INSTINCT/QB3

The INSTINCT (INformatics Supporting Therapy in INdividualized Clinical Trials) project is a QB3-based multidisciplinary collaboration between UC Santa Cruz and UC San Francisco designed to apply genomic knowledge to clinical research. The collaboration will address important scientific and health problems in the areas of cancer, autoimmune, and neurological diseases.

With the advent of high-throughput sequencing techniques, genomics plays an increasingly important role in many areas of medicine. The comprehensive analysis of genomic and clinical data can lead to major new insights in medical research. However, the application of genomic knowledge is hampered in part because limited tools are available for mining the vast amount of information and translating it into discovery.

The Haussler lab at UC Santa Cruz and the UCSC Genome Bioinformatics group have developed computational techniques and software programs that are widely used in genome research, including the popular UCSC Genome Browser and the UCSC Cancer Genomics Browser to facilitate the visualization, integration, comparison and analysis of large sets of genomic and clinical data in the cancer field. As genome-wide high-throughput data become more available, we expect tools of this nature to play a progressively more central role in many disease areas.

A leading center for biomedical sciences, UCSF is hosting some of the best clinical and experimental research in the country.

The combination of UCSC’s bioinformatics expertise with the clinical and experimental research at UCSF will lead to creative and powerful new genomics applications.

As part of this collaboration, UCSC will develop tools for the UCSC Cancer Genomics Browser for the analysis, visualization, and integration of exploratory data. UCSC's tools and algorithms perform advanced statistical analysis and use machine learning techniques to identify patterns in genomics data and correlate them with clinical information. By working together to apply these tools to genomics data generated by clinical research at UCSF, we hope to participate in the development of new approaches in critical disease areas.

UCSC is primarily interested in projects with a significant amount of genomics data, at minimum large sets of gene expression data, but ideally including data on copy number variation, mutation, epigenomic changes, or miRNA profiling.  Because large sample number is extremely important for statistical analysis, larger clinical trials or research projects with many samples from many patients will be essential.

This collaboration will generate a synergistic effect in important areas of disease research that could not be achieved by either group alone.