Predicting functional family of novel enzymes irrespective of sequence similarity: A statistical learning approach

Predicting functional family of novel enzymes irrespective of sequence similarity: A statistical learning approach

10.1093/nar/gkh984

Saved in:

Bibliographic Details
Main Authors:	Han, L.Y., Cai, C.Z., Ji, Z.L., Cao, Z.W., Cui, J., Chen, Y.Z.
Other Authors:	COMPUTATIONAL SCIENCE
Format:	Article
Published:	2014
Online Access:	http://scholarbank.nus.edu.sg/handle/10635/53099
Tags:	Add Tag No Tags, Be the first to tag this record!
Institution:	National University of Singapore

Similar Items

Prediction of functional class of novel viral proteins by a statistical learning method irrespective of sequence similarity
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)

Enzyme Family Classification by Support Vector Machines
by: Cai, C.Z., et al.
Published: (2014)

SVM-prot 2016: A web-server for machine learning prediction of protein functional families from sequence irrespective of similarity
by: Li Y.H., et al.
Published: (2018)

Prediction of transporter family from protein sequence by support vector machine approach
by: Lin, H.H., et al.
Published: (2014)

Advances in exploration of machine learning methods for predicting functional class and interaction profiles of proteins and peptides irrespective of sequence homology
by: Cui, J., et al.
Published: (2014)

Prediction of functional class of the SARS coronavirus proteins by a statistical learning method
by: Cai, C.Z., et al.
Published: (2014)

SVM-Prot: Web-based support vector machine software for functional classification of a protein from its primary sequence
by: Cai, C.Z., et al.
Published: (2014)

Recent progresses in the application of machine learning approach for predicting protein functional class independent of sequence similarity.
by: Han, L., et al.
Published: (2014)

Prediction of RNA-binding proteins from primary sequence by a support vector machine approach
by: Han, L.Y., et al.
Published: (2014)

MHC-BPS: MHC-binder prediction server for identifying peptides of flexible lengths from sequence-derived physicochemical properties
by: Cui, J., et al.
Published: (2014)

Prediction of transmembrane proteins from their primary sequence by support vector machine approach
by: Cai, C.Z., et al.
Published: (2014)

Computer prediction of allergen proteins from sequence-derived protein structural and physicochemical properties
by: Cui, J., et al.
Published: (2014)

Therapeutic targets: Progress of their exploration and investigation of their characteristics
by: Zheng, C.J., et al.
Published: (2014)

Increasing the odds of drug hit identification by screening against receptor homologs?
by: Ji, Z.L., et al.
Published: (2014)

Statistics with estimated parameters
by: Yang, Z.L., et al.
Published: (2014)

Prediction of compounds with specific pharmacodynamic, pharmacokinetic or toxicological property by statistical learning methods
by: Yap, C.W., et al.
Published: (2014)

Computer prediction of drug resistance mutations in proteins
by: Cao, Z.W., et al.
Published: (2014)

Prediction of genotoxicity of chemical compounds by statistical learning methods
by: Li, H., et al.
Published: (2014)

Internet resources for proteins associated with drug therapeutic effects, adverse reactions and ADME
by: Ji, Z.L., et al.
Published: (2014)

A computer method for validating traditional Chinese medicine herbal prescriptions
by: Wang, J.F., et al.
Published: (2014)

Prediction of the functional class of metal-binding proteins from sequence derived physicochemical properties by support vector machine approach
by: Lin, H.H., et al.
Published: (2014)

Computer prediction of cardiovascular and hematological agents by statistical learning methods
by: Chen, X., 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)

Effect of selection of molecular descriptors on the prediction of blood-brain barrier penetrating and nonpenetrating agents by statistical learning methods
by: Li, H., et al.
Published: (2014)

TTD: Therapeutic Target Database
by: Chen, X., et al.
Published: (2014)

Hydrogen-bond disruption probability in proteins by a modified self-consistent harmonic approach
by: Cao, Z.W., et al.
Published: (2014)

Angiotensin-converting enzyme inhibition after myocardial infarction
by: Zhu, Y.Z., et al.
Published: (2012)

Drug ADME-associated protein database as a resource for facilitating pharmacogenomics research
by: Zheng, C.J., et al.
Published: (2014)

Drug adverse reaction target database (DART): Proteins related to adverse drug reactions
by: Ji, Z.L., et al.
Published: (2014)

In silico search of putative adverse drug reaction related proteins as a potential tool for facilitating drug adverse effect prediction
by: Ji, Z.L., et al.
Published: (2014)

Statistical learning approach for predicting specific pharmacodynamic, pharmacokinetic, or toxicological properties of pharmaceutical agents
by: Li, H., et al.
Published: (2014)

A support vector machines approach for virtual screening of active compounds of single and multiple mechanisms from large libraries at an improved hit-rate and enrichment factor
by: Han, L.Y., et al.
Published: (2014)

Protein function classification via support vector machine approach
by: Cai, C.Z., et al.
Published: (2014)

Indexing similar DNA sequences
by: Huang, S., et al.
Published: (2013)

PROFEAT: A web server for computing structural and physicochemical features of proteins and peptides from amino acid sequence
by: Li, Z.R., et al.
Published: (2014)

Can an optimization/scoring procedure in ligand-protein docking be employed to probe drug-resistant mutations in proteins?
by: Chen, Y.Z, et al.
Published: (2014)

Traditional Chinese medicine information database
by: Ji, Z.L., et al.
Published: (2014)

Quantitative structure-pharmacokinetic relationships for drug clearance by using statistical learning methods
by: Yap, C.W., et al.
Published: (2014)