{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,8]],"date-time":"2025-11-08T17:33:44Z","timestamp":1762623224498},"reference-count":47,"publisher":"Oxford University Press (OUP)","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2010,1,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: MicroRNA (miRNA) is a set of newly discovered non-coding small RNA molecules. Its significant effects have contributed to a number of critical biological events including cell proliferation, apoptosis development, as well as tumorigenesis. High-dimensional genomic discovery platforms (e.g. microarray) have been employed to evaluate the important roles of miRNAs by analyzing their expression profiling. However, because of the small total number of miRNAs and the absence of well-known endogenous controls, the traditional normalization methods for messenger RNA (mRNA) profiling analysis could not offer a suitable solution for miRNA analysis. The need for the establishment of new adaptive methods has come to the forefront.<\/jats:p>\n               <jats:p>Results: Locked nucleic acid (LNA)-based miRNA array was employed to profile miRNAs using colorectal cancer cell lines under different treatments. The expression pattern of overall miRNA profiling was pre-evaluated by a panel of miRNAs using Taqman-based quantitative real-time polymerase chain reaction (qRT-PCR) miRNA assays. A logistic regression model was built based on qRT-PCR results and then applied to the normalization of miRNA array data. The expression levels of 20 additional miRNAs selected from the normalized list were post-validated. Compared with other popularly used normalization methods, the logistic regression model efficiently calibrates the variance across arrays and improves miRNA microarray discovery accuracy.<\/jats:p>\n               <jats:p>Availability: Datasets and R package are available at http:\/\/gauss.usouthal.edu\/publ\/logit\/<\/jats:p>\n               <jats:p>Contact: \u00a0xi@usouthal.edu<\/jats:p>","DOI":"10.1093\/bioinformatics\/btp655","type":"journal-article","created":{"date-parts":[[2009,11,24]],"date-time":"2009-11-24T03:58:40Z","timestamp":1259035120000},"page":"228-234","source":"Crossref","is-referenced-by-count":22,"title":["A personalized microRNA microarray normalization method using a logistic regression model"],"prefix":"10.1093","volume":"26","author":[{"given":"Bin","family":"Wang","sequence":"first","affiliation":[{"name":"1 Department of Mathematics and Statistics, University of South Alabama, Mobile, AL 36688, 2 Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH 44195, 3 Mitchell Cancer Institute, University of South Alabama, Mobile, AL 36604, 4 Department of Surgery, Ochsner Health System, Ochsner Cancer Institute, New Orleans, LA 70121 and 5 Department of Pathology, School of Medicine, Stony Brook University, Stony Brook, NY 11794, USA"}]},{"given":"Xiao-Feng","family":"Wang","sequence":"additional","affiliation":[{"name":"1 Department of Mathematics and Statistics, University of South Alabama, Mobile, AL 36688, 2 Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH 44195, 3 Mitchell Cancer Institute, University of South Alabama, Mobile, AL 36604, 4 Department of Surgery, Ochsner Health System, Ochsner Cancer Institute, New Orleans, LA 70121 and 5 Department of Pathology, School of Medicine, Stony Brook University, Stony Brook, NY 11794, USA"}]},{"given":"Paul","family":"Howell","sequence":"additional","affiliation":[{"name":"1 Department of Mathematics and Statistics, University of South Alabama, Mobile, AL 36688, 2 Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH 44195, 3 Mitchell Cancer Institute, University of South Alabama, Mobile, AL 36604, 4 Department of Surgery, Ochsner Health System, Ochsner Cancer Institute, New Orleans, LA 70121 and 5 Department of Pathology, School of Medicine, Stony Brook University, Stony Brook, NY 11794, USA"}]},{"given":"Xuemin","family":"Qian","sequence":"additional","affiliation":[{"name":"1 Department of Mathematics and Statistics, University of South Alabama, Mobile, AL 36688, 2 Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH 44195, 3 Mitchell Cancer Institute, University of South Alabama, Mobile, AL 36604, 4 Department of Surgery, Ochsner Health System, Ochsner Cancer Institute, New Orleans, LA 70121 and 5 Department of Pathology, School of Medicine, Stony Brook University, Stony Brook, NY 11794, USA"}]},{"given":"Kun","family":"Huang","sequence":"additional","affiliation":[{"name":"1 Department of Mathematics and Statistics, University of South Alabama, Mobile, AL 36688, 2 Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH 44195, 3 Mitchell Cancer Institute, University of South Alabama, Mobile, AL 36604, 4 Department of Surgery, Ochsner Health System, Ochsner Cancer Institute, New Orleans, LA 70121 and 5 Department of Pathology, School of Medicine, Stony Brook University, Stony Brook, NY 11794, USA"}]},{"given":"Adam I.","family":"Riker","sequence":"additional","affiliation":[{"name":"1 Department of Mathematics and Statistics, University of South Alabama, Mobile, AL 36688, 2 Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH 44195, 3 Mitchell Cancer Institute, University of South Alabama, Mobile, AL 36604, 4 Department of Surgery, Ochsner Health System, Ochsner Cancer Institute, New Orleans, LA 70121 and 5 Department of Pathology, School of Medicine, Stony Brook University, Stony Brook, NY 11794, USA"}]},{"given":"Jingfang","family":"Ju","sequence":"additional","affiliation":[{"name":"1 Department of Mathematics and Statistics, University of South Alabama, Mobile, AL 36688, 2 Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH 44195, 3 Mitchell Cancer Institute, University of South Alabama, Mobile, AL 36604, 4 Department of Surgery, Ochsner Health System, Ochsner Cancer Institute, New Orleans, LA 70121 and 5 Department of Pathology, School of Medicine, Stony Brook University, Stony Brook, NY 11794, USA"}]},{"given":"Yaguang","family":"Xi","sequence":"additional","affiliation":[{"name":"1 Department of Mathematics and Statistics, University of South Alabama, Mobile, AL 36688, 2 Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH 44195, 3 Mitchell Cancer Institute, University of South Alabama, Mobile, AL 36604, 4 Department of Surgery, Ochsner Health System, Ochsner Cancer Institute, New Orleans, LA 70121 and 5 Department of Pathology, School of Medicine, Stony Brook University, Stony Brook, NY 11794, USA"}]}],"member":"286","published-online":{"date-parts":[[2009,11,23]]},"reference":[{"key":"2023012508211168700_B1","volume-title":"Categorical Data Analysis","author":"Agresti","year":"1996"},{"key":"2023012508211168700_B2","first-page":"983","article-title":"Operational criteria for selecting a cDNA microarray data normalization algorithm","volume":"15","author":"Argyropoulos","year":"2006","journal-title":"Oncol. Rep."},{"key":"2023012508211168700_B3","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1261\/rna.7240905","article-title":"Microarray profiling of microRNAs reveals frequent coexpression with neighboring miRNAs and host genes","volume":"11","author":"Baskerville","year":"2005","journal-title":"RNA"},{"key":"2023012508211168700_B4","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1016\/j.cell.2004.12.031","article-title":"Phylogenetic shadowing and computational identification of human microRNA genes","volume":"120","author":"Berezikov","year":"2005","journal-title":"Cell"},{"key":"2023012508211168700_B5","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1093\/bioinformatics\/19.2.185","article-title":"A comparison of normalization methods for high density oligonucleotide array data based on variance and bias","volume":"19","author":"Bolstad","year":"2003","journal-title":"Bioinformatics"},{"key":"2023012508211168700_B6","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1038\/334213a0","article-title":"Spliceosomal RNA U6 is remarkably conserved from yeast to mammals","volume":"334","author":"Brow","year":"1988","journal-title":"Nature"},{"key":"2023012508211168700_B7","doi-asserted-by":"crossref","first-page":"1497","DOI":"10.1126\/science.282.5393.1497","article-title":"Requirement for p53 and p21 to sustain G2 arrest after DNA damage","volume":"282","author":"Bunz","year":"1998","journal-title":"Science"},{"key":"2023012508211168700_B8","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1172\/JCI6863","article-title":"Disruption of p53 in human cancer cells alters the responses to therapeutic agents","volume":"104","author":"Bunz","year":"1999","journal-title":"J. Clin. Invest."},{"key":"2023012508211168700_B9","doi-asserted-by":"crossref","first-page":"11755","DOI":"10.1073\/pnas.0404432101","article-title":"MicroRNA profiling reveals distinct signatures in B cell chronic lymphocytic leukemias","volume":"101","author":"Calin","year":"2004","journal-title":"Proc. Natl Acad. Sci. USA"},{"key":"2023012508211168700_B10","doi-asserted-by":"crossref","first-page":"2999","DOI":"10.1073\/pnas.0307323101","article-title":"Human microRNA genes are frequently located at fragile sites and genomic regions involved in cancers","volume":"101","author":"Calin","year":"2004","journal-title":"Proc. Natl Acad. Sci. USA"},{"key":"2023012508211168700_B11","doi-asserted-by":"crossref","first-page":"2733","DOI":"10.1101\/gad.1026102","article-title":"The Argonaute family: tentacles that reach into RNAi, developmental control, stem cell maintenance, and tumorigenesis","volume":"16","author":"Carmell","year":"2002","journal-title":"Genes Dev."},{"key":"2023012508211168700_B12","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1177\/001316446002000104","article-title":"A coefficient of agreement for nominal scales","volume":"20","author":"Cohen","year":"1960","journal-title":"Educ. Psychol. Meas."},{"key":"2023012508211168700_B13","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1007\/0-306-47947-8_7","article-title":"DNA arrays for genetic analyses and medical diagnosis","volume-title":"Topics in Fluorescence Spectroscopy.","author":"D'Auria","year":"2003"},{"key":"2023012508211168700_B14","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/S0076-6879(06)11002-2","article-title":"Analyzing micro-RNA expression using microarrays","volume":"411","author":"Davison","year":"2006","journal-title":"Methods Enzymol"},{"key":"2023012508211168700_B15","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1038\/labinvest.3700208","article-title":"Normalization of gene expression measurements in tumor tissues: comparison of 13 endogenous control genes","volume":"85","author":"de Kok","year":"2005","journal-title":"Lab. Invest."},{"key":"2023012508211168700_B16","first-page":"111","article-title":"Statistical methods for identifying genes with differential expression in replicated cDNA microarray experiments","volume":"12","author":"Dudoit","year":"2002","journal-title":"Stat. Sin"},{"key":"2023012508211168700_B17","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1038\/nrc1840","article-title":"Oncomirs - microRNAs with a role in cancer","volume":"6","author":"Esquela-Kerscher","year":"2006","journal-title":"Nat. Rev."},{"key":"2023012508211168700_B18","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1006\/dbio.1999.9272","article-title":"The timing of lin-4 RNA accumulation controls the timing of postembryonic developmental events in Caenorhabditis elegans","volume":"210","author":"Feinbaum","year":"1999","journal-title":"Dev. Biol."},{"key":"2023012508211168700_B19","first-page":"38","volume-title":"Statistical Methods for Rates and Proportions","author":"Fleiss","year":"1981","edition":"2"},{"key":"2023012508211168700_B20","doi-asserted-by":"crossref","first-page":"613","DOI":"10.1177\/001316447303300309","article-title":"The equivalence of weighted kappa and the intraclass correlation coefficient as measures of reliability","volume":"33","author":"Fleiss","year":"1973","journal-title":"Educ. Psychol. Meas."},{"key":"2023012508211168700_B21","doi-asserted-by":"crossref","first-page":"323","DOI":"10.1037\/h0028106","article-title":"Large sample standard errors of kappa and weighted kappa","volume":"72","author":"Fleiss","year":"1969","journal-title":"Psychol. Bull."},{"key":"2023012508211168700_B22","doi-asserted-by":"crossref","first-page":"3945","DOI":"10.1073\/pnas.0800135105","article-title":"Distinctive microRNA signature of acute myeloid leukemia bearing cytoplasmic mutated nucleophosmin","volume":"105","author":"Garzon","year":"2008","journal-title":"Proc. Natl Acad. Sci. USA"},{"key":"2023012508211168700_B23","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1016\/j.ygeno.2008.04.002","article-title":"Comparison of normalization methods with microRNA microarray","volume":"92","author":"Hua","year":"2008","journal-title":"Genomics"},{"key":"2023012508211168700_B24","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1111\/j.1349-7006.2005.00015.x","article-title":"Reduced expression of Dicer associated with poor prognosis in lung cancer patients","volume":"96","author":"Karube","year":"2005","journal-title":"Cancer Sci."},{"key":"2023012508211168700_B25","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/S0092-8674(02)00718-3","article-title":"Small nucleolar RNAs: an abundant group of noncoding RNAs with diverse cellular functions","volume":"109","author":"Kiss","year":"2002","journal-title":"Cell"},{"key":"2023012508211168700_B26","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1261\/rna.2146903","article-title":"New microRNAs from mouse and human","volume":"9","author":"Lagos-Quintana","year":"2003","journal-title":"RNA"},{"key":"2023012508211168700_B27","doi-asserted-by":"crossref","first-page":"159","DOI":"10.2307\/2529310","article-title":"The measurement of observer agreement for categorical data","volume":"33","author":"Landis","year":"1977","journal-title":"Biometrics"},{"key":"2023012508211168700_B28","doi-asserted-by":"crossref","first-page":"843","DOI":"10.1016\/0092-8674(93)90529-Y","article-title":"The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14","volume":"75","author":"Lee","year":"1993","journal-title":"Cell"},{"key":"2023012508211168700_B29","doi-asserted-by":"crossref","first-page":"16635","DOI":"10.1074\/jbc.M412247200","article-title":"Depletion of human micro-RNA miR-125b reveals that it is critical for the proliferation of differentiated cells but not for the down-regulation of putative targets during differentiation","volume":"280","author":"Lee","year":"2005","journal-title":"J. Biol. Chem."},{"key":"2023012508211168700_B30","doi-asserted-by":"crossref","first-page":"e17","DOI":"10.1093\/nar\/gni019","article-title":"An oligonucleotide microarray for microRNA expression analysis based on labeling RNA with quantum dot and nanogold probe","volume":"33","author":"Liang","year":"2005","journal-title":"Nucleic Acids Res."},{"key":"2023012508211168700_B31","doi-asserted-by":"crossref","first-page":"9740","DOI":"10.1073\/pnas.0403293101","article-title":"An oligonucleotide microchip for genome-wide microRNA profiling in human and mouse tissues","volume":"101","author":"Liu","year":"2004","journal-title":"Proc. Natl Acad. Sci. USA"},{"key":"2023012508211168700_B32","doi-asserted-by":"crossref","first-page":"402","DOI":"10.1006\/meth.2001.1262","article-title":"Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method","volume":"25","author":"Livak","year":"2001","journal-title":"Methods"},{"key":"2023012508211168700_B33","first-page":"23","article-title":"Using miRNA expression data for the study of human cancer","volume":"20","author":"Mascellani","year":"2008","journal-title":"MINERVA BIOTEC."},{"key":"2023012508211168700_B34","first-page":"317","article-title":"Non-coding microRNAs hsa-let-7g and hsa-miR-181b are associated with chemoresponse to S-1 in colon cancer","volume":"3","author":"Nakajima","year":"2006","journal-title":"Cancer Genomics Proteomics"},{"key":"2023012508211168700_B35","doi-asserted-by":"crossref","first-page":"3249","DOI":"10.1158\/0008-5472.CAN-08-4710","article-title":"The miR-17\/92 polycistron is up-regulated in sonic hedgehog-driven medulloblastomas and induced by N-myc in sonic hedgehog-treated cerebellar neural precursors","volume":"69","author":"Northcott","year":"2009","journal-title":"Cancer Res."},{"key":"2023012508211168700_B36","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1111\/j.1582-4934.2007.00207.x","article-title":"Differential expression of microRNAs in myometrium and leiomyomas and regulation by ovarian steroids","volume":"12","author":"Pan","year":"2008","journal-title":"J. Cell Mol. Med"},{"key":"2023012508211168700_B37","doi-asserted-by":"crossref","first-page":"R27","DOI":"10.1186\/gb-2007-8-2-r27","article-title":"microRNA expression in the prefrontal cortex of individuals with schizophrenia and schizoaffective disorder","volume":"8","author":"Perkins","year":"2007","journal-title":"Genome Biol"},{"key":"2023012508211168700_B38","doi-asserted-by":"crossref","first-page":"493","DOI":"10.1261\/rna.1295509","article-title":"Impact of normalization on miRNA microarray expression profiling","volume":"15","author":"Pradervand","year":"2009","journal-title":"RNA"},{"key":"2023012508211168700_B39","doi-asserted-by":"crossref","DOI":"10.2202\/1544-6115.1287","article-title":"A comparison of normalization techniques for microRNA microarray data","volume":"7","author":"Rao","year":"2008","journal-title":"Stat. Appl. Genet. Mol. Biol."},{"key":"2023012508211168700_B40","doi-asserted-by":"crossref","first-page":"901","DOI":"10.1038\/35002607","article-title":"The 21-nucleotide let-7 RNA regulates developmental timing in Caenorhabditis elegans","volume":"403","author":"Reinhart","year":"2000","journal-title":"Nature"},{"key":"2023012508211168700_B41","doi-asserted-by":"crossref","first-page":"e43","DOI":"10.1093\/nar\/gnh040","article-title":"A high-throughput method to monitor the expression of microRNA precursors","volume":"32","author":"Schmittgen","year":"2004","journal-title":"Nucleic Acids Res."},{"key":"2023012508211168700_B42","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.ymeth.2007.09.006","article-title":"Real-time PCR quantification of precursor and mature microRNA","volume":"44","author":"Schmittgen","year":"2008","journal-title":"Methods"},{"key":"2023012508211168700_B43","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/S0012-1606(03)00208-2","article-title":"Temporal regulation of microRNA expression in Drosophila melanogaster mediated by hormonal signals and broad-Complex gene activity","volume":"259","author":"Sempere","year":"2003","journal-title":"Dev. Biol."},{"key":"2023012508211168700_B44","doi-asserted-by":"crossref","first-page":"3753","DOI":"10.1158\/0008-5472.CAN-04-0637","article-title":"Reduced expression of the let-7 microRNAs in human lung cancers in association with shortened postoperative survival","volume":"64","author":"Takamizawa","year":"2004","journal-title":"Cancer Res."},{"key":"2023012508211168700_B45","first-page":"113","article-title":"Prognostic values of microRNAs in colorectal cancer","volume":"2","author":"Xi","year":"2006","journal-title":"Biomark. Insights"},{"key":"2023012508211168700_B46","doi-asserted-by":"crossref","first-page":"2014","DOI":"10.1158\/1078-0432.CCR-05-1853","article-title":"Differentially regulated micro-RNAs and actively translated messenger RNA transcripts by tumor suppressor p53 in colon cancer","volume":"12","author":"Xi","year":"2006","journal-title":"Clin. Cancer Res."},{"key":"2023012508211168700_B47","doi-asserted-by":"crossref","first-page":"1668","DOI":"10.1261\/rna.642907","article-title":"Systematic analysis of microRNA expression of RNA extracted from fresh frozen and formalin-fixed paraffin-embedded samples","volume":"13","author":"Xi","year":"2007","journal-title":"RNA"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/26\/2\/228\/48855518\/bioinformatics_26_2_228.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/26\/2\/228\/48855518\/bioinformatics_26_2_228.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,25]],"date-time":"2023-01-25T08:21:44Z","timestamp":1674634904000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/26\/2\/228\/210479"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2009,11,23]]},"references-count":47,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2010,1,15]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btp655","relation":{},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2010,1,15]]},"published":{"date-parts":[[2009,11,23]]}}}