Finding temporal gene expression patterns for translational research.
Translational research of time-series of gene-expression microarray datasets makes use on gene expression profiles that have been obtained at different points in time. Our web-based multi-user program helps a researcher find temporal patterns like peaks in large pre-selected microarray data sets that include data from different but related studies in publicly available databases. If all studies use the same platform, data can be combined for a meta-analysis type approach. For combination of data from different platforms we allow only Affymetrix GeneChips, for which a method for pooling of information exists. To search for time patterns, the data are transformed into an abstract layer that is independent from the particular selection of time point in the individual studies.
Medical and Bioinformatics Graduate Program, Grand Valley State University, Allendale, MI, USA.
Guenter
G
Tusch
Olvi
O
Tolea
Yuka
Y
Kutsumi
Vincent K
VK
Sam
Lakshmi
L
Mamidi
D000465:Algorithms; D001185:Artificial Intelligence; D057225:Data Mining / Q000379:methods*; D003628:Database Management Systems; D030541:Databases, Genetic; D020869:Gene Expression Profiling / Q000379:methods*; D005786:Gene Expression Regulation / Q000235:genetics; D008498:Medical Record Linkage / Q000379:methods; D015201:Meta-Analysis as Topic; D009323:Natural Language Processing; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D012984:Software; D057170:Translational Research, Biomedical / Q000379:methods*