| 書(shū)目名稱(chēng) | Protein Homology Detection Through Alignment of Markov Random Fields |
| 副標(biāo)題 | Using MRFalign |
| 編輯 | Jinbo Xu,Sheng Wang,Jianzhu Ma |
| 視頻video | http://file.papertrans.cn/762/761687/761687.mp4 |
| 概述 | Surveys the key topics to aid the reader in quickly learning about this area.Presents a novel technique for protein homology search, preparing the reader for future developments.Provides an introducti |
| 叢書(shū)名稱(chēng) | SpringerBriefs in Computer Science |
| 圖書(shū)封面 |  |
| 描述 | 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. |
| 出版日期 | Book 2015 |
| 關(guān)鍵詞 | Hidden Markov Model; Long-Range Residue Interaction; Markov Random Fields; Position-Specific Scoring Ma |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-14914-1 |
| isbn_softcover | 978-3-319-14913-4 |
| isbn_ebook | 978-3-319-14914-1Series ISSN 2191-5768 Series E-ISSN 2191-5776 |
| issn_series | 2191-5768 |
| copyright | The Author(s) 2015 |
|Archiver|手機(jī)版|小黑屋|
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