The Problem of Elsevier Series Journals Online Submission by Using Artificial Intelligence

Natural Science

ISSN Print: 2150-4091
ISSN Online: 2150-4105
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"The Problem of Elsevier Series Journals Online Submission by Using Artificial Intelligence"
written by Kuo-Chen Chou,
published by Natural Science, Vol.12 No.2, 2020

has been cited by the following article(s):

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[2]	The Remarkable impacts of Gordon life science institute
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[4]	Pathological analysis of hesperetin-derived small cell lung cancer by artificial intelligence technology under fiberoptic bronchoscopy
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[5]	The Development of Gordon Life Science Institute: Its Driving Force and Accomplishments
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[8]	How the artificial intelligence tool iPGK-PseAAC is working in predicting lysine phosphoglycerylation sites in proteins
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[9]	pLoc_Deep-mAnimal: A Novel Deep CNN-BLSTM Network to Predict Subcellular Localization of Animal Proteins
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[10]	A Call for a More Efficient Submission Process
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[15]	pLoc_Deep-mPlant: Predict Subcellular Localization of Plant Proteins by Deep Learning
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[16]	How the artificial intelligence tool pSumo-CD is working for predicting sumoylation sites in pro-teins
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[17]	How the artificial intelligence tool iHyd-PseAAC is working in predicting the hydroxyproline and hydroxylysine in proteins
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[18]	iATC_Deep-mISF: A Multi-Label Classifier for Predicting the Classes of Anatomical Therapeutic Chemicals by Deep Learning
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[1]	Pathological analysis of hesperetin-derived small cell lung cancer by artificial intelligence technology under fiberoptic bronchoscopy Mathematical Biosciences and Engineering, 2021 DOI:10.3934/mbe.2021423

[2]	The Remarkable Impacts of Gordon Life Science Institute Natural Science, 2021 DOI:10.4236/ns.2021.133006

[3]	pLoc_Deep-mGneg: Predict Subcellular Localization of Gram Negative Bacterial Proteins by Deep Learning Advances in Bioscience and Biotechnology, 2020 DOI:10.4236/abb.2020.115011

[4]	iATC_Deep-mISF: A Multi-Label Classifier for Predicting the Classes of Anatomical Therapeutic Chemicals by Deep Learning Advances in Bioscience and Biotechnology, 2020 DOI:10.4236/abb.2020.115012

[5]	A Call for a More Efficient Submission Process Publications, 2020 DOI:10.3390/publications8030040

[6]	pLoc_Deep-mPlant: Predict Subcellular Localization of Plant Proteins by Deep Learning Natural Science, 2020 DOI:10.4236/ns.2020.125021

[7]	pLoc_Deep-mHum: Predict Subcellular Localization of Human Proteins by Deep Learning Natural Science, 2020 DOI:10.4236/ns.2020.127042

[8]	pLoc_Deep-mAnimal: A Novel Deep CNN-BLSTM Network to Predict Subcellular Localization of Animal Proteins Natural Science, 2020 DOI:10.4236/ns.2020.125024

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