Ke Chen

发表

Analysis and prediction of RNA-binding residues using sequence, evolutionary conservation, and predicted secondary structure and solvent accessibility.

Tuo Zhang, Hua Zhang, Ke Chen, 2010, Current protein & peptide science.

Prediction of protein crystallization using collocation of amino acid pairs.

Lukasz Kurgan, Ke Chen, Mandana Rahbari, 2007, Biochemical and biophysical research communications.

Investigation of Atomic Level Patterns in Protein—Small Ligand Interactions

Ke Chen, Lukasz Kurgan, 2009, PloS one.

18 Neural Networks in Bioinformatics

Ke Chen, Lukasz Kurgan, 2012 .

Sequence based prediction of relative solvent accessibility using two-stage support vector regression with confidence values

Lukasz Kurgan, Ke Chen, Ke Chen, 2008 .

Sequence-Based Methods for Real Value Predictions of Protein Structure

Lukasz Kurgan, Krzysztof J. Cios, Ke Chen, 2008 .

Prediction of protein structural class for the twilight zone sequences.

Lukasz Kurgan, Ke Chen, Ke Chen, 2007, Biochemical and biophysical research communications.

Prediction of protein secondary structure content for the twilight zone sequences

Ke Chen, Jishou Ruan, Leila Homaeian, 2007, Proteins.

A statistical analysis on transcriptome sequences: The enrichment of Alu-element is associated with subcellular location.

Ke Chen, Yuxuan Wang, Jie Sun, 2018, Biochemical and biophysical research communications.

PFRES: protein fold classification by using evolutionary information and predicted secondary structure

Lukasz A. Kurgan, Ke Chen, Ke Chen, 2007, Bioinform..

A critical comparative assessment of predictions of protein-binding sites for biologically relevant organic compounds.

Lukasz Kurgan, Jianzhao Gao, Ke Chen, 2011, Structure.

HuMiTar: A sequence-based method for prediction of human microRNA targets

Lukasz A. Kurgan, Ke Chen, Jishou Ruan, 2008, Algorithms for Molecular Biology.

Optimization of the Sliding Window Size for Protein Structure Prediction

Lukasz A. Kurgan, Ke Chen, Jishou Ruan, 2006, 2006 IEEE Symposium on Computational Intelligence and Bioinformatics and Computational Biology.

On the relation between residue flexibility and local solvent accessibility in proteins

Lukasz Kurgan, Ke Chen, Shiyi Shen, 2009, Proteins.

Quantitative Analysis of the Conservation of the Tertiary Structure of Protein Segments

Ke Chen, Jishou Ruan, Lukasz A Kurgan, 2006, The protein journal.

Sequence based residue depth prediction using evolutionary information and predicted secondary structure

Lukasz A. Kurgan, Tuo Zhang, Ke Chen, 2008, BMC Bioinformatics.

Accurate sequence-based prediction of catalytic residues

Lukasz A. Kurgan, Tuo Zhang, Ke Chen, 2008, Bioinform..

Improved sequence-based prediction of disordered regions with multilayer fusion of multiple information sources

Lukasz A. Kurgan, Ke Chen, Wojciech Stach, 2010, Bioinform..

Prediction of Three Dimensional Structure of Calmodulin

Ke Chen, Jishou Ruan, Lukasz A Kurgan, 2006, The protein journal.

Computational Prediction of Secondary and Supersecondary Structures from Protein Sequences.

Lukasz Kurgan, Christopher J Oldfield, Ke Chen, 2019, Methods in molecular biology.

Computational prediction of secondary and supersecondary structures.

Lukasz Kurgan, Ke Chen, Ke Chen, 2013, Methods in molecular biology.

Critical assessment of high-throughput standalone methods for secondary structure prediction

Lukasz A. Kurgan, Tuo Zhang, Ke Chen, 2011, Briefings Bioinform..

Prediction of flexible/rigid regions from protein sequences using k-spaced amino acid pairs

Ke Chen, Jishou Ruan, Lukasz A Kurgan, 2007, BMC Structural Biology.

Prediction of protein structural class using novel evolutionary collocation‐based sequence representation

Lukasz A. Kurgan, Ke Chen, Jishou Ruan, 2008, J. Comput. Chem..

ATPsite: sequence-based prediction of ATP-binding residues

Lukasz Kurgan, Ke Chen, Marcin J Mizianty, 2011, Proteome Science.

Quad-PRE: A Hybrid Method to Predict Protein Quaternary Structure Attributes

Chen Zhang, Zheng Wei, Yanping Zhang, 2014, Comput. Math. Methods Medicine.

PFP-RFSM: Protein fold prediction by using random forests and sequence motifs

Ke Chen, Jigang Wu, Ke Chen, 2013 .

Prediction of integral membrane protein type by collocated hydrophobic amino acid pairs

Lukasz A. Kurgan, Li Du, Ke Chen, 2009, J. Comput. Chem..

SCPRED: Accurate prediction of protein structural class for sequences of twilight-zone similarity with predicting sequences

Lukasz A. Kurgan, Krzysztof J. Cios, Ke Chen, 2008, BMC Bioinformatics.

Prediction of Protein Structural Class Using PSI-BLAST Profile Based Collocation of Amino Acid Pairs

L. Kurgan, Ke Chen, Jishou Ruan, 2007, 2007 1st International Conference on Bioinformatics and Biomedical Engineering.

Prediction and analysis of nucleotide-binding residues using sequence and sequence-derived structural descriptors

Lukasz A. Kurgan, Ke Chen, Marcin J. Mizianty, 2012, Bioinform..

Accurate prediction of ATP-binding residues using sequence and sequence-derived structural descriptors

Lukasz A. Kurgan, Ke Chen, Marcin J. Mizianty, 2010, 2010 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

iFC2: an integrated web-server for improved prediction of protein structural class, fold type, and secondary structure content

Lukasz Kurgan, Ke Chen, Leila Homaeian, 2010, Amino Acids.

Improved Prediction of Relative Solvent Accessibility Using Two-stage Support Vector Regression

L. Kurgan, Ke Chen, M. Kurgan, 2007, 2007 1st International Conference on Bioinformatics and Biomedical Engineering.

Neural Networks in Bioinformatics

Lukasz A. Kurgan, Ke Chen, Ke Chen, 2012, Handbook of Natural Computing.

Systematic investigation of sequence and structural motifs that recognize ATP

Ke Chen, Lukasz Kurgan, Dacheng Wang, 2015, Comput. Biol. Chem..

Accurate prediction of secondary structure of tRNAs.

Jie Sun, Ke Chen, Guosong Jiang, 2019, Biochemical and biophysical research communications.

NSiteMatch: Prediction of Binding Sites of Nucleotides by Identifying the Structure Similarity of Local Surface Patches

Jie Sun, Ke Chen, Ke Chen, 2017, Comput. Math. Methods Medicine.

A critical comparative assessment of predictions of protein-binding sites for biologically relevant organic compounds.

Ke Chen, Lukasz Kurgan, M. Mizianty, 2011, Structure.