Predicting Presynaptic and Postsynaptic Neurotoxins by Developing Feature Selection Technique
Published 2017 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Predicting Presynaptic and Postsynaptic Neurotoxins by Developing Feature Selection Technique
Authors
Keywords
-
Journal
Biomed Research International
Volume 2017, Issue -, Pages 1-4
Publisher
Hindawi Limited
Online
2017-02-13
DOI
10.1155/2017/3267325
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- LBSizeCleav: improved support vector machine (SVM)-based prediction of Dicer cleavage sites using loop/bulge length
- (2016) Yu Bao et al. BMC BIOINFORMATICS
- DeepQA: improving the estimation of single protein model quality with deep belief networks
- (2016) Renzhi Cao et al. BMC BIOINFORMATICS
- Prediction of antiepileptic drug treatment outcomes using machine learning
- (2016) Sinisa Colic et al. Journal of Neural Engineering
- Identification of immunoglobulins using Chou's pseudo amino acid composition with feature selection technique
- (2016) Hua Tang et al. Molecular BioSystems
- iHyd-PseCp: Identify hydroxyproline and hydroxylysine in proteins by incorporating sequence-coupled effects into general PseAAC
- (2016) Wang-Ren Qiu et al. Oncotarget
- iOri-Human: identify human origin of replication by incorporating dinucleotide physicochemical properties into pseudo nucleotide composition
- (2016) Chang-Jian Zhang et al. Oncotarget
- Identification of apolipoprotein using feature selection technique
- (2016) Hua Tang et al. Scientific Reports
- Prediction of presynaptic and postsynaptic neurotoxins by bi-layer support vector machine with multi-features
- (2016) Song Chaohong African Journal of Microbiology Research
- Prediction of protein structural class using tri-gram probabilities of position-specific scoring matrix and recursive feature elimination
- (2015) Peiying Tao et al. AMINO ACIDS
- Prediction of protein subcellular localization by incorporating multiobjective PSO-based feature subset selection into the general form of Chou’s PseAAC
- (2015) Monalisa Mandal et al. MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING
- PECM: Prediction of extracellular matrix proteins using the concept of Chou’s pseudo amino acid composition
- (2014) Jian Zhang et al. JOURNAL OF THEORETICAL BIOLOGY
- iPro54-PseKNC: a sequence-based predictor for identifying sigma-54 promoters in prokaryote with pseudo k-tuple nucleotide composition
- (2014) Hao Lin et al. NUCLEIC ACIDS RESEARCH
- Efficient Feature Selection and Classification of Protein Sequence Data in Bioinformatics
- (2014) Muhammad Javed Iqbal et al. TheScientificWorldJOURNAL
- CD-HIT: accelerated for clustering the next-generation sequencing data
- (2012) Limin Fu et al. BIOINFORMATICS
- Hybrid biogeography based simultaneous feature selection and MHC class I peptide binding prediction using support vector machines and random forests
- (2012) Atulji Srivastava et al. JOURNAL OF IMMUNOLOGICAL METHODS
- Using Feature Selection Technique for Drug-Target Interaction Networks Prediction
- (2011) W. Yu et al. CURRENT MEDICINAL CHEMISTRY
- Postsynaptic mechanisms of excitotoxicity: Involvement of postsynaptic density proteins, radicals, and oxidant molecules
- (2008) J.P. Forder et al. NEUROSCIENCE
- Prediction of presynaptic and postsynaptic neurotoxins by the increment of diversity
- (2008) Lei Yang et al. TOXICOLOGY IN VITRO
Create your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create NowBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started