Back to Search
Start Over
A comparative study on filtering protein secondary structure prediction
- Source :
- IEEE/ACM Transactions on Computational Biology and Bioinformatics, IEEE/ACM Trans.Comput.BioL.Bioinf.
- Publication Year :
- 2012
-
Abstract
- Filtering of Protein Secondary Structure Prediction (PSSP) aims to provide physicochemically realistic results, while it usually improves the predictive performance. We performed a comparative study on this challenging problem, utilizing both machine learning techniques and empirical rules and we found that combinations of the two lead to the highest improvement. © 2006 IEEE. 9 3 731 739 Cited By :7
- Subjects :
- Computer science
Bioinformatics
Filtering theory
Machine learning
computer.software_genre
Protein secondary structure prediction
chemistry
protein database
Protein Structure, Secondary
Structural bioinformatics
Artificial Intelligence
Genetics
Humans
Animals
animal
human
Databases, Protein
bidirectional recurrent neural networks
Machine-learning
comparative study
Learning systems
business.industry
Applied Mathematics
article
Bidirectional recurrent neural networks
Proteins
structural bioinformatics
filtering
artificial intelligence
Comparative studies
machine learning
Recurrent neural networks
Artificial intelligence
protein secondary structure
business
protein
Machine learning techniques
computer
Filtration
Biotechnology
Predictive performance
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- IEEE/ACM Transactions on Computational Biology and Bioinformatics, IEEE/ACM Trans.Comput.BioL.Bioinf.
- Accession number :
- edsair.doi.dedup.....7fd69829e20cc70af2c85faec0cad452