Protein Function Prediction for Omics Era /

Protein Function Prediction for Omics Era /

Detalles Bibliográficos
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Kihara, Daisuke. (Editor )
Formato: eBook
Lenguaje:English
Publicado: Dordrecht : Springer Netherlands : Imprint: Springer, 2011.
Edición:1st ed. 2011.
Materias:
Medicine.
Biochemistry.
Proteomics.
Bioinformatics.
Biotechnology.
Biomedicine, general.
Biochemistry, general.
Tabla de Contenidos:
  • Preface
  • 1 Computational protein function prediction: framework and challenges, Meghana Chitale, Daisuke Kihara
  • 2 Enhanced sequence-based function prediction methods and application to functional similarity networks, Meghana Chitale, Daisuke Kihara
  • 3 Gene cluster prediction and its application to genome annotation, Vikas Rao Pejaver, Heewook Lee, Sun Kim
  • 4 Functional inference in microbial genomics based on large-scale comparative analysis, Ikuo Uchiyama
  • 5 Predicting protein functional sites with phylogenetic motifs: Past, present and beyond, Dennis R. Livesay, Dukka Bahadur K.C., David La
  • 6 Exploiting protein structures to predict protein functions, Alison Cuff, Oliver Redfern, Benoit Dessailly, Christine Orengo
  • 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
  • 8 Protein binding ligand prediction using moment-based methods, Rayan Chikhi, Lee Sael, Daisuke Kihara
  • 9 Computational methods for predicting DNA-binding sites at a genome scale, Shandar Ahmad
  • 10 Electrostatic properties for protein functional site annotation, Joslynn S. Lee, Mary Jo Ondrechen
  • 11 Function prediction of genes: from molecular function to cellular function, Kengo Kinoshita, Takeshi Obayashi
  • 12 Predicting gene function using omics data: from data preparation to data integration, Weidong Tian, Xinran Dong, Yuanpeng Zhou, Ren Ren
  • 13 Protein function prediction using protein-protein interaction networks, Hon Nian Chua, Guimei Liu, Limsoon Wong
  • 14 KEGG and GenomeNet resources for predicting protein function from omics data including KEGG PLANT Resource, Toshiaki Tokimatsu, Masaaki Kotera, Susumu Goto, Minoru Kanehisa
  • 15 Towards elucidation of the Escherichia coli K-12 unknowneome, Yukako Tohsato, Natsuko Yamamoto, Toru Nakayashiki, Rikiya Takeuchi, Barry L. Wanner, Hirotada Mori
  • Index.

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