0.25
0.5
0.75
1.25
1.5
1.75
2
Drug-Target Interaction Prediction Using Semantic Similarity and Edge Partition
Published on Dec 19, 20142267 Views
The ability to integrate a wealth of human-curated knowledge from scientific datasets and ontologies can benefit drug-target interaction prediction. The hypothesis is that similar drugs interact with
Related categories
Chapter list
Drug-Target Interaction Prediction Using Semantic Similarity and Edge Partitioning 00:00
News - September 28th 2014. CLEOPATRA PROJECT*00:15
Pertuzumab and Transtuzumab - 101:02
Pertuzumab and Transtuzumab - 202:06
Drug-Target Interactions02:14
Main Contributions03:14
Agenda03:55
semEP: Semantic Based Edge Partitioning04:04
Semantics Based Edge Partitioning Problem (semEP)04:32
Mapping to Vertex Coloring Graph (VCG) 05:11
The Vertex Coloring Problem06:41
cDensity07:20
The Vertex Coloring Problem08:04
EMPIRICAL EVALUATION08:46
Evaluation on Drug-Target Interactions08:50
semEP Predictions09:31
Evaluation Protocol09:48
State-of-the-art Machine Learning Methods09:59
Experiment I10:43
Evaluation of semEP and State-ofthe-art Machine Learning Methods - 111:00
Evaluation of semEP and State-ofthe-art Machine Learning Methods - 211:10
Overlap of Top10 positive predictions of semEP11:19
Experiment II11:40
STITCH 4.012:02
Validation of Top 5 Drug-Target Interactions (Novel predictions)12:16
Analyzing Top Drug-Target Interactions (Novel predictions for GPCRs)12:21
Conclusions12:35
Future Directions13:09
Thank you!13:40