A comparison and assessment of computational method for identifying recombination hotspots in Saccharomyces cerevisiae

iRNAD: a computational tool for identifying D modification sites in RNA sequence

(2019) Zhao-Chun Xu et al.   BIOINFORMATICS

Incorporating Distance-based Top-n-gram and Random Forest to Identify Electron Transport Proteins

(2019) Xiaoqing Ru et al.   JOURNAL OF PROTEOME RESEARCH

iProEP: A Computational Predictor for Predicting Promoter

(2019) Hong-Yan Lai et al.   Molecular Therapy-Nucleic Acids

DincRNA: a comprehensive web-based bioinformatics toolkit for exploring disease associations and ncRNA function

(2018) Liang Cheng et al.   BIOINFORMATICS

iFeature: a Python package and web server for features extraction and selection from protein and peptide sequences

(2018) Zhen Chen et al.   BIOINFORMATICS

Identifying diseases-related metabolites using random walk

(2018) Yang Hu et al.   BMC BIOINFORMATICS

InfAcrOnt: calculating cross-ontology term similarities using information flow by a random walk

(2018) Liang Cheng et al.   BMC GENOMICS

iProt-Sub: a comprehensive package for accurately mapping and predicting protease-specific substrates and cleavage sites

(2018) Jiangning Song et al.   BRIEFINGS IN BIOINFORMATICS

HBPred: a tool to identify growth hormone-binding proteins

(2018) Hua Tang et al.   International Journal of Biological Sciences

iRSpot-Pse6NC: Identifying recombination spots in Saccharomyces cerevisiae by incorporating hexamer composition into general PseKNC

(2018) Hui Yang et al.   International Journal of Biological Sciences

Machine-Learning-Based Prediction of Cell-Penetrating Peptides and Their Uptake Efficiency with Improved Accuracy

(2018) Balachandran Manavalan et al.   JOURNAL OF PROTEOME RESEARCH

iRSpot-ADPM: Identify recombination spots by incorporating the associated dinucleotide product model into Chou’s pseudo components

(2018) Lichao Zhang et al.   JOURNAL OF THEORETICAL BIOLOGY

PVP-SVM: Sequence-Based Prediction of Phage Virion Proteins Using a Support Vector Machine

(2018) Balachandran Manavalan et al.   Frontiers in Microbiology

A brief survey of machine learning methods in protein sub-Golgi localization

(2018) Wuritu Yang et al.   Current Bioinformatics

iRSpot-DTS: Predict recombination spots by incorporating the dinucleotide-based spare-cross covariance information into Chou's pseudo components

(2018) Shengli Zhang et al.   GENOMICS

Predicting protein structural classes for low-similarity sequences by evaluating different features

(2018) Xiao-Juan Zhu et al.   KNOWLEDGE-BASED SYSTEMS

LncRNA2Target v2.0: a comprehensive database for target genes of lncRNAs in human and mouse

(2018) Liang Cheng et al.   NUCLEIC ACIDS RESEARCH

Identifying sigma70 promoters with novel pseudo nucleotide composition

(2017) Hao Lin et al.   IEEE-ACM Transactions on Computational Biology and Bioinformatics

ProLanGO: Protein Function Prediction Using Neural Machine Translation Based on a Recurrent Neural Network

(2017) Renzhi Cao et al.   MOLECULES

Sequence-based predictive modeling to identify cancerlectins

(2017) Hong-Yan Lai et al.   Oncotarget

iRSpot-EL: identify recombination spots with an ensemble learning approach

(2016) Bin Liu et al.   BIOINFORMATICS

PseKRAAC: a flexible web server for generating pseudo K-tuple reduced amino acids composition

(2016) Yongchun Zuo et al.   BIOINFORMATICS

DeepQA: improving the estimation of single protein model quality with deep belief networks

(2016) Renzhi Cao et al.   BMC BIOINFORMATICS

Combining pseudo dinucleotide composition with the Z curve method to improve the accuracy of predicting DNA elements: a case study in recombination spots

(2016) Chuan Dong et al.   Molecular BioSystems

Identification of immunoglobulins using Chou's pseudo amino acid composition with feature selection technique

(2016) Hua Tang et al.   Molecular BioSystems

A novel features ranking metric with application to scalable visual and bioinformatics data classification

(2016) Quan Zou et al.   NEUROCOMPUTING

iRSpot-DACC: a computational predictor for recombination hot/cold spots identification based on dinucleotide-based auto-cross covariance

(2016) Bingquan Liu et al.   Scientific Reports

Identification of Secretory Proteins inMycobacterium tuberculosisUsing Pseudo Amino Acid Composition

(2016) Huan Yang et al.   Biomed Research International

Using weighted features to predict recombination hotspots in Saccharomyces cerevisiae

(2015) Guoqing Liu et al.   JOURNAL OF THEORETICAL BIOLOGY

Predicting the subcellular localization of mycobacterial proteins by incorporating the optimal tripeptides into the general form of pseudo amino acid composition

(2015) Pan-Pan Zhu et al.   Molecular BioSystems

iRSpot-GAEnsC: identifing recombination spots via ensemble classifier and extending the concept of Chou’s PseAAC to formulate DNA samples

(2015) Muhammad Kabir et al.   MOLECULAR GENETICS AND GENOMICS

CircNet: a database of circular RNAs derived from transcriptome sequencing data

(2015) Yu-Chen Liu et al.   NUCLEIC ACIDS RESEARCH

iTIS-PseTNC: A sequence-based predictor for identifying translation initiation site in human genes using pseudo trinucleotide composition

(2014) Wei Chen et al.   ANALYTICAL BIOCHEMISTRY

PseKNC: A flexible web server for generating pseudo K-tuple nucleotide composition

(2014) Wei Chen et al.   ANALYTICAL BIOCHEMISTRY

Sequence-based identification of recombination spots using pseudo nucleic acid representation and recursive feature extraction by linear kernel SVM

(2014) Liqi Li et al.   BMC BIOINFORMATICS

Predicting Recombination Hotspots in Yeast Based on DNA Sequence and Chromatin Structure

(2014) Bingjie Zhang et al.   Current Bioinformatics

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

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

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

(2014) Hui Ding et al.   Biomed Research International

iHSP-PseRAAAC: Identifying the heat shock protein families using pseudo reduced amino acid alphabet composition

(2013) Peng-Mian Feng et al.   ANALYTICAL BIOCHEMISTRY

iRSpot-PseDNC: identify recombination spots with pseudo dinucleotide composition

(2013) Wei Chen et al.   NUCLEIC ACIDS RESEARCH

CD-HIT: accelerated for clustering the next-generation sequencing data

(2012) Limin Fu et al.   BIOINFORMATICS

A Hierarchical Combination of Factors Shapes the Genome-wide Topography of Yeast Meiotic Recombination Initiation

(2011) Jing Pan et al.   CELL

Sequence-dependent prediction of recombination hotspots in Saccharomyces cerevisiae

(2011) Guoqing Liu et al.   JOURNAL OF THEORETICAL BIOLOGY

Direct and indirect consequences of meiotic recombination: implications for genome evolution

(2011) Matthew T. Webster et al.   TRENDS IN GENETICS

Drive Against Hotspot Motifs in Primates Implicates the PRDM9 Gene in Meiotic Recombination

(2010) S. Myers et al.   SCIENCE

Histone H3 lysine 4 trimethylation marks meiotic recombination initiation sites

(2008) Valérie Borde et al.   EMBO JOURNAL

Support vector machines combined with feature selection for breast cancer diagnosis

(2008) Mehmet Fatih Akay   EXPERT SYSTEMS WITH APPLICATIONS

The modified Mahalanobis Discriminant for predicting outer membrane proteins by using Chou's pseudo amino acid composition

(2008) Hao Lin   JOURNAL OF THEORETICAL BIOLOGY

High-resolution mapping of meiotic crossovers and non-crossovers in yeast

(2008) Eugenio Mancera et al.   NATURE

Predicting Subcellular Localization of Mycobacterial Proteins by Using Chous Pseudo Amino Acid Composition

(2008) Hao Lin et al.   PROTEIN AND PEPTIDE LETTERS