Name
Title | ||
|---|---|---|
Analysis of protein features and machine learning algorithms for prediction of druggable proteins |
Abstract | ||
|---|---|---|
Computational tools have been widely used in drug discovery process since they reduce the time and cost. Prediction of whether a protein is druggable is fundamental and crucial for drug research pipeline. Sequence based protein function prediction plays vital roles in many research areas. Training data, protein features selection and machine learning algorithms are three indispensable elements that drive the successfulness of the models. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/s40484-018-0157-2 | Quantitative Biology |
Keywords | DocType | Volume |
druggable protein,drug target,word2vec,deep learning | Journal | 6 |
Issue | ISSN | Citations |
4 | 2095-4697 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tanlin Sun | 1 | 21 | 1.41 |
| Luhua Lai | 2 | 369 | 33.78 |
| Jianfeng Pei | 3 | 37 | 3.99 |