Bioinformatics

David Mount, PhD, Director

Ritu Pandey, PhD, Co-Director

The Bioinformatics Shared Resource at The University of Arizona provides support in the following areas:

  • Analysis of genomic (e.g. gene expression, CGH, DNA methylation, RNAi screens, genome and sequence analysis), genetic (SNP analysis), proteomics, and other types of molecular data sets of cancer cells and tissues
  • Analysis of cancer genomic, molecular, and genetic data collected by other University of Arizona Cancer Center Shared Resources, TGen, and other data sources, but especially Cancer Center Genomics and Proteomics Shared Resources.
  • Biological interpretation of the above data, including pathway and ontology analysis, systems analysis, genetic vulnerabilities for drug targeting, predictive patterns for outcome, and data modeling
  • Informatics support for Cancer Center projects and other Shared Resources in the form of tissue and molecular databases, genome databases, and data sharing tools.

Who we are

The Bioinformatics Shared Resource was founded in 2002 to provide bioinformatics, genomics, and proteomics support to The University of Arizona Cancer Center researchers so that they can fully utilize the power of the human genome project in their research. The Shared Resosurce collects, stores, and makes available a variety of molecular and genetic data on cancer genomes. It uses established computational tools but also develops new tools as needed for analysis of all genome-related data. A variety of computer-related services for informatics support of research projects is also provided. Through these various levels of support, the Bioinformatics Shared Resource provides an integrated approach that assists researchers in their quest for new biological information about cancer cells and tissues and thus aids in finding new drug targets and preventative methods. Some examples of the types of services we offer are given below.

The Bioinformatics group includes the following staff members

  • David W. Mount, PhD, Director of the Bioinformatics Shared Resource, is Professor Emeritus of Molecular and Cellular Biology. He is an established geneticist and molecular biologist and an expert in bioinformatics and computational biology.
  • Ritu Pandey, PhD, Co-Director of Bioinformatics Shared Resource and Coordinator of Biomedical informatics at The University of Arizona Cancer Center. She was the CaBIG (Cancer Bioinformatics Grid) Deployment lead at the cancer center. Dr. Pandey specializes in storage, collection, management, and utilization of genomic and proteomics data for interpretation of large data sets.

   Location

  • All the Informatics and Bioinformatic team members are currently  located on the first floor of the Levy building in and around rooms 1930

      Mailing Address: 
                          
                           The University of Arizona Cancer Center
                           1515 N. Campbell Ave.
                           PO Box 245024
                           Tucson, AZ  85724-5024

BSR Project Pricing, Turnaround Time & Consulting

Interaction with Cancer Center Members:

The service offered is expertise in data analysis and management. If staff can assist a cancer researcher on a temporary consulting basis, then the Shared Resource will charge for the time spent on a project. The Shared Resource staff welcomes the opportunity to participate in laboratory meetings, research discussions and writing papers and grant applications. Staff can perform a free preliminary data analysis to support the feasibility of an application and can also add experience and expertise in data management and analysis, thereby helping to increase the fundability of many research grant applications. 

Expertise

Areas of expertise include both computational biology - biological sequence analysis, protein structure analysis, genome analysis, advanced computational analysis of large data sets such as gene expression, single nucleotide polymorphism (SNPs) and proteomics data and basic biological studies - population and molecular genetics, molecular and cell biology, biochemistry, and evolutionary biology. The goal is to provide assistance with data analysis that will lead to testable hypotheses and fundamentally important discoveries in cancer research. Staff specializes in the biological interpretation of data, leading to a new understanding of cancer biology, and the discovery of new diagnostic markers, risk genetic markers (haplotypes), patterns in data, and drug targets. The staff is well prepared to perform all of these types of analysis.

Some of our Past Informatics Initiatives at the Cancer Center

These are some of the tools that were developed by the group or adopted and deployed to support Cancer Center programs, Shared Resources and the researchers. 

  • Protbase — This is a web based lab data management system for Proteomics Shared Resource. This system offers users to submit sample request, track their experiment, download/view results and share their experiments. Further more, it offers facility core staff to track experiments request and lab usage for proteomics services, upload results and bill the researchers for services offered. 
  • Genomics Core database — A storing and tracking system for microarray data for the Genomics Shared Resource. 
  • AZCC PubDB —  A web based system for storing and tracking publications by University of Arizona Cancer Center members, programs and shared services.
  • Pathway Miner — A web based system for biological interpretation of results from microarray experiments. 


    Informatics systems that have been discontinued for further use:

  • CaIntegrator2  
  • CaArray 
  • CaTissue
  • GI Tissue DB
  • Prostate Tissue DB

Future role for the Bioinformatics Shared Resource as a resource for Cancer Genome and Population Genetic Data.

The Bioinformatics Shared Resource will continue to aid The University of Arizona Cancer Center investigators with access to genome and proteome data, data analysis, and integration of large data sets data with clinical and biological information for specific research projects. It will keep abreast of new data sets, analytical tools and generate new computational tools and methods, as needed. Submit Feedback

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