Name
Title | ||
|---|---|---|
On The Critical Review Of Five Machine Learning-Based Algorithms For Predicting Protein Stability Changes Upon Mutation |
Abstract | ||
|---|---|---|
A review, recently published in this journal by Fang (2019), showed that methods trained for the prediction of protein stability changes upon mutation have a very critical bias: they neglect that a protein variation (A-> B) and its reverse (B-> A) must have the opposite value of the free energy difference (Delta Delta G(AB) = - Delta Delta G(BA)). In this letter, we complement the Fang's paper presenting a more general view of the problem. In particular, a machine learning-based method, published in 2015 (INPS), addressed the bias issue directly. We include the analysis of the missing method, showing that INPS is nearly insensitive to the addressed problem. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1093/bib/bbz168 | BRIEFINGS IN BIOINFORMATICS |
DocType | Volume | Issue |
Journal | 22 | 1 |
ISSN | Citations | PageRank |
1467-5463 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Castrense Savojardo | 1 | 99 | 10.27 |
| Pier Luigi Martelli | 2 | 375 | 29.49 |
| Rita Casadio | 3 | 1032 | 108.10 |
| Piero Fariselli | 4 | 851 | 96.03 |