| nr |
titel |
auteur |
tijdschrift |
jaar |
jaarg. |
afl. |
pagina('s) |
type |
| 1 |
An integrated approach to infer dynamic protein-gene interactions – A case study of the human P53 protein
|
Wang, Junbai
|
|
2016
|
110 |
C |
p. 3-13
|
artikel
|
| 2 |
Boosting compound-protein interaction prediction by deep learning
|
Tian, Kai
|
|
2016
|
110 |
C |
p. 64-72
|
artikel
|
| 3 |
Conservation of hot regions in protein–protein interaction in evolution
|
Hu, Jing
|
|
2016
|
110 |
C |
p. 73-80
|
artikel
|
| 4 |
Cover 1
|
|
|
2016
|
110 |
C |
p. OFC
|
artikel
|
| 5 |
Editorial
|
Liao, Li
|
|
2016
|
110 |
C |
p. 1-2
|
artikel
|
| 6 |
Editorial Board
|
|
|
2016
|
110 |
C |
p. IFC
|
artikel
|
| 7 |
Essential protein discovery based on a combination of modularity and conservatism
|
Zhao, Bihai
|
|
2016
|
110 |
C |
p. 54-63
|
artikel
|
| 8 |
Identifying protein complexes based on brainstorming strategy
|
Shen, Xianjun
|
|
2016
|
110 |
C |
p. 44-53
|
artikel
|
| 9 |
Improving drug safety: From adverse drug reaction knowledge discovery to clinical implementation
|
Tan, Yuxiang
|
|
2016
|
110 |
C |
p. 14-25
|
artikel
|
| 10 |
Improving hot region prediction by parameter optimization of density clustering in PPI
|
Hu, Jing
|
|
2016
|
110 |
C |
p. 35-43
|
artikel
|
| 11 |
Neighbor affinity based algorithm for discovering temporal protein complex from dynamic PPI network
|
Shen, Xianjun
|
|
2016
|
110 |
C |
p. 90-96
|
artikel
|
| 12 |
Prediction of Protein–Protein Interaction via co-occurring Aligned Pattern Clusters
|
Sze-To, Antonio
|
|
2016
|
110 |
C |
p. 26-34
|
artikel
|
| 13 |
Prediction of residue-residue contact matrix for protein-protein interaction with Fisher score features and deep learning
|
Du, Tianchuan
|
|
2016
|
110 |
C |
p. 97-105
|
artikel
|
| 14 |
Protein interaction network (PIN)-based breast cancer subsystem identification and activation measurement for prognostic modeling
|
Lim, S.
|
|
2016
|
110 |
C |
p. 81-89
|
artikel
|
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