Name
Title | ||
|---|---|---|
In silico design of MHC class I high binding affinity peptides through motifs activation map. |
Abstract | ||
|---|---|---|
We design the MAM network to extract the motifs from MHC-peptides binding through prediction, which are proved to generate the peptides with high binding affinity successfully. The new peptides preserve the motifs but vary in sequences. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1186/s12859-018-2517-3 | BMC Bioinformatics |
Keywords | Field | DocType |
Convolutional neural network,Design new peptides with high binding affinity to MHC-I molecule,Motifs activation map | Drug discovery,Biology,Ligand (biochemistry),Amino acid,MHC class I,Major histocompatibility complex,Computational biology,Genetics,Affinities,DNA microarray,In silico | Journal |
Volume | Issue | ISSN |
19 | Suppl 19 | 1471-2105 |
Citations | PageRank | References |
0 | 0.34 | 17 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhoujian Xiao | 1 | 0 | 0.34 |
| Yu-Wei Zhang | 2 | 40 | 6.19 |
| Runsheng Yu | 3 | 0 | 0.34 |
| Yin Chen | 4 | 16 | 7.04 |
| Xiaosen Jiang | 5 | 0 | 0.34 |
| Ziwei Wang | 6 | 0 | 0.34 |
| Shuai Cheng Li | 7 | 184 | 30.25 |