Overview
- Editors:
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Daisuke Kihara
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Dept. Biological Science, Purdue University, West Lafayette, USA
- The first book which focus on describing state-of-the-art function prediction methods
- Probably the first book which points out that the role of function prediction has been changing for analyzing omics type large scale data, rather than function of a small set of individual genes of interest
- Observes emerging development of computational gene function prediction methods
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Table of contents (15 chapters)
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Front Matter
Pages i-xiii
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- Meghana Chitale, Daisuke Kihara
Pages 1-17
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- Meghana Chitale, Daisuke Kihara
Pages 19-34
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- Vikas Rao Pejaver, Heewook Lee, Sun Kim
Pages 35-54
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- Dennis R. Livesay, Dukka Bahadur KC, David La
Pages 93-105
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- Alison Cuff, Oliver Redfern, Benoit Dessailly, Christine Orengo
Pages 107-123
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- Joe Dundas, Bhaskar DasGupta, Jie Liang
Pages 125-143
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- Rayan Chikhi, Lee Sael, Daisuke Kihara
Pages 145-163
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- Joslynn S. Lee, Mary Jo Ondrechen
Pages 183-196
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- Kengo Kinoshita, Takeshi Obayashi
Pages 197-214
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- Weidong Tian, Xinran Dong, Yuanpeng Zhou, Ren Ren
Pages 215-242
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- Hon Nian Chua, Guimei Liu, Limsoon Wong
Pages 243-270
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- Toshiaki Tokimatsu, Masaaki Kotera, Susumu Goto, Minoru Kanehisa
Pages 271-288
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- Yukako Tohsato, Natsuko Yamamoto, Toru Nakayashiki, Rikiya Takeuchi, Barry L. Wanner, Hirotada Mori
Pages 289-305
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Back Matter
Pages 307-310
About this book
Gene function annotation has been a central question in molecular biology. The importance of computational function prediction is increasing because more and more large scale biological data, including genome sequences, protein structures, protein-protein interaction data, microarray expression data, and mass spectrometry data, are awaiting biological interpretation. Traditionally when a genome is sequenced, function annotation of genes is done by homology search methods, such as BLAST or FASTA. However, since these methods are developed before the genomics era, conventional use of them is not necessarily most suitable for analyzing a large scale data. Therefore we observe emerging development of computational gene function prediction methods, which are targeted to analyze large scale data, and also those which use such omics data as additional source of function prediction. In this book, we overview this emerging exciting field. The authors have been selected from 1) those who develop novel purely computational methods 2) those who develop function prediction methods which use omics data 3) those who maintain and update data base of function annotation of particular model organisms (E. coli), which are frequently referred
Editors and Affiliations
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Dept. Biological Science, Purdue University, West Lafayette, USA
Daisuke Kihara
