Predicting protein crystallization using a simple scoring card method
Many computational methods have been developed to predict protein crystallization. Most methods use amino acid and dipeptide compositions as part of the informative features. To advance the prediction accuracy, the support vector machine (SVM) based classifiers and ensemble approaches were effective...
Saved in:
Main Authors: | Watshara Shoombuatong, Hui Ling Huang, Jeerayut Chaijaruwanich, Phasit Charoenkwan, Hua Chin Lee, Shinn Ying Ho |
---|---|
Format: | Conference Proceeding |
Published: |
2018
|
Online Access: | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84885053814&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/47580 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Chiang Mai University |
Similar Items
-
Predicting protein crystallization using a simple scoring card method
by: Watshara Shoombuatong, et al.
Published: (2018) -
SCMCRYS: Predicting Protein Crystallization Using an Ensemble Scoring Card Method with Estimating Propensity Scores of P-Collocated Amino Acid Pairs
by: Phasit Charoenkwan, et al.
Published: (2018) -
SCMCRYS: Predicting Protein Crystallization Using an Ensemble Scoring Card Method with Estimating Propensity Scores of P-Collocated Amino Acid Pairs
by: Phasit Charoenkwan, et al.
Published: (2018) -
iAMY-SCM: Improved prediction and analysis of amyloid proteins using a scoring card method with propensity scores of dipeptides
by: Phasit Charoenkwan, et al.
Published: (2020) -
iUmami-SCM: A Novel Sequence-Based Predictor for Prediction and Analysis of Umami Peptides Using a Scoring Card Method with Propensity Scores of Dipeptides
by: Phasit Charoenkwan, et al.
Published: (2020)