Computational prediction of lysine acetylation proteome-wide.
Clicks: 555
ID: 51433
2013
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Steady Performance
78.2
/100
555 views
382 readers
Trending
AI Quality Assessment
Not analyzed
Readership in this journal
SteadyRanked #1 of 139 articles by views in methods in molecular biology (clifton, nj)
Most read
Least read
Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 139 in total.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
Several studies have contributed to our knowledge of the enzymology underlying acetylation, including focused efforts to understand the molecular mechanism of substrate recognition by several acetyltransferases; however, conventional experiments to determine intrinsic features of substrate site specificity have proven challenging. In this chapter, I describe in detail a computational method that involves clustering analysis of protein sequences to predict protein acetylation based on the sequence characteristics of acetylated lysines within histones. This method illustrates that sequence composition has predictive power on datasets of acetylation marks, and can be used to predict other posttranslational modifications such as methylation and phosphorylation. Later in this chapter, other recent methods to predict lysine acetylation are described and together, these approaches combined with more traditional experimental methods, can be useful for identifying acetylated substrates proteome-wide.
| Reference Key |
basu2013computationalmethods
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | Basu, Amrita; |
| Journal | methods in molecular biology (clifton, nj) |
| Year | 2013 |
| DOI |
10.1007/978-1-62703-305-3_10
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.