Predicting Fold Novelty Based on ProtoNet Hierarchical Classification
Structural genomics projects aim to solve a large number of protein structures with the ultimate objective of representing the entire protein space. The computational challenge is to identify and prioritize a small set of proteins with new, currently unknown, superfamilies or folds. We develop a met...
Saved in:
Main Authors: | KIFER, Ilona, SASSON, Ori, Linial, Michal |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2005
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/86 http://dx.doi.org/10.1093/bioinformatics/bti135 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
Protonet: Hierarchical Classification of the Protein Space
by: SASSON, Ori, et al.
Published: (2003) -
Protonet 4.0: A Hierarchical Classification of One Million Protein Sequences
by: KAPLAN, Noam, et al.
Published: (2005) -
Protarget: Automatic Prediction of Protein Structure Novelty
by: SASSON, Ori, et al.
Published: (2005) -
Protein Clustering and Classification
by: SASSON, Ori, et al.
Published: (2004) -
Functional Annotation Prediction: All for One and One for All
by: SASSON, Ori, et al.
Published: (2006)