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Information Systems Program

Functional Genomics Group

As a subgroup of ABCC Bioinformatics Support Group, Functional Genomics Group was created to support functional genomics-related bioinformatics needs and requests including data analysis, lab-based data management and analysis pipelines, modules/tools, web portals, or other bioinformatics infrastructures for NCI clients or collaborators. We also provide suggestions of new needs of databases and tools and methodologies for peer colleagues from other groups of ABCC Bioinformatics Support Group. Most importantly, as Functional Genomic Group, we will more focus on developing methodologies that can help interpret the data for underlying biological implication and meanings such as insights of disease pathogenesis mechanisms through comprehensive pathway and network analysis, data integration from existing and curated databases, text/literature mining as well as users’ and public available high-throughput data at systems biology scale. In the past, the OD-funded staffs primarily engaged in data analysis of collaborators’ data and at the mean time looking for opportunity to develop new methods or algorithms to improve the analysis or address new aspects of questions using the same set of data. The yellow-task staffs primarily engaged in assigned NCI-client-based bioinformatics activities including data analysis, developing lab-based data management and analysis pipelines, modules/tools, web portals or other bioinformatics infrastructures. With the CCR initiative group on board, we will gradually move toward technoogy development direction as a part of strategic plan for ABCC mission, which would back up for CCR initiative group to provide customized or specialized solutions for problems raised from the NCI clients and enhance the capacity of ABCC for functional genomics-related bioinformatics needs and requests.

We primarily performed data analysis of collaborators’ high-throughput data of all kinds including microarray data (expression profiling of mRNAs, miRNA, CGH array etc), proteomic data, metabolome data, SNP data, methylation data, nanostring data etc, as well as downstream analysis (e.g., pathway analysis, interpretation of underlying biological themes) of NextGen data after preprocessing, mapping and alignment such as RNAseq data analysis for differential genes, SNV detection, and SNP impact assessment using Sift/Polyphen-based pipeline (Yellow-task staffs in Dr. Javed’s group). At the mean time, we collated and installed (collaboration with peer colleagues from core infrastructure group), compared, and tested existing analysis tools, methodologies, and algorithms, trying to develop new analysis algorithms, methodologies to improve data analysis and data integration. We are also involved in administrating and training of NCI-licensed commercial analysis tools such as Partek Genomic Suite. Pathway Studio and Agilent Genomic Workbench, which could not only help the NCI clients to have internal support and get hand-on knowledge on these tools for data analysis on their own, but also potentially retrieve and learn the underlying strategies and algorithms from commercial products to help our own tech dev in a long run.

We have also developed and deployed numerous bioinformatics applications to the NCI labs and scientific community including database and processing/analysis pipeline design and construction for NextGen data and microarray data (including NextGen pipeline and databases in Dr. Javed’s lab, Neuroblastoma microarray database in Dr. Javed’s lab;  arrayDB database in Dr. Meltzer’s lab; solexaDB and sraDB databases and tools for NextGen data in Dr. Meltzer’s lab; MAQuery database and web portal tool for Dr. Camphausen’s lab), all of which primarily were accomplished by dedicated yellow-task staffs in the group and can be useful for a broader community as well although currently set up in the designated labs and branches (e.g., sraDB has R package that has been used by broader community). We have also independently developed in-house pathway analysis tool suite WPS (with SLEPR and PPEP methods/tools), which has been published in peer-reviewed journals.

Below is a selected list of our publications from various collaborative projects as well as our tech dev projects showing the breadth of bioinformatics engagement for Functional Genomics Group:

  • miRNA-7 attenuation in Schwannoma tumors stimulates growth by upregulating three oncogenic signaling pathways. Cancer Res. 2011 (PMID: 21156648)
  • Increased NOS2 predicts poor survival in estrogen receptor-negative breast cancer patients. J Clin Invest. 2010 (PMID: 20978357)
  • Reprogramming of T Cells to Natural Killer–Like Cells upon Bcl11b Deletion, Science 2010 (PMID: 20538915)
  • Pathway Analysis: Pathway Signatures and Classification. Chapter 6 in book “Statistics and Informatics in Molecular Cancer Research”, June, 2009. Oxford University Press.
  • microRNA profiling identifies cancer-specific and prognostic signatures in pediatric malignancies. Clin Cancer Res. 2009 (PMID: 19706822)
  • Murine leukemias with retroviral insertions at Lmo2 are predictive of the leukemias induced in SCID-X1 patients following retroviral gene therapy. PLoS Genet. 2009 (PMID: 19461887)
  • SLEPR: a sample-level enrichment-based pathway ranking method — seeking biological themes through pathway-level consistency. PLoS One. 2008 (PMID: 18818771).
  • Genomic profiling of microRNA and messenger RNA reveals deregulated microRNA expression in prostate cancer. Cancer Res. 2008. (PMID: 18676839)
  • Tumor immunobiological differences in prostate cancer between African-American and European-American men. Cancer Res. 2008 (PMID: 18245496)
  • GEOmetadb: powerful alternative search engine for the Gene Expression Omnibus. Bioinformatics 2008 (PMID: 18842599)