Literature DB >> 21780006

In silico prediction of post-translational modifications.

Chunmei Liu1, Hui Li.   

Abstract

Methods for predicting protein post-translational modifications have been developed extensively. In this chapter, we review major post-translational modification prediction strategies, with a particular focus on statistical and machine learning approaches. We present the workflow of the methods and summarize the advantages and disadvantages of the methods.

Mesh:

Year:  2011        PMID: 21780006     DOI: 10.1007/978-1-61779-176-5_20

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  2 in total

1.  A homology-based pipeline for global prediction of post-translational modification sites.

Authors:  Xiang Chen; Shao-Ping Shi; Hao-Dong Xu; Sheng-Bao Suo; Jian-Ding Qiu
Journal:  Sci Rep       Date:  2016-05-13       Impact factor: 4.379

2.  Observation selection bias in contact prediction and its implications for structural bioinformatics.

Authors:  G Orlando; D Raimondi; W F Vranken
Journal:  Sci Rep       Date:  2016-11-18       Impact factor: 4.379

  2 in total

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