Book chapter
Algorithmic Frameworks for Protein Disulfide Connectivity Determination
Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics, pp.171-203
John Wiley & Sons, Inc
10/28/2013
DOI: 10.1002/9781118567869.ch9
Abstract
This chapter presents a comprehensive introduction to the different algorithmic frameworks available at the state of the art for the determination of disulfide bonds by utilizing data from either protein sequences or tandem mass spectrometry (MS). For the former class of techniques, the authors identify the different problem formulations, features, and solution frameworks. They also review a number of techniques in the area and show how the aforementioned issues are addressed in them. For MS‐based methods, our narrative focuses primarily on two methods that the authors developed to provide insight into the key challenges and the anatomy of possible solutions and the underlying algorithmic frameworks. In the chapter, the authors present results from the two methods MS2DB and MS2DB+. The underlying MS/MS data were obtained using a capillary liquid chromatography system coupled with a Thermo‐Fisher LCQ ion trap mass spectrometer LC/ESI‐MS/MS system.
Details
- Title: Subtitle
- Algorithmic Frameworks for Protein Disulfide Connectivity Determination
- Creators
- Rahul SinghWilliam MuradTimothy Lee
- Contributors
- Yi Pan (Editor) - Georgia State UniversityJianxin Wang (Editor) - Central South University, ChinaMin Li (Editor) - Central South University, China
- Resource Type
- Book chapter
- Publication Details
- Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics, pp.171-203
- Publisher
- John Wiley & Sons, Inc; Hoboken, NJ, USA
- DOI
- 10.1002/9781118567869.ch9
- Number of pages
- 33
- Language
- English
- Date published
- 10/28/2013
- Academic Unit
- Computer Science
- Record Identifier
- 9984446421902771
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