The Bioinformatics Facility provides Cancer Center investigators with database management, software applications support, and expertise in statistical analyses and computational modeling of biomedical research data. In response to the growing informatics needs of funded Cancer Center researchers, the Bioinformatics Facility was established in 2001 with a combination of Cancer Center developmental funds and institutional support. The Cancer Center has made major investments to increase Bioinformatics facility space, instrumentation, and personnel over the past funding period. Under the direction of Dr. Ramana Davuluri, Director of Computational Biology, the Bioinformatics Facility has recently grown to consist of faculty, programmers, and statistical specialists from the Center for Systems and Computational Biology. Functions of the Facility reflect the research requirements of the three Cancer Center programs and are broadly divided into three areas: (i) data-management;(ii) statistical analyses and computational modeling; and (iii) advanced bioinformatics tools for integrative cancer biology. Specific services of the Bioinformatics Facility are to: 1) provide computational support for use of database software and bioinformatics tools;2) provide consulting support regarding statistical design and data analyses for high-throughput experiments;3) provide shared archives for high throughput molecular (both microarray and sequencing) data, tissue related data, image data, and pharmacodynamics data (extended and new service);and 4) adapt and implement cohesive analysis and data mining tools that allow for integration and cross-validation of the comprehensive molecular data used in integrative cancer biology research (new service in 2008). The Facility has placed a high priority on integrating cancer research information representing a variety of data types, including clinical patient data, molecular data from microarrays, massive-parallel sequencers (e.g. Illumina [Solexa] Genome Analyzer) and RT-PCR, and image data from digitized microscopy slides. Data security is a primary focus of the Bioinformatics Facility in designing and implementing software systems. The Facility also provides computational bioinformatics support to assist in the analysis of genomic, molecular, and proteomic data using commercial and locally-developed software packages. Most recently, the facility has been re-located into newly renovated space (2,006 sq. ft.), providing a state-ofthe- art server room and expanded office and conference room space.
Modern Cancer research creates large amount of data, much in digital forms. These data need to be managed, interpreted, and stored by qualified professionals who have an understanding of biology and computer sciences as well as adequate modern resources to carry out these functions.
|Tempera, Italo; De Leo, Alessandra; Kossenkov, Andrew V et al. (2016) Identification of MEF2B, EBF1, and IL6R as Direct Gene Targets of Epstein-Barr Virus (EBV) Nuclear Antigen 1 Critical for EBV-Infected B-Lymphocyte Survival. J Virol 90:345-55|
|Nelson, David M; Jaber-Hijazi, Farah; Cole, John J et al. (2016) Mapping H4K20me3 onto the chromatin landscape of senescent cells indicates a function in control of cell senescence and tumor suppression through preservation of genetic and epigenetic stability. Genome Biol 17:158|
|Seo, Jae Ho; Rivadeneira, Dayana B; Caino, M Cecilia et al. (2016) The Mitochondrial Unfoldase-Peptidase Complex ClpXP Controls Bioenergetics Stress and Metastasis. PLoS Biol 14:e1002507|
|Haut, Larissa H; Gill, Amanda L; Kurupati, Raj K et al. (2016) A Partial E3 Deletion in Replication-Defective Adenoviral Vectors Allows for Stable Expression of Potentially Toxic Transgene Products. Hum Gene Ther Methods :|
|Peck, Barrie; Schug, Zachary T; Zhang, Qifeng et al. (2016) Inhibition of fatty acid desaturation is detrimental to cancer cell survival in metabolically compromised environments. Cancer Metab 4:6|
|Chae, Young Chan; Vaira, Valentina; Caino, M Cecilia et al. (2016) Mitochondrial Akt Regulation of Hypoxic Tumor Reprogramming. Cancer Cell 30:257-72|
|Vazquez, Alexei; Kamphorst, Jurre J; Markert, Elke K et al. (2016) Cancer metabolism at a glance. J Cell Sci 129:3367-73|
|Kumar, Vinit; Patel, Sima; Tcyganov, Evgenii et al. (2016) The Nature of Myeloid-Derived Suppressor Cells in the Tumor Microenvironment. Trends Immunol 37:208-20|
|Kung, Che-Pei; Murphy, Maureen E (2016) The role of the p53 tumor suppressor in metabolism and diabetes. J Endocrinol 231:R61-R75|
|Patro, Sean C; Azzoni, Livio; Joseph, Jocelin et al. (2016) Antiretroviral therapy in HIV-1-infected individuals with CD4 count below 100 cells/mm3 results in differential recovery of monocyte activation. J Leukoc Biol 100:223-31|
Showing the most recent 10 out of 582 publications