web-based applications to support interactive visualization of networks and dynamical models. We have extensive experience in the development and distribution of such web based programs as have been described in the Progress Report Section (19, 21, 24, 26, 27, 29-32, 47, 50). In the coming term we will use newer technologies such as HTML5 including the implementation of the features offered by D3, a new JavaScript library for data visualization. We will maintain a mySQL database that contains information about drug properties, drug-drug networks, gene properties, gene regulatory networks, protein-protein interactions, protein kinase-substrate interactions, cell signaling networks and data from quantitative dynamical models. In addition, since HTML5 offers easy Mobile integration we will launch several of the web-based applications for Mobile use as phone and tablet Apps. As part of the research themes we plan to develop a web-interface for the drug/side-effect classifier proposed for Theme 1. We will develop web visualization for the both the underlying networks and the dynamical models that will be developed in Themes 2 and 3. This will enable the wide dissemination of these models so that they can be used by others. For Theme 4 we will develop the heart 3D models as an interactive online tool where users will be able to tune parameters and run simulations online.

Agency
National Institute of Health (NIH)
Type
Specialized Center (P50)
Project #
5P50GM071558-07
Application #
8728883
Study Section
Special Emphasis Panel (ZGM1)
Project Start
Project End
Budget Start
Budget End
Support Year
7
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Icahn School of Medicine at Mount Sinai
Department
Type
DUNS #
City
New York
State
NY
Country
United States
Zip Code
10029
Duarte, Luis F; Young, Andrew R J; Wang, Zichen et al. (2014) Histone H3.3 and its proteolytically processed form drive a cellular senescence programme. Nat Commun 5:5210
Gao, Hao; Wang, Huiming; Berry, Colin et al. (2014) Quasi-static image-based immersed boundary-finite element model of left ventricle under diastolic loading. Int J Numer Method Biomed Eng 30:1199-222
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
Hays, Thomas; Ma'ayan, Avi; Clark, Neil R et al. (2014) Proteomics analysis of the non-muscle myosin heavy chain IIa-enriched actin-myosin complex reveals multiple functions within the podocyte. PLoS One 9:e100660
Rangamani, Padmini; Xiong, Granville Yuguang; Iyengar, Ravi (2014) Multiscale modeling of cell shape from the actin cytoskeleton. Prog Mol Biol Transl Sci 123:143-67
Azeloglu, Evren U; Hardy, Simon V; Eungdamrong, Narat John et al. (2014) Interconnected network motifs control podocyte morphology and kidney function. Sci Signal 7:ra12
Kivell, Bronwyn; Uzelac, Zeljko; Sundaramurthy, Santhanalakshmi et al. (2014) Salvinorin A regulates dopamine transporter function via a kappa opioid receptor and ERK1/2-dependent mechanism. Neuropharmacology 86:228-40
Cummins, Megan A; Dalal, Pavan J; Bugana, Marco et al. (2014) Comprehensive analyses of ventricular myocyte models identify targets exhibiting favorable rate dependence. PLoS Comput Biol 10:e1003543
Chary, Michael; Kaplan, Ehud (2014) Synchrony can destabilize reward-sensitive networks. Front Neural Circuits 8:44
Bouhaddou, Mehdi; Birtwistle, Marc R (2014) Dimerization-based control of cooperativity. Mol Biosyst 10:1824-32

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