Results 141 to 150 of about 557,537 (198)

Glioma immune microenvironment composition calculator (GIMiCC): a method of estimating the proportions of eighteen cell types from DNA methylation microarray data. [PDF]

Acta Neuropathol Commun
Pike SC, Wiencke JK, Zhang Z, Molinaro AM, Hansen HM, Koestler DC, Christensen BC, Kelsey KT, Salas LA.   +8 more
europepmc   +1 more source

Enhancement of Classifier Performance with Adam and RanAdam Hyper-Parameter Tuning for Lung Cancer Detection from Microarray Data-In Pursuit of Precision. [PDF]

Bioengineering (Basel)
M S K, Rajaguru H, Nair AR.
europepmc   +1 more source

Meta-analysis of microarray data to determine gene indicators involved in cisplatin resistance in non-small cell lung cancer. [PDF]

Cancer Rep (Hoboken)
Sheikhshabani SH, Modarres P, Ghafouri-Fard S, Amini-Farsani Z, Khodaee L, Shaygan N, Amini-Farsani Z, Omrani MD.   +7 more
europepmc   +1 more source

Identification of PPARG as key gene to link coronary atherosclerosis disease and rheumatoid arthritis via microarray data analysis. [PDF]

PLoS One
Zhang Z, Chen Y, Fu X, Chen L, Wang J, Zheng Q, Zhang S, Zhu X.   +7 more
europepmc   +1 more source

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Computational analysis of microarray data

Nature Reviews Genetics, 2001
Microarray experiments are providing unprecedented quantities of genome-wide data on gene-expression patterns. Although this technique has been enthusiastically developed and applied in many biological contexts, the management and analysis of the millions of data points that result from these experiments has received less attention.
John Quackenbush
openaire   +4 more sources

Microarray data normalization and transformation

Nature Genetics, 2002
Underlying every microarray experiment is an experimental question that one would like to address. Finding a useful and satisfactory answer relies on careful experimental design and the use of a variety of data-mining tools to explore the relationships between genes or reveal patterns of expression.
John Quackenbush
openaire   +4 more sources

Microarray Data Analysis Protocol

2021
Microarrays are broadly used in the omic investigation and have several areas of applications in biology and medicine, providing a significant amount of data for a single experiment. Different kinds of microarrays are available, identifiable by characteristics such as the type of probes, the surface used as support, and the method used for the target ...
Agapito G, Arbitrio M
openaire   +3 more sources

Analyzing Microarray Data

Cold Spring Harbor Protocols, 2016
Because there is no widely used software for analyzing RNA-seq data that has a graphical user interface, this protocol provides an example of analyzing microarray data using Babelomics. This analysis entails performing quantile normalization and then detecting differentially expressed genes associated with the transgenesis of a human oncogene c-Myc in ...
Hung, Jui-Hung, Weng, Zhiping
openaire   +3 more sources

Unfolding of Microarray Data

Journal of Computational Biology, 2001
The use of DNA microarrays for the analysis of complex biological samples is becoming a mainstream part of biomedical research. One of the most commonly used methods compares the relative abundance of mRNA in two different samples by probing a single DNA microarray simultaneously.
A B, Goryachev, P F, Macgregor, A M, Edwards   +2 more
openaire   +2 more sources

Standards for Microarray Data

Science, 2002
One of the underlying principles of scientific publication in peer-reviewed journals has been the requirement that the authors make available the data and materials necessary for a reader to reproduce the experiment or analysis and to determine whether the data support the authors' conclusions.
Catherine A, Ball, Gavin, Sherlock, Helen, Parkinson, Philippe, Rocca-Sera, Catherine, Brooksbank, Helen C, Causton, Duccio, Cavalieri, Terry, Gaasterland, Pascal, Hingamp, Frank, Holstege, Martin, Ringwald, Paul, Spellman, Christian J, Stoeckert, Jason E, Stewart, Ronald, Taylor, Alvis, Brazma, John, Quackenbush   +16 more
openaire   +2 more sources