The application of alternative splicing graphs in quantitative analysis of alternative splicing form from EST database

  • Authors:

  • Hsun-Chang Chang;Po-Shun Yu;Tze-Wei Huang;Fang-Rong Hsu;Yaw-Ling Lin

  • Affiliations:

  • Department of Computer Science and Information Management, Providence University, Shalu, Taichung County, Taiwan 443, ROC.;Department of Computer Science and Information Management, Providence University, Shalu, Taichung County, Taiwan 443, ROC.;Department of Computer Science and Information Management, Providence University, Shalu, Taichung County, Taiwan 443, ROC.;Department of Information Engineerging and Computer Science, Feng Chia University, Taichung, Taiwan 40724, ROC.;Department of Computer Science and Information Management, Providence University, Shalu, Taichung County, Taiwan 443, ROC

  • Venue:
  • International Journal of Computer Applications in Technology
  • Year:
  • 2005

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Abstract

Alternative splicing is an important mechanism for generating protein diversity from a single gene. However, standard molecular biology techniques have only identified several hundred alternative splicing variants and created a bottleneck in terms of experimental validation. In this paper, we propose models of weighted alternative splicing graphs and ways of generating all alternative splicing forms from an alternative splicing graph. By formulating linear programming models, we can deduce the quantitative distributions of various alternative splicing forms. Linear time algorithms that produce all alternative splicing variants with their corresponding probabilities are proposed. Finally, by aligning sequences of EST databases to the genomic data, locations of exons as well as the alternative splicing sites can be identified, and several sets of putative alternative splicing forms is inferred using these methods.