The STMC Data Analysis and Informatics Core has three principal goals: 1) to improve the mathematical and statistical analysis of quantitative image data generated through both electron and fluorescence microscopy in order to test predicitive models linking membrane organization and dynamics to the control of signaling;2) to provide expertise and computational resources in information acquisition, representation, storage and exchange;and 3) to facilitate sharing and dissemination of STMC-generated data and models. The Data Analysis and Informatics Core will contribute to the state-of-the-art for biomedical image storage, retrieval and analysis and will integrate image data with biological pathways and networks data and with mathematical and statistical models. The STMC Data Anaysis and Informatics Core will operate as a subcore of the CRTC's Bioinformatics and Computational Biology Core (BCB) and will have full access to the expertise and effort of its Director, Dr. Susan Atlas, and professional staff. Through this arrangement, STMC users access a highly functional computational core at a small fraction of its actual cost. The resource is physically located in the UNM Center for High Performance Computing (CHPC), a campus wide facility for computing and data base management and development. As one of five resident Resources of the CHPC, the BCB has highest priority access to its hardware that includes an 8-processor parallel Oracle server, Delphi, a 512-processor Linux supercluster and a new (2005) 20-processor shared-memory IBM supercomputer. The resource has an additional 220 nsf office on the first floor of CRF (immediately below the STMC administrative office) that provides office space and computers for consultation and interactive research. Images of live and fixed cells, including time series images, are critical tools for the biology driving several STMC projects. Initial research will therefore focus on developing, improving and populating image databases and on upgrading an interoperable environment to represent, store, retrieve and share these images among the researchers. The core will additionally provide links to pathways data bases and it will import new bioinformatics and computational biology approaches to the quantitative analysis and modeling of cell signaling and image analysis data established by other groups and centers. Additionally, it will disseminate STMC models and codes to other users.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Specialized Center (P50)
Project #
5P50GM085273-04
Application #
8380700
Study Section
Special Emphasis Panel (ZGM1-CBCB-4)
Project Start
Project End
Budget Start
2012-08-01
Budget End
2013-07-31
Support Year
4
Fiscal Year
2012
Total Cost
$157,076
Indirect Cost
$52,358
Name
University of New Mexico
Department
Type
DUNS #
868853094
City
Albuquerque
State
NM
Country
United States
Zip Code
87131
Tasnim, Humayra; Fricke, G Matthew; Byrum, Janie R et al. (2018) Quantitative Measurement of Naïve T Cell Association With Dendritic Cells, FRCs, and Blood Vessels in Lymph Nodes. Front Immunol 9:1571
Travers, Timothy; López, Cesar A; Van, Que N et al. (2018) Molecular recognition of RAS/RAF complex at the membrane: Role of RAF cysteine-rich domain. Sci Rep 8:8461
Suderman, Ryan; Mitra, Eshan D; Lin, Yen Ting et al. (2018) Generalizing Gillespie's Direct Method to Enable Network-Free Simulations. Bull Math Biol :
Pallikkuth, Sandeep; Martin, Cheyenne; Farzam, Farzin et al. (2018) Sequential super-resolution imaging using DNA strand displacement. PLoS One 13:e0203291
López, Cesar A; Unkefer, Clifford J; Swanson, Basil I et al. (2018) Membrane perturbing properties of toxin mycolactone from Mycobacterium ulcerans. PLoS Comput Biol 14:e1005972
Peretti, Amanda S; Dominguez, Dayna; Grimes, Martha M et al. (2018) The R-Enantiomer of Ketorolac Delays Mammary Tumor Development in Mouse Mammary Tumor Virus-Polyoma Middle T Antigen (MMTV-PyMT) Mice. Am J Pathol 188:515-524
Brandsma, Arianne M; Schwartz, Samantha L; Wester, Michael J et al. (2018) Mechanisms of inside-out signaling of the high-affinity IgG receptor Fc?RI. Sci Signal 11:
Hudson, Laurie G; Gillette, Jennifer M; Kang, Huining et al. (2018) Ovarian Tumor Microenvironment Signaling: Convergence on the Rac1 GTPase. Cancers (Basel) 10:
Palsuledesai, Charuta C; Surviladze, Zurab; Waller, Anna et al. (2018) Activation of Rho Family GTPases by Small Molecules. ACS Chem Biol 13:1514-1524
Kumar, Suresh; Jain, Ashish; Farzam, Farzin et al. (2018) Mechanism of Stx17 recruitment to autophagosomes via IRGM and mammalian Atg8 proteins. J Cell Biol 217:997-1013

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