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For: Zhao Y, Wong L, Goh WWB. How to do quantile normalization correctly for gene expression data analyses. Sci Rep 2020;10:15534. [PMID: 32968196 DOI: 10.1038/s41598-020-72664-6] [Cited by in Crossref: 24] [Cited by in F6Publishing: 25] [Article Influence: 12.0] [Reference Citation Analysis]
Number Citing Articles
1 Möller S, Saul N, Projahn E, Barrantes I, Gézsi A, Walter M, Antal P, Fuellen G. Gene co-expression analyses of health(span) across multiple species. NAR Genom Bioinform 2022;4:lqac083. [PMID: 36458022 DOI: 10.1093/nargab/lqac083] [Reference Citation Analysis]
2 Kumar S, Ahmad A, Kushwaha N, Shokeen N, Negi S, Gautam K, Singh A, Tiwari P, Garg R, Agarwal R, Mohan A, Trikha A, Thakar A, Saini V. Selection of Ideal Reference Genes for Gene Expression Analysis in COVID-19 and Mucormycosis. Microbiol Spectr 2022. [DOI: 10.1128/spectrum.01656-22] [Reference Citation Analysis]
3 Nikitushkin V, Shleeva M, Loginov D, Dyčka F. F, Sterba J, Kaprelyants A. Shotgun proteomic profiling of dormant, ‘non-culturable’ Mycobacterium tuberculosis. PLoS ONE 2022;17:e0269847. [DOI: 10.1371/journal.pone.0269847] [Reference Citation Analysis]
4 Motta FC, Mcgoff K, Moseley RC, Cho C, Kelliher CM, Smith LM, Ortiz MS, Leman AR, Campione SA, Devos N, Chaorattanakawee S, Uthaimongkol N, Kuntawunginn W, Thongpiam C, Thamnurak C, Arsanok M, Wojnarski M, Vanchayangkul P, Boonyalai N, Smith PL, Spring M, Jongsakul K, Chuang I, Harer J, Haase SB. The Parasite Intraerythrocytic Cycle and Human Circadian Cycle are Coupled During Malaria Infection.. [DOI: 10.1101/2022.08.02.499203] [Reference Citation Analysis]
5 Schreiber J, Boix C, Lee JW, Li H, Guan Y, Chang C, Chang J, Hawkins-hooker A, Schölkopf B, Schweikert G, Carulla MR, Canakoglu A, Guzzo F, Nanni L, Masseroli M, Carman MJ, Pinoli P, Hong C, Yip KY, Spence JP, Batra SS, Song YS, Mahony S, Zhang Z, Tan W, Shen Y, Sun Y, Shi M, Adrian J, Sandstrom R, Farrell N, Halow J, Lee K, Jiang L, Yang X, Epstein C, Strattan JS, Snyder M, Kellis M, Noble WS, Kundaje A, ENCODE Imputation Challenge Participants. The ENCODE Imputation Challenge: A critical assessment of methods for cross-cell type imputation of epigenomic profiles.. [DOI: 10.1101/2022.07.30.502157] [Reference Citation Analysis]
6 Zhang X, Lee J, Bin Goh WW. An Investigation of How Normalisation and Local Modelling Techniques Confound Machine Learning Performance In a Mental Health Study. Heliyon 2022. [DOI: 10.1016/j.heliyon.2022.e09502] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
7 Konovalov N, Timonin S, Asyutin D, Raevskiy M, Sorokin M, Buzdin A, Kaprovoy S. Transcriptomic Portraits and Molecular Pathway Activation Features of Adult Spinal Intramedullary Astrocytomas. Front Oncol 2022;12:837570. [PMID: 35387112 DOI: 10.3389/fonc.2022.837570] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
8 Chekka LMS, Langaee T, Johnson JA. Comparison of Data Normalization Strategies for Array-Based MicroRNA Profiling Experiments and Identification and Validation of Circulating MicroRNAs as Endogenous Controls in Hypertension. Front Genet 2022;13:836636. [DOI: 10.3389/fgene.2022.836636] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
9 Nersisyan S, Novosad V, Galatenko A, Sokolov A, Bokov G, Konovalov A, Alekseev D, Tonevitsky A. ExhauFS: exhaustive search-based feature selection for classification and survival regression. PeerJ 2022;10:e13200. [DOI: 10.7717/peerj.13200] [Reference Citation Analysis]
10 Kumar S, Ahmad A, Kushwaha N, Negi S, Gautam K, Singh A, Tiwari P, Garg R, Agarwal R, Mohan A, Trikha A, Thakar A, Saini V. Selection of appropriate reference genes for normalization of qRT-PCR based gene expression analysis in SARS-CoV-2, and Covid-associated Mucormycosis infection.. [DOI: 10.1101/2022.03.15.22272441] [Reference Citation Analysis]
11 Zhuang W, Camacho L, Silva CS, Thomson M, Snyder K. A robust biostatistical method leverages informative but uncertainly determined qPCR data for biomarker detection, early diagnosis, and treatment. PLoS ONE 2022;17:e0263070. [DOI: 10.1371/journal.pone.0263070] [Reference Citation Analysis]
12 Troisi J, Richards SM, Troisi G, Scala G. Techniques for converting metabolomic data for analysis. Metabolomics Perspectives 2022. [DOI: 10.1016/b978-0-323-85062-9.00008-8] [Reference Citation Analysis]
13 Nguyen TM, Kim N, Kim DH, Le HL, Piran MJ, Um SJ, Kim JH. Deep Learning for Human Disease Detection, Subtype Classification, and Treatment Response Prediction Using Epigenomic Data. Biomedicines 2021;9:1733. [PMID: 34829962 DOI: 10.3390/biomedicines9111733] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
14 Раевский М, Сорокин М, Владимирова У, Сунцова М, Ефимов В, Гаража А, Дробышев А, Моисеев А, Румянцев П, Ли З, Буздин А. Основанные на молекулярном пути EGFR генные подписи клинически значимых мутаций при раке молочной железы, легких, щитовидной железы и при меланоме. БМ 2021;86:1719-1732. [DOI: 10.31857/s0320972521110099] [Reference Citation Analysis]
15 Raevskiy M, Sorokin M, Vladimirova U, Suntsova M, Efimov V, Garazha A, Drobyshev A, Moisseev A, Rumiantsev P, Li X, Buzdin A. EGFR Pathway-Based Gene Signatures of Druggable Gene Mutations in Melanoma, Breast, Lung, and Thyroid Cancers. Biochemistry Moscow 2021;86:1477-1488. [DOI: 10.1134/s0006297921110110] [Reference Citation Analysis]
16 Kundnani D, Storici F. FeatureCorr: An R package to study feature correlations aided with data transformation for sequencing and microarray data. Software Impacts 2021;10:100144. [DOI: 10.1016/j.simpa.2021.100144] [Reference Citation Analysis]
17 Angelescu R, Dobrescu R. MIDGET:Detecting differential gene expression on microarray data. Comput Methods Programs Biomed 2021;211:106418. [PMID: 34555591 DOI: 10.1016/j.cmpb.2021.106418] [Reference Citation Analysis]
18 Nikitushkin V, Shleeva M, Loginov D, Dycka F, Sterba J, Kaprelyants A. Shotgun proteomic profiling of dormant, ‘non-culturable’ Mycobacterium tuberculosis.. [DOI: 10.1101/2021.08.06.455493] [Reference Citation Analysis]
19 Zeng T, Cui L, Huang W, Liu Y, Si C, Qian T, Deng C, Fu L. The establishment of a prognostic scoring model based on the new tumor immune microenvironment classification in acute myeloid leukemia. BMC Med 2021;19:176. [PMID: 34348737 DOI: 10.1186/s12916-021-02047-9] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
20 Sorokin M, Raevskiy M, Zottel A, Šamec N, Skoblar Vidmar M, Matjašič A, Zupan A, Mlakar J, Suntsova M, Kuzmin DV, Buzdin A, Jovčevska I. Large-Scale Transcriptomics-Driven Approach Revealed Overexpression of CRNDE as a Poor Survival Prognosis Biomarker in Glioblastoma. Cancers (Basel) 2021;13:3419. [PMID: 34298634 DOI: 10.3390/cancers13143419] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 5.0] [Reference Citation Analysis]
21 Ding D, Lang T, Zou D, Tan J, Chen J, Zhou L, Wang D, Li R, Li Y, Liu J, Ma C, Zhou Q. Machine learning-based prediction of survival prognosis in cervical cancer. BMC Bioinformatics 2021;22:331. [PMID: 34134623 DOI: 10.1186/s12859-021-04261-x] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 5.0] [Reference Citation Analysis]
22 Pezoulas VC, Papaloukas C, Veyssiere M, Goules A, Tzioufas AG, Soumelis V, Fotiadis DI. A computational workflow for the detection of candidate diagnostic biomarkers of Kawasaki disease using time-series gene expression data. Comput Struct Biotechnol J 2021;19:3058-68. [PMID: 34136104 DOI: 10.1016/j.csbj.2021.05.036] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
23 Lykhenko OK, Frolova AO, Obolenskaya MY. Changes in the human placental transcriptome during the physiological course of pregnancy. Biopolym Cell 2021;37:73-82. [DOI: 10.7124/bc.000a4d] [Reference Citation Analysis]
24 Lykhenko O; Institute of Molecular Biology and Genetics of the National Academy of the Sciences of Ukraine, Kyiv. СONSECUTIVE INTEGRATION OF AVAILABLE MICROARRAY DATA FOR ANALYSIS OF DIFFERENTIAL GENE EXPRESSION IN HUMAN PLACENTA. Biotechnol acta 2021;14:38-45. [DOI: 10.15407/biotech14.01.38] [Reference Citation Analysis]