ENTPRISE is an algorithm for predicting human disease-associated amino acid mutations from sequence entropy and predicted protein structures
This server will fast retrieve pre-computed mutation scores (average exome coverage is 90%, score >0.45 is disease-associated).
Notice: This server is freely available to all academic and non-commercial users.
Commercial users – to use this server, or request a download of all pre-computed scores, please send an email to Dr. Jeffrey Skolnick: skolnick@gatech.edu.
Citation: Zhou, H, Gao M, Skolnick J. 2016. ENTPRISE: An Algorithm for Predicting Human Disease-Associated Amino Acid Substitutions from Sequence Entropy and Predicted Protein Structures. PLOS ONE. 11(3):e0150965. PDF
Benchmarking Results:
Comparison of methods on a balanced data set PredictSNP-filter
Download ENTPRISE benchmark result on PredictSNP-filter set
Download ENTPRISE benchmark result on 1k-Genome set
Download ENTPRISE benchmark result on VariSNP set
Training & test datasets:
Download ENTPRISE-TR benchmarking training set
Download ENTPRISE-TR benchmarking training set with duplicated samples
Download ENTPRISE-TE benchmarking test set
Download ENTPRISE-balance benchmarking test set (a subset of ENTPRISE-TE)
Download protein sequences for ENTPRISE dataset
Download 1k-Genome test set
Download protein sequences for 1k-Genome test set
Predictions for proteins of human transcription machinery:
Download “hot” spot predictions
Please send questions to Dr. Hongyi Zhou: hzhou3@gatech.edu.