Protein Function Prediction for Omics Era (Record no. 109387)
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| 000 -LEADER | |
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| fixed length control field | 04698nam a22004935i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-94-007-0881-5 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | DE-He213 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20140220083831.0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
| fixed length control field | cr nn 008mamaa |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 110418s2011 ne | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9789400708815 |
| -- | 978-94-007-0881-5 |
| 024 7# - OTHER STANDARD IDENTIFIER | |
| Standard number or code | 10.1007/978-94-007-0881-5 |
| Source of number or code | doi |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
| Classification number | R-RZ |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | MBGR |
| Source | bicssc |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | MED000000 |
| Source | bisacsh |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 610 |
| Edition number | 23 |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Kihara, Daisuke. |
| Relator term | editor. |
| 245 10 - TITLE STATEMENT | |
| Title | Protein Function Prediction for Omics Era |
| Medium | [electronic resource] / |
| Statement of responsibility, etc | edited by Daisuke Kihara. |
| 264 #1 - | |
| -- | Dordrecht : |
| -- | Springer Netherlands, |
| -- | 2011. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | XIII, 310p. |
| Other physical details | online resource. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | c |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
| -- | cr |
| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
| -- | |
| -- | rda |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Formatted contents note | 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. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | 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 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Medicine. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Biotechnology. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Biochemistry. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Proteomics. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Bioinformatics. |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Biomedicine. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Biomedicine general. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Biochemistry, general. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Proteomics. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Bioinformatics. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Biotechnology. |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | SpringerLink (Online service) |
| 773 0# - HOST ITEM ENTRY | |
| Title | Springer eBooks |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Display text | Printed edition: |
| International Standard Book Number | 9789400708808 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | http://dx.doi.org/10.1007/978-94-007-0881-5 |
| 912 ## - | |
| -- | ZDB-2-SBL |
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