Proposing 5-Steps Rule Is a Notable Milestone for Studying Molecular Biology

Natural Science

ISSN Print: 2150-4091
ISSN Online: 2150-4105
www.scirp.net/journal/ns
E-mail: [email protected]

Citations

Journals Menu

Guidelines & Policies

"Proposing 5-Steps Rule Is a Notable Milestone for Studying Molecular Biology"
written by Kuo-Chen Chou,
published by Natural Science, Vol.12 No.3, 2020

has been cited by the following article(s):

Google Scholar
CrossRef

[1]	DNA methylation prediction using reduced features obtained via Gappy Pair Kernel and Partial Least Square
	IEEE …, 2022

[2]	Lasso regression under stochastic restrictions in linear regression: An application to genomic data
	Communications in Statistics-Theory and …, 2022

[3]	Identification of intelligence-related proteins through a robust two-layer predictor
	… & Integrative Biology, 2022

[4]	The significant and profound impacts of Gordon life science institute
	2021

[5]	The Remarkable impacts of Gordon life science institute
	2021

[6]	iDRP-PseAAC: Identification of DNA Replication Proteins Using General PseAAC and Position Dependent Features
	2021

[7]	pLoc_Deep-mHum: Predict Subcellular Localization of Human Proteins by Deep Learning
	2020

[8]	Use Chou's 5-steps rule to identify DNase I hypersensitive sites via dinucleotide property matrix and extreme gradient boosting
	2020

[9]	pLoc_Deep-mAnimal: A Novel Deep CNN-BLSTM Network to Predict Subcellular Localization of Animal Proteins
	2020

[10]	Using Chou's Five-steps Rule to Classify and Predict Glutathione S-transferases with Different Machine Learning Algorithms and Pseudo Amino Acid Composition
	2020

[11]	Using Chou's 5-steps rule to identify N6-methyladenine sites by ensemble learning combined with multiple feature extraction methods
	2020

[12]	pLoc_Deep-mGpos: Predict Subcellular Localization of Gram Positive Bacteria Proteins by Deep Learning
	2020

[13]	Identification of ligand-binding residues using protein sequence profile alignment and query-specific support vector machine model
	2020

[14]	pLoc_Deep-mGneg: Predict Subcellular Localization of Gram Negative Bacterial Proteins by Deep Learning
	2020

[15]	pLoc_Deep-mPlant: Predict Subcellular Localization of Plant Proteins by Deep Learning
	2020

[16]	Machine learning model to predict oncologic outcomes for drugs in randomized clinical trials
	2020

[17]	iATC_Deep-mISF: A Multi-Label Classifier for Predicting the Classes of Anatomical Therapeutic Chemicals by Deep Learning
	2020

[18]	lncSLPre: An Ensemble Method with Multi-Source Sequence Descriptors to Predict lncRNA Subcellular Localizations from Imbalanced Data

[1]	Using Chou’s 5-steps rule to identify N6-methyladenine sites by ensemble learning combined with multiple feature extraction methods Journal of Biomolecular Structure and Dynamics, 2022 DOI:10.1080/07391102.2020.1821778

[2]	DNA Methylation Prediction Using Reduced Features Obtained via Gappy Pair Kernel and Partial Least Square IEEE Access, 2022 DOI:10.1109/ACCESS.2022.3174260

[3]	Lasso regression under stochastic restrictions in linear regression: An application to genomic data Communications in Statistics - Theory and Methods, 2022 DOI:10.1080/03610926.2022.2149243

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

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

[6]	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

[7]	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

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

[9]	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

	[email protected]
	+86 18163351462(WhatsApp)
	1655362766

	Paper Publishing WeChat

Natural Science

Natural Science

Journals Menu

Guidelines & Policies

Home

About SCIRP

Service

Policies