Prediction of functional class of novel viral proteins by a statistical learning method irrespective of sequence similarity
10.1016/j.virol.2004.10.020
Saved in:
Main Authors: | Han, L.Y., Cai, C.Z., Ji, Z.L., Chen, Y.Z. |
---|---|
Other Authors: | COMPUTATIONAL SCIENCE |
Format: | Article |
Published: |
2014
|
Subjects: | |
Online Access: | http://scholarbank.nus.edu.sg/handle/10635/104845 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | National University of Singapore |
Similar Items
-
Predicting functional family of novel enzymes irrespective of sequence similarity: A statistical learning approach
by: Han, L.Y., et al.
Published: (2014) -
Prediction of the functional class of lipid binding proteins from sequence-derived properties irrespective of sequence similarity
by: Lin, H.H., et al.
Published: (2014) -
Prediction of functional class of novel bacterial proteins without the use of sequence similarity by a statistical learning method
by: Cui, J., et al.
Published: (2014) -
Prediction of functional class of novel plant proteins by a statistical learning method
by: Han, L.Y., et al.
Published: (2014) -
Sequential representation of fuzzy similarity relations
by: Tan, S.K., et al.
Published: (2014)