The mission of the Systems and Computational Biology Core (SCB) is to provide technology resources and support services in systems and computational biology for KCI members, and to promote collaborative research in systems-based oncology across all five Programs. To accomplish this mission, SCB activities are focused in the areas of: 1) workflow planning and experimental design of studies in functional genomics, genetic variation, and cancer systems biology;2) analysis and interpretation of gene expression profiling data (e.g., oncogenomic signatures);3) analysis and modeling of genotype profiling data from both population studies of inherited cancer risk factors and from molecular studies of somatic variation in individual tumors;4) pathway and network modeling of high throughput (""""""""omics"""""""") data for biomarker and drug target discovery;and 5) database management and integration of functional genomics and genotype data for clinical translational oncology (e.g., deployment of NCI caBIG? tools). In particular, SCB activities enable the application of molecular profiling and network modeling approaches to clinical studies ranging from the molecular to the population level. The key service lines for the SCB provide an integrated workflow pipeline for all stages of a systems-based project, from pre-project planning and experimental design through post-experiment data analysis and interpretation. Consultation and user training are key components of SCB's approach to lowering the technology barrier for KCI members who wish to incorporate computational analytics and molecular profiling tools into their research projects.
The Systems and Computational Biology Core provides integrative capabilities that support the translation of results from basic research in cancer biology into practical clinical applications for the diagnosis, prognosis and therapy of cancer as a systemic disease.
|Watza, Donovan; Purrington, Kristen S; Chen, Kang et al. (2017) Transcriptional programs of tumor infiltrating T-cells provide insight into mechanisms of immune response and new targets for immunotherapy. J Thorac Dis 9:4162-4164|
|Eggly, Susan; Hamel, Lauren M; Foster, Tanina S et al. (2017) Randomized trial of a question prompt list to increase patient active participation during interactions with black patients and their oncologists. Patient Educ Couns 100:818-826|
|Bao, Bin; Mitrea, Cristina; Wijesinghe, Priyanga et al. (2017) Treating triple negative breast cancer cells with erlotinib plus a select antioxidant overcomes drug resistance by targeting cancer cell heterogeneity. Sci Rep 7:44125|
|Bernardo, Margarida M; Dzinic, Sijana H; Matta, Maria J et al. (2017) The Opportunity of Precision Medicine for Breast Cancer With Context-Sensitive Tumor Suppressor Maspin. J Cell Biochem 118:1639-1647|
|Soave, Claire L; Guerin, Tracey; Liu, Jinbao et al. (2017) Targeting the ubiquitin-proteasome system for cancer treatment: discovering novel inhibitors from nature and drug repurposing. Cancer Metastasis Rev 36:717-736|
|Jones, Carissa C; Bush, William S; Crawford, Dana C et al. (2017) Germline Genetic Variants and Lung Cancer Survival in African Americans. Cancer Epidemiol Biomarkers Prev 26:1288-1295|
|Bosnyák, Edit; Michelhaugh, Sharon K; Klinger, Neil V et al. (2017) Prognostic Molecular and Imaging Biomarkers in Primary Glioblastoma. Clin Nucl Med 42:341-347|
|Ben Khedher, Soumaya; Neri, Monica; Papadopoulos, Alexandra et al. (2017) Menstrual and reproductive factors and lung cancer risk: A pooled analysis from the international lung cancer consortium. Int J Cancer 141:309-323|
|Tan, Zhijing; Nie, Song; McDermott, Sean P et al. (2017) Single Amino Acid Variant Profiles of Subpopulations in the MCF-7 Breast Cancer Cell Line. J Proteome Res 16:842-851|
|Embogama, D Maheeka; Pflum, Mary Kay H (2017) K-BILDS: A Kinase Substrate Discovery Tool. Chembiochem 18:136-141|
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