NATIONAL CANCER INSTITUTE - CANCER.GOV

Contact Information


Primary Contact

Uma Shankavaram
Associate Scientist

Location

10 center dr
Bethesda
Bethesda, Maryland 20854

Additional Contacts

Kevin Camphausen
Branch Chief

Overview

Radiation Oncology Branch is part of CCR. Bioinformatics core is a collaborative resource to support ROB branch and provide service to ROB investigators from NCI and other Institutes access to new technologies, bioinformatics, statistical analysis related to genetics/genomics, and offers access to in-house built software tools.

Bioinformatics analysis: work with research scientists to provide consulting prior to experiments, analysis of high-throughput sequencing, gene expression, metabolomics, proteomics, and other biological data to identify:

  • prognostic biomarkers
  • transcription factor analysis
  • gene set enrichment analysis
  • prediction models
  • clinical genomics
  • meta-analysis

In-house application development: develop applications to enhance research through web applications for data analysis, databases, visualization, and custom analysis tools:

  • The Glioma Bio Discovery Portal (Glioma-BioDP) is a resource for accessing and displaying interactive views of brain cancer related high throughput molecular data from The Cancer Genome Atlas (TCGA).
  • Query and visualize gene, protein, and microRNA expression profiles.
  • Allow molecular, clinical and histological subtype comparisons.
  • Clinically relevant molecular profiles and inspection of predicted gene-microRNA regulatory relationships.
  • GBM: Search TCGA-GBM dataset by genes and miRNAs
  • LGG: Search TCGA-LGG dataset by genes and miRNAs
  • GBM vs LGG: Search both TCGA-GBM and TCGA-LGG dataset by genes and compare results between two TCGA brain cancer studies
  • SL-BioDP (The Synthetic Lethality BioDiscovery Portal) is a comprehensive web tool for systematic exploration and functional analysis of cancer-specific synthetic lethal (SL) interactions of known cancer susceptibility genes. It hosts SL interactions predicted using DiscoverSL: a machine-learning algorithm for multi-omic TCGA cancer data-driven synthetic lethal interactions. It provides extensive cross-references and user-friendly querying interfaces to support SL-related research. This web portal currently hosts SL interactions for 18 cancer types.

User Guidelines

Collaboration on a case-by-case basis on projects of mutual interest after initial consultation.

Keywords

CCR Radiation Oncology Branch Bioinformatics CoreStRAPbioinformaticsdata analysisgene expresison analysisglioblastoma bio discovery portalhigh throughput sequencing analysismetabolomics analysisproteomics analysissoftwarestatistical analysisstress response array profilier