Computational analysis of microarray gene expression profiles of lung cancer

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F44555601%3A13440%2F16%3A43887623" target="_blank" >RIV/44555601:13440/16:43887623 - isvavai.cz</a>
Result on the web
<a href="http://www.biopolymers.org.ua/pdf/32/1/070/biopolym.cell-2016-32-1-070-en.pdf" target="_blank" >http://www.biopolymers.org.ua/pdf/32/1/070/biopolym.cell-2016-32-1-070-en.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.7124/bc.00090F" target="_blank" >10.7124/bc.00090F</a>

Result language
angličtina
Original language name
Computational analysis of microarray gene expression profiles of lung cancer
Original language description
The article is dedicated to optimization of the DNA microarray data processing, which is aimed at improving the quality of object clustering. Methods. Data preprocessing was performed with program R using Bioconductor package. Modelling the clustering process was made in the software environment KNIME using the program WEKA functions. Results. The data preprocessing is shown to be optimal while using such techniques as the background correction rma method, quantile normalization, mas PM correction and summarization by mas method. The simulation results have demonstrated a high effectiveness of the clustering algorithm Sota for this category of data. Conclusion. Improvement of the quality of biological object clustering is possible by means of hybridization and optimization of the methods and algorithms at different stages of data processing.
Czech name
—
Czech description
—

Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
—

Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Similar results(10)