RgS-miner: A biological data warehousing, analyzing and mining system for identifying transcriptional regulatory sites in human genome

Yi Ming Sun, Hsien Da Huang, Jorng Tzong Horng, Ann Ping Tsou, Shir Ly Huang

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Recently, biological databases and analytical methods have become available for analyzing gene expression and transcriptional regulatory sequences. However, users must make the complicated analyses to query the data in various databases, and then they must analyze the gene upstreams using various predictive tools, before finally converting date among formats. Beyond methods for predicting transcriptional regulatory sites, new automated and integrated methods for analyzing gene upstream sequences on a higher level are urgently required. Efficient and integrated data management methods are essential, too. We present an integrated system, namely RgS-Miner, to predict transcriptional regulatory sites and detect co-occurrence of these regulatory sites. RgS-Miner comprises a biological data warehousing system, pattern discovery programs, pattern occurrence association detectors and user interfaces. The system is available at http://rgsminer.csie.ncu.edu.tw/.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsFernando Galindo, Makoto Takizawa, Roland Traunmuller
PublisherSpringer Verlag
Pages751-760
Number of pages10
ISBN (Print)3540229361, 9783540229360
DOIs
StatePublished - 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3180
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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