Systematic Discovery of Non-Obvious Human Disease Models and Candidate Disease Genes Through Phenologs

Life Sciences : Research Tools

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  • Edward Marcotte, Ph.D. , Molecular Biosciences
  • Kriston McGary , Cellular and Molecular Biology
  • John Wallingford, Ph.D. , Molecular Cell and Developmental Biology
  • Tae Joo Park, Ph.D. , Integrative Biology
  • John Woods III , Cellular and Molecular Biology
  • Hye Ji Cha , Cellular and Molecular Biology

Background/unmet need

Determining individual gene functions is a challenging endeavor. Few standard systems to demonstrate gene function and impact exist, and identifying new ways to scan for specific disease-related genes remains a top medical priority.

Some of the most rapidly growing medical analyses depend on breakthroughs in understanding the human genome. Identifying the function, utility, and impact of individual genes will lead to advances in many medical fields and perhaps revolutionize the way many diseases are treated.

Invention Description

The mapping between genotype and phenotype is often non-obvious, and predicting genes underlying a particular phenotype is difficult. Researchers at The University of Texas at Austin have developed a novel computational method that identifies non-obvious human disease models in a manner that simultaneously identifies candidate disease genes. This quantitative, software supported, system has generated leads to several new disease-relevant genes.

The novel UT Austin invention has already been applied to identify a non-vertebrate model for neural-tube closure birth defects, such as spina bifida. The model was successfully applied to find new vertebrate genes associated with neural-tube closure defects. Other demonstrated applications include identification of a yeast model system capable of identifying vertebrate genes that participate in angiogenesis. In principle, this technology can be applied to any human disease for which a limited initial set of candidate genes is already available. Interested parties will benefit from the inventors’ funding from an NIH grant.

The current key application for this novel UT Austin invention is disease-related gene identification. However, the inventors predict that their novel system could, in the near future, be incorporated into model organism-based lead compound drug screening assays.


  • Non-obvious human disease models and candidate disease genes
  • Offers efficient, systematic model of analysis
  • Provides cheaper and faster alternative to existing methods

Market potential/applications

The U.S. market for therapeutics and diagnostics for genetic diseases reached $4.8 billion in 2005 and is expected to grow at an average annual rate of 8.7%, reaching $7.3 billion by 2010. (

Development Stage

Proof of concept