Pacific Symposium on Biocomputing

The article, "Discovering Implicit Association Between Genes and Hereditary Diseases," authored by SLIS faculty member Javed Mostafa and Kazuhiro Seki (recent SLIS Ph.D. graduate - now working at Kobe University in Japan), has been published in the Proceedings of the Pacific Symposium on Biocomputing.

The Pacific Symposium on Biocomputing (PSB) was held in Hawaii, January 2007. According to the symposium's website, PSB "was an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in problems of biological significance."

Abstract
We propose an approach to predicting implicit gene-disease association based on the inference network, whereby genes and diseases are represented as nodes and are connected via two types of intermediate nodes: gene functions and phenotypes. To estimate the probabilities involved in the model, two learning schemes are compared; one baseline using co-annotations of keywords and the other taking advantage of free text. Additionally, we explore the use of domain ontologies to complement data sparseness and examine the impact of full text documents. The validity of the proposed framework is demonstrated on the benchmark data set created from real-world data.

Seki, K. & Mostafa, J. Discovering implicit association between genes and hereditary diseases. In the Proceedings of the Pacific Symposium on Biocomputing, Wailea, Maui, Jan. 3rd, 2007.

Posted February 08, 2007