{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,7,19]],"date-time":"2024-07-19T00:53:45Z","timestamp":1721350425191},"reference-count":62,"publisher":"World Scientific Pub Co Pte Lt","issue":"04","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Bioinform. Comput. Biol."],"published-print":{"date-parts":[[2016,8]]},"abstract":"<jats:p> Cancer is a complex disease that cannot be diagnosed reliably using only single gene expression analysis. Using gene-set analysis on high throughput gene expression profiling controlled by various environmental factors is a commonly adopted technique used by the cancer research community. This work develops a comprehensive gene expression analysis tool (gene-set activity toolbox: (GAT)) that is implemented with data retriever, traditional data pre-processing, several gene-set analysis methods, network visualization and data mining tools. The gene-set analysis methods are used to identify subsets of phenotype-relevant genes that will be used to build a classification model. To evaluate GAT performance, we performed a cross-dataset validation study on three common cancers namely colorectal, breast and lung cancers. The results show that GAT can be used to build a reasonable disease diagnostic model and the predicted markers have biological relevance. GAT can be accessed from http:\/\/gat.sit.kmutt.ac.th where GAT\u2019s java library for gene-set analysis, simple classification and a database with three cancer benchmark datasets can be downloaded. <\/jats:p>","DOI":"10.1142\/s0219720016500153","type":"journal-article","created":{"date-parts":[[2016,3,15]],"date-time":"2016-03-15T08:11:12Z","timestamp":1458029472000},"page":"1650015","source":"Crossref","is-referenced-by-count":4,"title":["Gene-set activity toolbox (GAT): A platform for microarray-based cancer diagnosis using an integrative gene-set analysis approach"],"prefix":"10.1142","volume":"14","author":[{"given":"Worrawat","family":"Engchuan","sequence":"first","affiliation":[{"name":"Data and Knowledge Engineering Laboratory, School of Information Technology, King Mongkut\u2019s University of Technology Thonburi, Bangkok, Thailand"}]},{"given":"Asawin","family":"Meechai","sequence":"additional","affiliation":[{"name":"Department of Chemical Engineering, Faculty of Engineering, King Mongkut\u2019s University of Technology Thonburi, Bangkok, Thailand"}]},{"given":"Sissades","family":"Tongsima","sequence":"additional","affiliation":[{"name":"Biostatistics and Informatics Laboratory, Genome Technology Research Unit, National Center for Genetic Engineering and Biotechnology"}]},{"given":"Narumol","family":"Doungpan","sequence":"additional","affiliation":[{"name":"Biological Engineering Program, Faculty of Engineering, King Mongkut\u2019s University of Technology Thonburi, Bangkok, Thailand"}]},{"given":"Jonathan H.","family":"Chan","sequence":"additional","affiliation":[{"name":"Data and Knowledge Engineering Laboratory, School of Information Technology, King Mongkut\u2019s University of Technology Thonburi, Bangkok, 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