About the Book
Preface; 1 Computational protein function prediction: framework and challenges, Meghana Chitale, Daisuke Kihara (Purdue University, USA); 2 Enhanced sequence-based function prediction methods and application to functional similarity networks, Meghana Chitale, Daisuke Kihara (Purdue University, USA); 3 Gene cluster prediction and its application to genome annotation, Vikas Rao Pejaver, Heewook Lee, Sun Kim (Indiana University, USA); 4 Functional inference in microbial genomics based on large-scale comparative analysis, Ikuo Uchiyama (National Institute for Basic Biology, Japan); 5 Predicting protein functional sites with phylogenetic motifs: Past, present and beyond, Dennis R. Livesay, Dukka Bahadur K.C., David La (Univ. North Carolina, USA); 6 Exploiting protein structures to predict protein functions, Alison Cuff, Oliver Redfern, Benoit Dessailly, Christine Orengo (University College London, UK); 7 Sequence order independent comparison of protein global backbone structures and local binding surfaces for evolutionary and functional inference, Joe Dundas, Bhaskar DasGupta, Jie Liang (Univ. Illinois at Chicago, USA); 8 Protein binding ligand prediction using moment-based methods, Rayan Chikhi, Lee Sael, Daisuke Kihara (Purdue University, USA); 9 Computational methods for predicting DNA-binding sites at a genome scale, Shandar Ahmad (Nat. Institute of Biomedical Innovation, Japan); 10 Electrostatic properties for protein functional site annotation, Joslynn S. Lee, Mary Jo Ondrechen (Northeastern University, USA); 11 Function prediction of genes: from molecular function to cellular function, Kengo Kinoshita, Takeshi Obayashi (Tohoku University, Japan); 12 Predicting gene function using omics data: from data preparation to data integration, Weidong Tian, Xinran Dong, Yuanpeng Zhou, Ren Ren (Fudan University, China); 13 Protein function prediction using protein-protein interaction networks, Hon Nian Chua, Guimei Liu, Limsoon Wong (Nat. University of Singapore, Singapore); 14 KEGG and GenomeNet resources for predicting protein function from omics data including KEGG PLANT Resource, Toshiaki Tokimatsu, Masaaki Kotera, Susumu Goto, Minoru Kanehisa (Kyoto University, Japan); 15 Towards elucidation of the Escherichia coli K-12 unknowneome, Yukako Tohsato, Natsuko Yamamoto, Toru Nakayashiki, Rikiya Takeuchi, Barry L. Wanner, Hirotada Mori (Nara Institute of Science and Technology, Japan); Index
