Finding Temporal Gene Expression Patterns for Translational Research

被引：0

作者：

Tusch, Guenter ^{[1
]}

Tole, Olvi ^{[1
]}

Kutsumi, Yuka ^{[1
]}

Sam, Vincent K. ^{[1
]}

Mamidi, Lakshmi ^{[1
]}

机构：

[1] Grand Valley State Univ, Med & Bioinformat Grad Program, Allendale, MI 49401 USA

来源：

MEDINFO 2013: PROCEEDINGS OF THE 14TH WORLD CONGRESS ON MEDICAL AND HEALTH INFORMATICS, PTS 1 AND 2 | 2013年 / 192卷

关键词：

Research; education; enhancing biological; clinical and epidemiological research and trials; bioinformatics; translational research;

D O I：

10.3233/978-1-61499-289-9-1173

中图分类号：

R19 [保健组织与事业（卫生事业管理）];

学科分类号：

摘要：

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.

引用

页码：1173 / 1173

页数：1

共 4 条

[1]

Morris J.S., 2006, Meta-Analysis in Genetics, P1

[2]

O'Connor Martin J, 2009, Int J Med Inform, V78 Suppl 1, pS77, DOI 10.1016/j.ijmedinf.2008.07.013

[3] Key Issues in Conducting a Meta-Analysis of Gene Expression Microarray Datasets [J].