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Identification of synthetic lethality based on a functional network by using machine learning algorithms
期刊论文
JOURNAL OF CELLULAR BIOCHEMISTRY, 2019, 卷号: 120, 页码: 405-416
作者:
Li, JiaRui[1]
;
Lu, Lin[2]
;
Zhang, Yu-Hang[3]
;
Liu, Min[4]
;
Chen, Lei[5]
收藏
  |  
浏览/下载:24/0
  |  
提交时间:2019/04/22
maximum relevance and minimum redundancy (mRMR)
random forest (RF)
synthetic lethality
Classification of Widely and Rarely Expressed Genes with Recurrent Neural Network
期刊论文
Computational and structural biotechnology journal, 2019, 卷号: 17, 页码: 49-60
作者:
Chen Lei[1]
;
Pan XiaoYong[2]
;
Zhang Yu-Hang[3]
;
Liu Min[4]
;
Huang Tao[5]
收藏
  |  
浏览/下载:13/0
  |  
提交时间:2019/04/22
Enrichment theory
Incremental feature selection
Minimum redundancy maximum relevance
Rarely expressed gene
Recurrent neural network
Widely expressed gene
Fault Diagnosis and Condition Division Criterion of DC Gas Insulating Equipment Based on SF6 Partial Discharge Decomposition Characteristics
期刊论文
IEEE ACCESS, 2019, 卷号: 7
作者:
Zeng, Fuping
;
Wu, Siying
;
Yang, Xu
;
Wan, Zhaofeng
;
Tang, Ju
收藏
  |  
浏览/下载:4/0
  |  
提交时间:2019/12/05
Negative DC
SF6 decomposition characteristics
minimum-redundancy-maximum-relevance
fault diagnosis
decision tree
condition evaluation
Identification of synthetic lethality based on a functional network by using machine learning algorithms
期刊论文
JOURNAL OF CELLULAR BIOCHEMISTRY, 2019, 卷号: Vol.120 No.1, 页码: 405-416
作者:
Li, JiaRui
;
Lu, Lin
;
Zhang, Yu-Hang
;
Liu, Min
;
Chen, Lei
收藏
  |  
浏览/下载:6/0
  |  
提交时间:2019/12/17
maximum relevance and minimum redundancy (mRMR)
random forest (RF)
synthetic lethality
Classification of Widely and Rarely Expressed Genes with Recurrent Neural Network.
期刊论文
Computational and structural biotechnology journal, 2019, 卷号: Vol.17, 页码: 49-60
作者:
Chen Lei
;
Pan XiaoYong
;
Zhang Yu-Hang
;
Liu Min
;
Huang Tao
收藏
  |  
浏览/下载:9/0
  |  
提交时间:2019/12/13
Enrichment
theory
Incremental
feature
selection
Minimum
redundancy
maximum
relevance
Rarely
expressed
gene
Recurrent
neural
network
Widely
expressed
gene
Prediction of Protein-Peptide Interactions with a Nearest Neighbor Algorithm
期刊论文
CURRENT BIOINFORMATICS, 2018, 卷号: 13, 页码: 14-24
作者:
Li, Bi-Qing[1]
;
Zhang, Yu-Hang[2]
;
Jin, Mei-Ling[3]
;
Huang, Tao[4]
;
Cai, Yu-Dong[5]
收藏
  |  
浏览/下载:19/0
  |  
提交时间:2019/04/24
Protein-peptide interactions
maximum relevance minimum redundancy
incremental feature selection
functional domain composition
pseudo-amino acid composition
Analysis and Prediction of Nitrated Tyrosine Sites with the mRMR Method and Support Vector Machine Algorithm
期刊论文
CURRENT BIOINFORMATICS, 2018, 卷号: 13, 页码: 3-13
作者:
Wang, Shao Peng[1]
;
Zhang, Qing[2]
;
Lu, Jing[3]
;
Cai, Yu-Dong[4]
收藏
  |  
浏览/下载:3/0
  |  
提交时间:2019/04/24
Post-translational modification
tyrosine nitration prediction
minimum redundancy maximum relevance
support vector machine
incremental feature selection
Discriminating cirRNAs from other lncRNAs using a hierarchical extreme learning machine (H-ELM) algorithm with feature selection
期刊论文
MOLECULAR GENETICS AND GENOMICS, 2018, 卷号: 293, 页码: 137-149
作者:
Chen, Lei[1]
;
Zhang, Yu-Hang[2]
;
Huang, Guohua[3]
;
Pan, Xiaoyong[4]
;
Wang, ShaoPeng[5]
收藏
  |  
浏览/下载:12/0
  |  
提交时间:2019/04/22
cirRNAs
lncRNAs
Minimum redundancy maximum relevance
Hierarchical extreme learning machine algorithm
Computational Method for the Identification of Molecular Metabolites Involved in Cereal Hull Color Variations
期刊论文
Combinatorial chemistry & high throughput screening, 2018, 卷号: 21, 页码: 760-770
作者:
Zhang Yunhua[1]
;
Dong Dong[2]
;
Li Dai[3]
;
Lu Lin[4]
;
Li JiaRui[5]
收藏
  |  
浏览/下载:9/0
  |  
提交时间:2019/04/22
Cereal hull color
incrementalforward search
minimum redundancy maximum relevance
molecular metabolites
random forest.
Computational method for identifying malonylation sites by using random forest algorithm
期刊论文
Combinatorial chemistry & high throughput screening, 2018
作者:
Wang ShaoPeng[1]
;
Li JiaRui[2]
;
Sun Xijun[3]
;
Zhang Yu-Hang[4]
;
Huang Tao[5]
收藏
  |  
浏览/下载:2/0
  |  
提交时间:2019/04/22
Post-translational modification
malonylation site
maximum relevance minimum redundancy
random forest
synthetic minority over-sampling technique
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