A Multi-Label Classifier for Predicting the Subcellular Localization of Gram-Negative Bacterial Proteins with Both Single and Multiple Sites
Published 2011 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
A Multi-Label Classifier for Predicting the Subcellular Localization of Gram-Negative Bacterial Proteins with Both Single and Multiple Sites
Authors
Keywords
-
Journal
PLoS One
Volume 6, Issue 6, Pages e20592
Publisher
Public Library of Science (PLoS)
Online
2011-06-18
DOI
10.1371/journal.pone.0020592
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- A novel feature representation method based on Chou's pseudo amino acid composition for protein structural class prediction
- (2010) Sitanshu Sekhar Sahu et al. COMPUTATIONAL BIOLOGY AND CHEMISTRY
- Supersecondary structure prediction using Chou's pseudo amino acid composition
- (2010) Dongsheng Zou et al. JOURNAL OF COMPUTATIONAL CHEMISTRY
- Knowledge-based computational mutagenesis for predicting the disease potential of human non-synonymous single nucleotide polymorphisms
- (2010) Majid Masso et al. JOURNAL OF THEORETICAL BIOLOGY
- Gneg-mPLoc: A top-down strategy to enhance the quality of predicting subcellular localization of Gram-negative bacterial proteins
- (2010) Hong-Bin Shen et al. JOURNAL OF THEORETICAL BIOLOGY
- Some remarks on protein attribute prediction and pseudo amino acid composition
- (2010) Kuo-Chen Chou JOURNAL OF THEORETICAL BIOLOGY
- Plant-mPLoc: A Top-Down Strategy to Augment the Power for Predicting Plant Protein Subcellular Localization
- (2010) Kuo-Chen Chou et al. PLoS One
- Prediction of Protein Subcellular Locations with Feature Selection and Analysis
- (2010) Yudong Cai et al. PROTEIN AND PEPTIDE LETTERS
- Prediction of Cyclin Proteins Using Chous Pseudo Amino Acid Composition
- (2010) Hassan Mohabatkar PROTEIN AND PEPTIDE LETTERS
- Prediction of nuclear receptors with optimal pseudo amino acid composition
- (2009) Qing-Bin Gao et al. ANALYTICAL BIOCHEMISTRY
- SubChlo: Predicting protein subchloroplast locations with pseudo-amino acid composition and the evidence-theoretic K-nearest neighbor (ET-KNN) algorithm
- (2009) Pufeng Du et al. JOURNAL OF THEORETICAL BIOLOGY
- γ-turn types prediction in proteins using the two-stage hybrid neural discriminant model
- (2009) Samad Jahandideh et al. JOURNAL OF THEORETICAL BIOLOGY
- Exploring the Function-Location Nexus: Using Multiple Lines of Evidence in Defining the Subcellular Location of Plant Proteins
- (2009) A. H. Millar et al. PLANT CELL
- Prediction of Cell Wall Lytic Enzymes Using Chous Amphiphilic Pseudo Amino Acid Composition
- (2009) Hui Ding et al. PROTEIN AND PEPTIDE LETTERS
- Prediction of Protein Secondary Structure Content by Using the Concept of Chous Pseudo Amino Acid Composition and Support Vector Machine
- (2009) Chao Chen et al. PROTEIN AND PEPTIDE LETTERS
- Protein function annotation by homology-based inference
- (2009) Yaniv Loewenstein et al. GENOME BIOLOGY
- Prediction of protein structural class using novel evolutionary collocation-based sequence representation
- (2008) Ke Chen et al. JOURNAL OF COMPUTATIONAL CHEMISTRY
- Predicting protein structural class based on multi-features fusion
- (2008) Chao Chen et al. JOURNAL OF THEORETICAL BIOLOGY
- The modified Mahalanobis Discriminant for predicting outer membrane proteins by using Chou's pseudo amino acid composition
- (2008) Hao Lin JOURNAL OF THEORETICAL BIOLOGY
- Cell-PLoc: a package of Web servers for predicting subcellular localization of proteins in various organisms
- (2008) Kuo-Chen Chou et al. Nature Protocols
- Function Prediction of Hypothetical Proteins Without Sequence Similarity to Proteins of Known Function (SUPPLEMENTARY MATERIALS)
- (2008) S. Kannan et al. PROTEIN AND PEPTIDE LETTERS
- Predicting Protein Subcellular Location Using Chous Pseudo Amino Acid Composition and Improved Hybrid Approach
- (2008) Feng-Min Li et al. PROTEIN AND PEPTIDE LETTERS
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started