Protein Homology Detection Through Alignment of Markov Random Fields (Record no. 57687)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02682nam a22005415i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-3-319-14914-1 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20200421112226.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 150122s2015 gw | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9783319149141 |
| -- | 978-3-319-14914-1 |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 570.285 |
| 100 1# - AUTHOR NAME | |
| Author | Xu, Jinbo. |
| 245 10 - TITLE STATEMENT | |
| Title | Protein Homology Detection Through Alignment of Markov Random Fields |
| Sub Title | Using MRFalign / |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | VIII, 51 p. 13 illus., 1 illus. in color. |
| 490 1# - SERIES STATEMENT | |
| Series statement | SpringerBriefs in Computer Science, |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Remark 2 | Introduction -- Method -- Software -- Experiments and Results -- Conclusion. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | This work covers sequence-based protein homology detection, a fundamental and challenging bioinformatics problem with a variety of real-world applications. The text first surveys a few popular homology detection methods, such as Position-Specific Scoring Matrix (PSSM) and Hidden Markov Model (HMM) based methods, and then describes a novel Markov Random Fields (MRF) based method developed by the authors. MRF-based methods are much more sensitive than HMM- and PSSM-based methods for remote homolog detection and fold recognition, as MRFs can model long-range residue-residue interaction. The text also describes the installation, usage and result interpretation of programs implementing the MRF-based method. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Wang, Sheng. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Ma, Jianzhu. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | http://dx.doi.org/10.1007/978-3-319-14914-1 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | Cham : |
| -- | Springer International Publishing : |
| -- | Imprint: Springer, |
| -- | 2015. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | c |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
| -- | cr |
| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
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| -- | rda |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer science. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Mathematical statistics. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Bioinformatics. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Statistics. |
| 650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer Science. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computational Biology/Bioinformatics. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Probability and Statistics in Computer Science. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Bioinformatics. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Statistics for Life Sciences, Medicine, Health Sciences. |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| -- | 2191-5768 |
| 912 ## - | |
| -- | ZDB-2-SCS |
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