Search Results - "Chou, Kuo‐Chen" :: K.UTB vyhledávací portál | TBU Library Retrieval Portal

An Unprecedented Revolution in Medicinal Chemistry Driven by the Progress of Biological Science

An Unprecedented Revolution in Medicinal Chemistry Driven by the Progress of Biological Science

by Chou, Kuo-Chen
Published in Current topics in medicinal chemistry (01.08.2017)

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Some remarks on protein attribute prediction and pseudo amino acid composition

Some remarks on protein attribute prediction and pseudo amino acid composition

by Chou, Kuo-Chen
Published in Journal of theoretical biology (21.03.2011)

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Impacts of bioinformatics to medicinal chemistry

Impacts of bioinformatics to medicinal chemistry

by Chou, Kuo-Chen
Published in Medicinal chemistry (Shp-sariqah, United Arab Emirates) (01.01.2015)

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Advances in Predicting Subcellular Localization of Multi-label Proteins and its Implication for Developing Multi-target Drugs

Advances in Predicting Subcellular Localization of Multi-label Proteins and its Implication for Developing Multi-target Drugs

by Chou, Kuo-Chen
Published in Current medicinal chemistry (01.01.2019)

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2L-piRNA: A Two-Layer Ensemble Classifier for Identifying Piwi-Interacting RNAs and Their Function

2L-piRNA: A Two-Layer Ensemble Classifier for Identifying Piwi-Interacting RNAs and Their Function

by Liu, Bin, Yang, Fan, Chou, Kuo-Chen
Published in Molecular therapy. Nucleic acids (16.06.2017)

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Plant-mPLoc: A Top-Down Strategy to Augment the Power for Predicting Plant Protein Subcellular Localization

Plant-mPLoc: A Top-Down Strategy to Augment the Power for Predicting Plant Protein Subcellular Localization

by Chou, Kuo-Chen, Shen, Hong-Bin
Published in PloS one (28.06.2010)

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pLoc-mHum: predict subcellular localization of multi-location human proteins via general PseAAC to winnow out the crucial GO information

pLoc-mHum: predict subcellular localization of multi-location human proteins via general PseAAC to winnow out the crucial GO information

by Cheng, Xiang, Xiao, Xuan, Chou, Kuo-Chen
Published in Bioinformatics (01.05.2018)

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pLoc-mGneg: Predict subcellular localization of Gram-negative bacterial proteins by deep gene ontology learning via general PseAAC

pLoc-mGneg: Predict subcellular localization of Gram-negative bacterial proteins by deep gene ontology learning via general PseAAC

by Cheng, Xiang, Xiao, Xuan, Chou, Kuo-Chen
Published in Genomics (San Diego, Calif.) (01.07.2018)

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iDNA-Prot|dis: identifying DNA-binding proteins by incorporating amino acid distance-pairs and reduced alphabet profile into the general pseudo amino acid composition

by Liu, Bin, Xu, Jinghao, Lan, Xun, Xu, Ruifeng, Zhou, Jiyun, Wang, Xiaolong, Chou, Kuo-Chen
Published in PloS one (03.09.2014)

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Identification of real microRNA precursors with a pseudo structure status composition approach

Identification of real microRNA precursors with a pseudo structure status composition approach

by Liu, Bin, Fang, Longyun, Liu, Fule, Wang, Xiaolong, Chen, Junjie, Chou, Kuo-Chen
Published in PloS one (30.03.2015)

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Progresses in Predicting Post-translational Modification

Progresses in Predicting Post-translational Modification

by Chou, Kuo-Chen
Published in International journal of peptide research and therapeutics (01.06.2020)

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iSNO-PseAAC: predict cysteine S-nitrosylation sites in proteins by incorporating position specific amino acid propensity into pseudo amino acid composition

iSNO-PseAAC: predict cysteine S-nitrosylation sites in proteins by incorporating position specific amino acid propensity into pseudo amino acid composition

by Xu, Yan, Ding, Jun, Wu, Ling-Yun, Chou, Kuo-Chen
Published in PloS one (07.02.2013)

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iLoc-Euk: a multi-label classifier for predicting the subcellular localization of singleplex and multiplex eukaryotic proteins

iLoc-Euk: a multi-label classifier for predicting the subcellular localization of singleplex and multiplex eukaryotic proteins

by Chou, Kuo-Chen, Wu, Zhi-Cheng, Xiao, Xuan
Published in PloS one (30.03.2011)

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Pseudo nucleotide composition or PseKNC: an effective formulation for analyzing genomic sequences

Pseudo nucleotide composition or PseKNC: an effective formulation for analyzing genomic sequences

by Chen, Wei, Lin, Hao, Chou, Kuo-Chen
Published in Molecular bioSystems (01.01.2015)

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Insights into the mutation-induced HHH syndrome from modeling human mitochondrial ornithine transporter-1

Insights into the mutation-induced HHH syndrome from modeling human mitochondrial ornithine transporter-1

by Wang, Jing-Fang, Chou, Kuo-Chen
Published in PloS one (26.01.2012)

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Graphic rule for drug metabolism systems

Graphic rule for drug metabolism systems

by Chou, Kuo-Chen
Published in Current drug metabolism (01.05.2010)

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iLearn: an integrated platform and meta-learner for feature engineering, machine-learning analysis and modeling of DNA, RNA and protein sequence data

iLearn: an integrated platform and meta-learner for feature engineering, machine-learning analysis and modeling of DNA, RNA and protein sequence data

by Chen, Zhen, Zhao, Pei, Li, Fuyi, Marquez-Lago, Tatiana T, Leier, André, Revote, Jerico, Zhu, Yan, Powell, David R, Akutsu, Tatsuya, Webb, Geoffrey I, Chou, Kuo-Chen, Smith, A Ian, Daly, Roger J, Li, Jian, Song, Jiangning
Published in Briefings in bioinformatics (21.05.2020)

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repDNA: a Python package to generate various modes of feature vectors for DNA sequences by incorporating user-defined physicochemical properties and sequence-order effects

repDNA: a Python package to generate various modes of feature vectors for DNA sequences by incorporating user-defined physicochemical properties and sequence-order effects

by Liu, Bin, Liu, Fule, Fang, Longyun, Wang, Xiaolong, Chou, Kuo-Chen
Published in Bioinformatics (15.04.2015)

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iRNA-PseColl: Identifying the Occurrence Sites of Different RNA Modifications by Incorporating Collective Effects of Nucleotides into PseKNC

iRNA-PseColl: Identifying the Occurrence Sites of Different RNA Modifications by Incorporating Collective Effects of Nucleotides into PseKNC

by Feng, Pengmian, Ding, Hui, Yang, Hui, Chen, Wei, Lin, Hao, Chou, Kuo-Chen
Published in Molecular therapy. Nucleic acids (16.06.2017)

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A new method for predicting the subcellular localization of eukaryotic proteins with both single and multiple sites: Euk-mPLoc 2.0

A new method for predicting the subcellular localization of eukaryotic proteins with both single and multiple sites: Euk-mPLoc 2.0

by Chou, Kuo-Chen, Shen, Hong-Bin
Published in PloS one (01.04.2010)

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