Jeffrey Shih-Chieh Chu

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BACKGROUND Computational prediction of functionally related groups of genes (functional modules) from large-scale data is an important issue in computational biology. Gene expression experiments and interaction networks are well studied large-scale data sources, available for many not yet exhaustively annotated organisms. It has been well established, when(More)
BACKGROUND Five regulatory factor X (RFX) transcription factors (TFs)-RFX1-5-have been previously characterized in the human genome, which have been demonstrated to be critical for development and are associated with an expanding list of serious human disease conditions including major histocompatibility (MHC) class II deficiency and ciliaophathies. (More)
MOTIVATION BLAST users frequently expect to obtain homologous genes with certain similarity to their query genes. But what they get from BLAST searches are often collections of local alignments called high-scoring segment pairs (HSPs). On the other hand, most homology-based gene finders have been built using computation-intensive algorithms, without taking(More)
Gene prediction is one of the most challenging tasks in genome analysis, for which many tools have been developed and are still evolving. In this paper, we present a novel gene prediction method that is both fast and accurate , by making use of protein homology and decision tree classification. Specifically, we apply the principled entropy and decision tree(More)
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