Cancer Transcriptomics: Integrative and Computational Approaches

Oncogenomics is a relatively new sub-field of genomics that applies high throughput technologies to characterize genes associated with cancer. The study involves the research in to the Bioinformatics and functional analysis of oncogenes, which refers to the gene that has the potential to cause cancer. In tumor cells, they are often mutated or expressed at high levels.

Cancer genome sequencing requires the development of new techniques utilizing Genomics and bioinformatics tools for target assessment, including both experimental protocols and data analysis algorithms, to enable a deeper understanding of complex biological systems. Databases for Cancer Research have been developed which primarily study the Mutations in Mitochondrial DNA and Cancer to come up with effective and informative databases.   It involves the development of Tools for integrative meta-analysis, 3c-based data integration and application of Networks and OMICS data, mathematical modeling and computational simulation techniques to the study of Integrative eqtl-based analyses, High performance genomics data visualization and Laboratory information management system to come up with Potential Diagnostic Applications. 

Computational Genomics research has grown after the increased research in Genomics with major universities like Iowa State University, University Of California, and The George Washington University Concentrating on the growing topic. The Bisti Consortium has even launched the NIH and Government Programs and Initiatives in Biomedical Informatics and Computational Biology (BICB) with a list of programs concentrating on Computational Biology Research.

 

The overall mission of Oncogenomics is to leverage the power of genome wide high-throughput approaches to improve the outcome of patients with high risk cancers. A genomic era of cancer studies is developing rapidly, fueled by the emergence of next-generation sequencing technologies that provide exquisite sensitivity and resolution. Integrative analyses that evaluate cancer transcriptome data in the context of other data sources are often capable of extracting deeper biological insight from the data. Comparative oncogenomics identifies breast tumors enriched in functional tumor-initiating cells and several other types of oncogenic cells. Somatic mitochondrial DNA (mtDNA) mutations have been increasingly observed in primary human cancers. As each cell contains many mitochondria with multiple copies of mtDNA, it is possible that wild-type and mutant mtDNA can co-exist in a state called heteroplasmy. A cancer biomarker refers to a substance or process that is indicative of the presence of cancer in the body.

  • Introduction to Oncogenomics
  • Cancer genome sequencing
  • Cancer Transcriptomes
  • Bioinformatics and functional analysis of oncogenes
  • Comparative Oncogenomics
  • Databases for Cancer Research
  • Advances from Oncogenomics
  • Mutations in Mitochondrial DNA and Cancer
  • Potential Diagnostic Applications
  • Cancer Biomarkers
  • P53 mediated Transcriptomics

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