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Cited by in F6Publishing
For: Yang Q, Li B, Chen S, Tang J, Li Y, Li Y, Zhang S, Shi C, Zhang Y, Mou M, Xue W, Zhu F. MMEASE: Online meta-analysis of metabolomic data by enhanced metabolite annotation, marker selection and enrichment analysis. J Proteomics 2021;232:104023. [PMID: 33130111 DOI: 10.1016/j.jprot.2020.104023] [Cited by in Crossref: 23] [Cited by in F6Publishing: 27] [Article Influence: 11.5] [Reference Citation Analysis]
Number Citing Articles
1 Tang H, Sun L, Huang J, Yang Z, Li C, Zhou X. The mechanism and biomarker function of Cavin-2 in lung ischemia-reperfusion injury. Computers in Biology and Medicine 2022;151:106234. [DOI: 10.1016/j.compbiomed.2022.106234] [Reference Citation Analysis]
2 Yang Q, Li B, Wang P, Xie J, Feng Y, Liu Z, Zhu F. LargeMetabo: an out-of-the-box tool for processing and analyzing large-scale metabolomic data. Briefings in Bioinformatics 2022. [DOI: 10.1093/bib/bbac455] [Reference Citation Analysis]
3 Sun X, Zhang Y, Li H, Zhou Y, Shi S, Chen Z, He X, Zhang H, Li F, Yin J, Mou M, Wang Y, Qiu Y, Zhu F. DRESIS: the first comprehensive landscape of drug resistance information. Nucleic Acids Res 2022:gkac812. [PMID: 36243960 DOI: 10.1093/nar/gkac812] [Reference Citation Analysis]
4 Li F, Yin J, Lu M, Mou M, Li Z, Zeng Z, Tan Y, Wang S, Chu X, Dai H, Hou T, Zeng S, Chen Y, Zhu F. DrugMAP: molecular atlas and pharma-information of all drugs. Nucleic Acids Res 2022:gkac813. [PMID: 36243961 DOI: 10.1093/nar/gkac813] [Reference Citation Analysis]
5 Liu S, Chen L, Zhang Y, Zhou Y, He Y, Chen Z, Qi S, Zhu J, Chen X, Zhang H, Luo Y, Qiu Y, Tao L, Zhu F. M6AREG: m6A-centered regulation of disease development and drug response. Nucleic Acids Res 2022:gkac801. [PMID: 36134713 DOI: 10.1093/nar/gkac801] [Reference Citation Analysis]
6 Rong Z, Liu Z, Song J, Cao L, Yu Y, Qiu M, Hou Y. MCluster-VAEs: An end-to-end variational deep learning-based clustering method for subtype discovery using multi-omics data. Comput Biol Med 2022;150:106085. [PMID: 36162197 DOI: 10.1016/j.compbiomed.2022.106085] [Reference Citation Analysis]
7 Huo J, Xie W, Fan X, Sun P. Pyroptosis, apoptosis, and necroptosis molecular subtype derived prognostic signature universal applicable for gastric cancer-A large sample and multicenter retrospective analysis. Comput Biol Med 2022;149:106037. [PMID: 36044785 DOI: 10.1016/j.compbiomed.2022.106037] [Reference Citation Analysis]
8 Iqbal N, Kumar P. Integrated COVID-19 Predictor: Differential expression analysis to reveal potential biomarkers and prediction of coronavirus using RNA-Seq profile data. Computers in Biology and Medicine 2022;147:105684. [DOI: 10.1016/j.compbiomed.2022.105684] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
9 Nosrati V, Rahmani M. An ensemble framework for microarray data classification based on feature subspace partitioning. Comput Biol Med 2022;148:105820. [PMID: 35872409 DOI: 10.1016/j.compbiomed.2022.105820] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
10 de Fátima Cobre A, Surek M, Stremel DP, Fachi MM, Lobo Borba HH, Tonin FS, Pontarolo R. Diagnosis and prognosis of COVID-19 employing analysis of patients' plasma and serum via LC-MS and machine learning. Computers in Biology and Medicine 2022;146:105659. [DOI: 10.1016/j.compbiomed.2022.105659] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
11 Zhang C, Mou M, Zhou Y, Zhang W, Lian X, Shi S, Lu M, Sun H, Li F, Wang Y, Zeng Z, Li Z, Zhang B, Qiu Y, Zhu F, Gao J. Biological activities of drug inactive ingredients. Brief Bioinform 2022:bbac160. [PMID: 35524477 DOI: 10.1093/bib/bbac160] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
12 Ding W, Nan Y, Wu J, Han C, Xin X, Li S, Liu H, Zhang L. Combining multi-dimensional molecular fingerprints to predict the hERG cardiotoxicity of compounds. Computers in Biology and Medicine 2022;144:105390. [DOI: 10.1016/j.compbiomed.2022.105390] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
13 Shi Q, Liu Y, Lu M, Lei Q, Chen Z, Wang L, He X. A pathway-guided strategy identifies a metabolic signature for prognosis prediction and precision therapy for hepatocellular carcinoma. Computers in Biology and Medicine 2022;144:105376. [DOI: 10.1016/j.compbiomed.2022.105376] [Reference Citation Analysis]
14 Xia W, Zheng L, Fang J, Li F, Zhou Y, Zeng Z, Zhang B, Li Z, Li H, Zhu F. PFmulDL: a novel strategy enabling multi-class and multi-label protein function annotation by integrating diverse deep learning methods. Comput Biol Med 2022;145:105465. [PMID: 35366467 DOI: 10.1016/j.compbiomed.2022.105465] [Cited by in Crossref: 12] [Cited by in F6Publishing: 14] [Article Influence: 12.0] [Reference Citation Analysis]
15 Zheng Z, Li Y, Lu X, Zhang J, Liu Q, Zhou D, Deng X, Qiu Y, Chen Q, Zheng H, Dai J. A novel mTOR-associated gene signature for predicting prognosis and evaluating tumor immune microenvironment in lung adenocarcinoma. Comput Biol Med 2022;145:105394. [PMID: 35325730 DOI: 10.1016/j.compbiomed.2022.105394] [Reference Citation Analysis]
16 Paul A, Azhar S, Das PN, Bairagi N, Chatterjee S. Elucidating the metabolic characteristics of pancreatic β-cells from patients with type 2 diabetes (T2D) using a genome-scale metabolic modeling. Comput Biol Med 2022;144:105365. [PMID: 35276551 DOI: 10.1016/j.compbiomed.2022.105365] [Reference Citation Analysis]
17 Li F, Zhou Y, Zhang Y, Yin J, Qiu Y, Gao J, Zhu F. POSREG: proteomic signature discovered by simultaneously optimizing its reproducibility and generalizability. Brief Bioinform 2022:bbac040. [PMID: 35183059 DOI: 10.1093/bib/bbac040] [Cited by in Crossref: 25] [Cited by in F6Publishing: 25] [Article Influence: 25.0] [Reference Citation Analysis]
18 Xue W, Fu T, Deng S, Yang F, Yang J, Zhu F. Molecular Mechanism for the Allosteric Inhibition of the Human Serotonin Transporter by Antidepressant Escitalopram. ACS Chem Neurosci 2022;13:340-51. [PMID: 35041375 DOI: 10.1021/acschemneuro.1c00694] [Cited by in Crossref: 33] [Cited by in F6Publishing: 35] [Article Influence: 33.0] [Reference Citation Analysis]
19 Wang Z, Zhang Y, Li Q, Zou Q, Liu Q. A road map for happiness: The psychological factors related cell types in various parts of human body from single cell RNA-seq data analysis. Computers in Biology and Medicine 2022. [DOI: 10.1016/j.compbiomed.2022.105286] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
20 Yang Q, Gong Y. Construction of the Classification Model Using Key Genes Identified Between Benign and Malignant Thyroid Nodules From Comprehensive Transcriptomic Data. Front Genet 2022;12:791349. [DOI: 10.3389/fgene.2021.791349] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
21 Jiao S, Xu L, Ju Y. CWLy-RF: A novel approach for identifying cell wall lyases based on random forest classifier. Genomics 2021;113:2919-24. [PMID: 34186189 DOI: 10.1016/j.ygeno.2021.06.038] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
22 Gałęzowska G, Ratajczyk J, Wolska L. Determination of amino acids in human biological fluids by high-performance liquid chromatography: critical review. Amino Acids 2021;53:993-1009. [PMID: 34028614 DOI: 10.1007/s00726-021-03002-x] [Cited by in Crossref: 7] [Cited by in F6Publishing: 5] [Article Influence: 7.0] [Reference Citation Analysis]
23 Zhang S, Amahong K, Sun X, Lian X, Liu J, Sun H, Lou Y, Zhu F, Qiu Y. The miRNA: a small but powerful RNA for COVID-19. Brief Bioinform 2021;22:1137-49. [PMID: 33675361 DOI: 10.1093/bib/bbab062] [Cited by in Crossref: 54] [Cited by in F6Publishing: 60] [Article Influence: 54.0] [Reference Citation Analysis]
24 Xu L, Jiao S, Zhang D, Wu S, Zhang H, Gao B. Identification of long noncoding RNAs with machine learning methods: a review. Brief Funct Genomics 2021;20:174-80. [PMID: 33758917 DOI: 10.1093/bfgp/elab017] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
25 Zhao Q, Ma J, Xie F, Wang Y, Zhang Y, Li H, Sun Y, Wang L, Guo M, Han K. Recent Advances in Predicting Protein S-Nitrosylation Sites. Biomed Res Int 2021;2021:5542224. [PMID: 33628788 DOI: 10.1155/2021/5542224] [Cited by in Crossref: 3] [Cited by in F6Publishing: 4] [Article Influence: 3.0] [Reference Citation Analysis]
26 Chen X, School of Basic Education, Changsha Aeronautical Vocational and Technical College, Changsha, Hunan 410124, China, Lin Y, Qu Q, Ning B, Chen H, Li X, College of Computer Science and Electronic Engineering, Hunan University, Changsha, Hunan 410082, China, School of Software, East China Jiaotong University, Nanchang 330013, China. An epistasis and heterogeneity analysis method based on maximum correlation and maximum consistence criteria. MBE 2021;18:7711-7726. [DOI: 10.3934/mbe.2021382] [Reference Citation Analysis]