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Natural Science

Natural Science

Natural Science

ISSN Print: 2150-4091
ISSN Online: 2150-4105
www.scirp.org/journal/ns
E-mail: ns@scirp.org
"Other Mountain Stones Can Attack Jade: The 5-Steps Rule"
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] The significant and profound impacts of Gordon life science institute
2021
[4] The Remarkable impacts of Gordon life science institute
2021
[5] iDRP-PseAAC: Identification of DNA Replication Proteins Using General PseAAC and Position Dependent Features
2021
[6] pLoc_Deep-mHum: Predict Subcellular Localization of Human Proteins by Deep Learning
2020
[7] Use Chou's 5-steps rule to predict remote homology proteins by merging grey incidence analysis and domain similarity analysis
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 5-steps rule to identify N6-methyladenine sites by ensemble learning combined with multiple feature extraction methods
2020
[11] pLoc_Deep-mGpos: Predict Subcellular Localization of Gram Positive Bacteria Proteins by Deep Learning
2020
[12] Identification of ligand-binding residues using protein sequence profile alignment and query-specific support vector machine model
2020
[13] pLoc_Deep-mGneg: Predict Subcellular Localization of Gram Negative Bacterial Proteins by Deep Learning
2020
[14] pLoc_Deep-mPlant: Predict Subcellular Localization of Plant Proteins by Deep Learning
2020
[15] iATC_Deep-mISF: A Multi-Label Classifier for Predicting the Classes of Anatomical Therapeutic Chemicals by Deep Learning
2020
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