Suchergebnisse - "Microarray data"

Predicting survival from microarray data—a comparative study von Bøvelstad, H.M., Nygård, S., Størvold, H.L., Aldrin, M., Borgan, Ø., Frigessi, A., Lingjærde, O.C.

“… Motivation: Survival prediction from gene expression data and other high-dimensional genomic data has been subject to much research during the last years …”
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Genetic algorithm-based feature selection with manifold learning for cancer classification using microarray data von Wang, Zixuan, Zhou, Yi, Takagi, Tatsuya, Song, Jiangning, Tian, Yu-Shi, Shibuya, Tetsuo

“… Background Microarray data have been widely utilized for cancer classification. The main characteristic of microarray data is “large p and small n …”
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Identifying mislabeled and contaminated DNA methylation microarray data: an extended quality control toolset with examples from GEO von Heiss, Jonathan A., Just, Allan C.

“… Background Mislabeled, contaminated or poorly performing samples can threaten power in methylation microarray analyses or even result in spurious associations …”
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Mining Affymetrix microarray data for long non-coding RNAs: altered expression in the nucleus accumbens of heroin abusers von Michelhaugh, Sharon K, Lipovich, Leonard, Blythe, Jason, Jia, Hui, Kapatos, Gregory, Bannon, Michael J

“… J. Neurochem. (2011) 116, 459-466. ABSTRACT: Although recent data suggest that some long non-coding RNAs (lncRNAs) exert widespread effects on gene expression …”
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Logistic regression for disease classification using microarray data: model selection in a large p and small n case von Liao, J.G., Chin, Khew-Voon

“… Motivation: Logistic regression is a standard method for building prediction models for a binary outcome and has been extended for disease classification with microarray data by many authors. A feature (gene …”
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Mfuzz: a software package for soft clustering of microarray data von Kumar, Lokesh, E Futschik, Matthias

“… For the analysis of microarray data, clustering techniques are frequently used. Most of such methods are based on hard clustering of data wherein one gene (or sample …”
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Identification and analysis of key genes associated with ulcerative colitis based on DNA microarray data von Song, Ruifeng, Li, Ya, Hao, Weiwei, Wang, Bingxue, Yang, Lei, Xu, Feng

“… ), 8 advanced-stage UC (AUC), and 5 control subjects, were downloaded from the Gene Expression Omnibus database under the accession number of GSE9452 …”
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Integrating gene selection and deep learning for enhanced Autisms' disease prediction: a comparative study using microarray data von Abdelwahab, Mahmoud M., Al-Karawi, Khamis A., Semary, H. E.

“… The study used microarray data to provide a novel approach that integrated gene selection techniques with deep learning models to improve the accuracy of ASD prediction …”
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Should We Abandon the t-Test in the Analysis of Gene Expression Microarray Data: A Comparison of Variance Modeling Strategies von Jeanmougin, Marine, de Reynies, Aurelien, Marisa, Laetitia, Paccard, Caroline, Nuel, Gregory, Guedj, Mickael

“… The main statistical approach to select genes differentially expressed between two groups is to apply a t-test, which is subject of criticism in the literature …”
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ARACNe-based inference, using curated microarray data, of Arabidopsis thaliana root transcriptional regulatory networks von Chávez Montes, Ricardo A, Coello, Gerardo, González-Aguilera, Karla L, Marsch-Martínez, Nayelli, de Folter, Stefan, Alvarez-Buylla, Elena R

“… Results In this study we present a simple bioinformatics methodology that uses public, carefully curated microarray data and the mutual information algorithm ARACNe in order to obtain a database …”
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Intelligent Microarray Data Analysis through Non-negative Matrix Factorization to Study Human Multiple Myeloma Cell Lines von Casalino, Gabriella, Coluccia, Mauro, Pati, Maria L., Pannunzio, Alessandra, Vacca, Angelo, Scilimati, Antonio, Perrone, Maria G.

“… Microarray data are a kind of numerical non-negative data used to collect gene expression profiles …”
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Microarray Data Normalization and Robust Detection of Rhythmic Features von Larriba, Yolanda, Rueda, Cristina, Fernández, Miguel A, Peddada, Shyamal D

“… Data derived from microarray technologies are generally subject to various sources of noise and accordingly the raw data are pre-processed before formally analysed …”
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A comparative study of nonlinear manifold learning methods for cancer microarray data classification von Orsenigo, Carlotta, Vercellis, Carlo

“… ► Methods were applied for dimensionality reduction in microarray data classification. ► LLE-based classifier emerged as the most effective method …”
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Variable selection for discriminant analysis with Markov random field priors for the analysis of microarray data von Stingo, Francesco C., Vannucci, Marina

“… Here, we consider the typical problem of classifying subjects according to phenotypes via gene expression data and propose a method that incorporates variable selection into the inferential procedure …”
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Microarray data and pathway analyses of peripheral blood mononuclear cells from healthy subjects after a three weeks grape-rich diet von Milella, Rosa Anna, Gasparro, Marica, Alagna, Fiammetta, Cardone, Maria Francesca, Rotunno, Silvia, Ammollo, Concetta Tiziana, Semeraro, Fabrizio, Tullo, Apollonia, Marzano, Flaviana, Catalano, Domenico, Antonacci, Donato, Colucci, Mario, D'Elia, Domenica

“… of healthy subjects after 21 days of fresh table grape-rich diet and after an additional 28-day washout. Several hundreds of genes were differentially expressed after grape intake or after washout …”
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Workflows for microarray data processing in the Kepler environment von Stropp, Thomas, McPhillips, Timothy, Ludäscher, Bertram, Bieda, Mark

“… Background Microarray data analysis has been the subject of extensive and ongoing pipeline development due to its complexity, the availability of several options at each analysis step …”
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Integrated analysis of the heterogeneous microarray data von Yi, Sung Gon, Park, Taesung

“… Thus, it is important to analyze microarray data together to derive a combined conclusion after accounting for heterogeneity among data sets …”
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A comparison of normalization techniques for microRNA microarray data von Rao, Youlan, Lee, Yoonkyung, Jarjoura, David, Ruppert, Amy S, Liu, Chang-Gong, Hsu, Jason C, Hagan, John P

“… ) microarray data, which are subject to similar sources of measurement error. In this paper, we compare the performance of cyclic loess, quantile normalization, median …”
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Microarray data can predict diurnal changes of starch content in the picoalga Ostreococcus von Sorokina, Oksana, Corellou, Florence, Dauvillée, David, Sorokin, Anatoly, Goryanin, Igor, Ball, Steven, Bouget, François-Yves, Millar, Andrew J

“… Background The storage of photosynthetic carbohydrate products such as starch is subject to complex regulation, effected at both transcriptional and post-translational levels …”
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SaDA: From Sampling to Data Analysis—An Extensible Open Source Infrastructure for Rapid, Robust and Automated Management and Analysis of Modern Ecological High-Throughput Microarray Data von Singh, Kumar, Thual, Dominique, Spurio, Roberto, Cannata, Nicola

“… One of the most crucial characteristics of day-to-day laboratory information management is the collection, storage and retrieval of information about research subjects and environmental or biomedical samples …”
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