Classifying Multifunctional Enzymes by Incorporating Three Different Models into Chou’s General Pseudo Amino Acid Composition

MultiP-SChlo: multi-label protein subchloroplast localization prediction with Chou’s pseudo amino acid composition and a novel multi-label classifier

(2015) Xiao Wang et al.   BIOINFORMATICS

iEnhancer-2L: a two-layer predictor for identifying enhancers and their strength by pseudok-tuple nucleotide composition

(2015) Bin Liu et al.   BIOINFORMATICS

iDrug-Target: predicting the interactions between drug compounds and target proteins in cellular networking via benchmark dataset optimization approach

(2015) Xuan Xiao et al.   JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS

Predicting the Functional Types of Singleplex and Multiplex Eukaryotic Membrane Proteins via Different Models of Chou’s Pseudo Amino Acid Compositions

(2015) Hong-Liang Zou et al.   JOURNAL OF MEMBRANE BIOLOGY

Discrimination of acidic and alkaline enzyme using Chou’s pseudo amino acid composition in conjunction with probabilistic neural network model

(2015) Zaheer Ullah Khan et al.   JOURNAL OF THEORETICAL BIOLOGY

iPPI-Esml: An ensemble classifier for identifying the interactions of proteins by incorporating their physicochemical properties and wavelet transforms into PseAAC

(2015) Jianhua Jia et al.   JOURNAL OF THEORETICAL BIOLOGY

Pse-in-One: a web server for generating various modes of pseudo components of DNA, RNA, and protein sequences

(2015) Bin Liu et al.   NUCLEIC ACIDS RESEARCH

Simultaneously Identify Three Different Attributes of Proteins by Fusing their Three Different Modes of Chou's Pseudo Amino Acid Compositions

(2015) Chao Huang et al.   PROTEIN AND PEPTIDE LETTERS

PseAAC-General: Fast Building Various Modes of General Form of Chou’s Pseudo-Amino Acid Composition for Large-Scale Protein Datasets

(2014) Pufeng Du et al.   INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES

iRSpot-TNCPseAAC: Identify Recombination Spots with Trinucleotide Composition and Pseudo Amino Acid Components

(2014) Wang-Ren Qiu et al.   INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES

iNitro-Tyr: Prediction of Nitrotyrosine Sites in Proteins with General Pseudo Amino Acid Composition

(2014) Yan Xu et al.   PLoS One

iCTX-Type: A Sequence-Based Predictor for Identifying the Types of Conotoxins in Targeting Ion Channels

(2014) Hui Ding et al.   Biomed Research International

iAMP-2L: A two-level multi-label classifier for identifying antimicrobial peptides and their functional types

(2013) Xuan Xiao et al.   ANALYTICAL BIOCHEMISTRY

propy: a tool to generate various modes of Chou’s PseAAC

(2013) Dong-Sheng Cao et al.   BIOINFORMATICS

BinMemPredict: a Web Server and Software for Predicting Membrane Protein Types

(2013) Quan Zou et al.   Current Proteomics

A Multilabel Model Based on Chou’s Pseudo–Amino Acid Composition for Identifying Membrane Proteins with Both Single and Multiple Functional Types

(2013) Chao Huang et al.   JOURNAL OF MEMBRANE BIOLOGY

Predicting protein subchloroplast locations with both single and multiple sites via three different modes of Chou's pseudo amino acid compositions

(2013) Chao Huang et al.   JOURNAL OF THEORETICAL BIOLOGY

iLoc-Animal: a multi-label learning classifier for predicting subcellular localization of animal proteins

(2013) Wei-Zhong Lin et al.   Molecular BioSystems

iSNO-PseAAC: Predict Cysteine S-Nitrosylation Sites in Proteins by Incorporating Position Specific Amino Acid Propensity into Pseudo Amino Acid Composition

(2013) Yan Xu et al.   PLoS One

PseAAC-Builder: A cross-platform stand-alone program for generating various special Chou’s pseudo-amino acid compositions

(2012) Pufeng Du et al.   ANALYTICAL BIOCHEMISTRY

iNR-PhysChem: A Sequence-Based Predictor for Identifying Nuclear Receptors and Their Subfamilies via Physical-Chemical Property Matrix

(2012) Xuan Xiao et al.   PLoS One

A Multi-Label Predictor for Identifying the Subcellular Locations of Singleplex and Multiplex Eukaryotic Proteins

(2012) Xiao Wang et al.   PLoS One

iNuc-PhysChem: A Sequence-Based Predictor for Identifying Nucleosomes via Physicochemical Properties

(2012) Wei Chen et al.   PLoS One

iLoc-Gpos: A Multi-Layer Classifier for Predicting the Subcellular Localization of Singleplex and Multiplex Gram-Positive Bacterial Proteins

(2012) Zhi-Cheng Wu et al.   PROTEIN AND PEPTIDE LETTERS

Prediction of membrane proteins using split amino acid and ensemble classification

(2011) Maqsood Hayat et al.   AMINO ACIDS

Multi-kernel transfer learning based on Chou's PseAAC formulation for protein submitochondria localization

(2011) Suyu Mei   JOURNAL OF THEORETICAL BIOLOGY

iDNA-Prot: Identification of DNA Binding Proteins Using Random Forest with Grey Model

(2011) Wei-Zhong Lin et al.   PLoS One

CD-HIT Suite: a web server for clustering and comparing biological sequences

(2010) Ying Huang et al.   BIOINFORMATICS

Some remarks on protein attribute prediction and pseudo amino acid composition

(2010) Kuo-Chen Chou   JOURNAL OF THEORETICAL BIOLOGY

A New Method for Predicting the Subcellular Localization of Eukaryotic Proteins with Both Single and Multiple Sites: Euk-mPLoc 2.0

(2010) Kuo-Chen Chou et al.   PLoS One

Using the concept of Chou's pseudo amino acid composition for risk type prediction of human papillomaviruses

(2009) Maryam Esmaeili et al.   JOURNAL OF THEORETICAL BIOLOGY

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

Gpos-mPLoc: A Top-Down Approach to Improve the Quality of Predicting Subcellular Localization of Gram-Positive Bacterial Proteins

(2009) Hong-Bin Shen 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

PseAAC: A flexible web server for generating various kinds of protein pseudo amino acid composition

(2007) Hong-Bin Shen et al.   ANALYTICAL BIOCHEMISTRY

Predicting enzyme family class in a hybridization space

(2004) Kuo-Chen Chou et al.   PROTEIN SCIENCE