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

Current topics in medicinal chemistry, 2017-08, Vol.17 (21), p.2337

Chou, Kuo-Chen

2017

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Some remarks on protein attribute prediction and pseudo amino acid composition

Journal of theoretical biology, 2011-03, Vol.273 (1), p.236-247

Chou, Kuo-Chen

2011

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Impacts of bioinformatics to medicinal chemistry

Medicinal chemistry (Shp-sariqah, United Arab Emirates), 2015-01, Vol.11 (3), p.218-234

Chou, Kuo-Chen

2015

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Osteoporosis Due to Hormone Imbalance: An Overview of the Effects of Estrogen Deficiency and Glucocorticoid Overuse on Bone Turnover

International journal of molecular sciences, 2022-01, Vol.23 (3), p.1376

2022

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

Current medicinal chemistry, 2019-01, Vol.26 (26), p.4918-4943

Chou, Kuo-Chen

2019

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

Molecular therapy. Nucleic acids, 2017-06, Vol.7 (C), p.267-277

2017

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Some remarks on predicting multi-label attributes in molecular biosystems

Molecular bioSystems, 2013-01, Vol.9 (6), p.1092-1100

Chou, Kuo-Chen

2013

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pLoc-mEuk: Predict subcellular localization of multi-label eukaryotic proteins by extracting the key GO information into general PseAAC

Genomics (San Diego, Calif.), 2018-01, Vol.110 (1), p.50-58

2018

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

PloS one, 2010-06, Vol.5 (6), p.e11335-e11335

2010

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

PloS one, 2015-03, Vol.10 (3), p.e0121501

2015

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iDHS-EL: identifying DNase I hypersensitive sites by fusing three different modes of pseudo nucleotide composition into an ensemble learning framework

Bioinformatics (Oxford, England), 2016-08, Vol.32 (16), p.2411-2418

2016

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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

Briefings in bioinformatics, 2020-05, Vol.21 (3), p.1047-1057

2020

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

Bioinformatics, 2018-05, Vol.34 (9), p.1448-1456

2018

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pLoc-mVirus: Predict subcellular localization of multi-location virus proteins via incorporating the optimal GO information into general PseAAC

Gene, 2017-09, Vol.628, p.315-321

2017

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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

PloS one, 2014-09, Vol.9 (9), p.e106691-e106691

2014

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

Molecular therapy. Nucleic acids, 2017-06, Vol.7 (C), p.155-163

2017

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

Nucleic acids research, 2015-07, Vol.43 (W1), p.W65-W71

2015

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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

PloS one, 2013-02, Vol.8 (2), p.e55844-e55844

2013

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

Molecular bioSystems, 2015-01, Vol.11 (1), p.262-2634

2015

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

PloS one, 2011-03, Vol.6 (3), p.e18258-e18258

2011

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pLoc-mPlant: predict subcellular localization of multi-location plant proteins by incorporating the optimal GO information into general PseAAC

Molecular bioSystems, 2017-08, Vol.13 (9), p.1722-1727

2017

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Uncovering Information Linkages between Bitcoin, Sustainable Finance and the Impact of COVID-19: Fractal and Entropy Analysis

Fractal and fractional, 2023-05, Vol.7 (6), p.424

2023

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Academic outcomes of flipped classroom learning: a meta‐analysis

Medical education, 2018-09, Vol.52 (9), p.910-924

2018

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

Genomics (San Diego, Calif.), 2018-07, Vol.110 (4), p.231-239

2018

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A mass spectrometry imaging and lipidomic investigation reveals aberrant lipid metabolism in the orthotopic mouse glioma

Journal of lipid research, 2022-12, Vol.63 (12), p.100304-100304, Article 100304

2022

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

Some remarks on protein attribute prediction and pseudo amino acid composition

Impacts of bioinformatics to medicinal chemistry

Osteoporosis Due to Hormone Imbalance: An Overview of the Effects of Estrogen Deficiency and Glucocorticoid Overuse on Bone Turnover

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

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

Some remarks on predicting multi-label attributes in molecular biosystems

pLoc-mEuk: Predict subcellular localization of multi-label eukaryotic proteins by extracting the key GO information into general PseAAC

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

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

iDHS-EL: identifying DNase I hypersensitive sites by fusing three different modes of pseudo nucleotide composition into an ensemble learning framework

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

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

pLoc-mVirus: Predict subcellular localization of multi-location virus proteins via incorporating the optimal GO information into general PseAAC

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

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

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

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

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

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

pLoc-mPlant: predict subcellular localization of multi-location plant proteins by incorporating the optimal GO information into general PseAAC

Uncovering Information Linkages between Bitcoin, Sustainable Finance and the Impact of COVID-19: Fractal and Entropy Analysis

Academic outcomes of flipped classroom learning: a meta‐analysis

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

A mass spectrometry imaging and lipidomic investigation reveals aberrant lipid metabolism in the orthotopic mouse glioma

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