Literature DB >> 12795415

Statistical approach to DNA chip analysis.

N M Svrakic1, O Nesic, M R K Dasu, D Herndon, J R Perez-Polo.   

Abstract

Statistical methods for analyzing data from DNA microarray experiments are reviewed. Specifically, we discuss common experimental setups, methods for data reduction and clustering, and analysis of time-course experiments. While early microarray studies focused mainly on the basic methodological and technical aspects of DNA arrays, emphasis has shifted to biological, medical, and clinical applications. We mention several of these and present results from our recent research as illustrative examples. New developments in this ever-growing field are outlined.

Mesh:

Year:  2003        PMID: 12795415     DOI: 10.1210/rp.58.1.75

Source DB:  PubMed          Journal:  Recent Prog Horm Res        ISSN: 0079-9963


  5 in total

1.  Functional development of the mammary gland: use of expression profiling and trajectory clustering to reveal changes in gene expression during pregnancy, lactation, and involution.

Authors:  Michael C Rudolph; James L McManaman; Larry Hunter; Tzulip Phang; Margaret C Neville
Journal:  J Mammary Gland Biol Neoplasia       Date:  2003-07       Impact factor: 2.673

2.  Arrayed cellular microenvironments for identifying culture and differentiation conditions for stem, primary and rare cell populations.

Authors:  David A Brafman; Shu Chien; Karl Willert
Journal:  Nat Protoc       Date:  2012-03-15       Impact factor: 13.491

3.  Gene expression changes with time in skeletal muscle of severely burned children.

Authors:  Mohan R K Dasu; Robert E Barrow; David N Herndon
Journal:  Ann Surg       Date:  2005-04       Impact factor: 12.969

4.  Microarray data analysis and mining tools.

Authors:  Saravanakumar Selvaraj; Jeyakumar Natarajan
Journal:  Bioinformation       Date:  2011-04-22

5.  Time-course microarray analysis for identifying candidate genes involved in obesity-associated pathological changes in the mouse colon.

Authors:  Yun Jung Bae; Sung-Eun Kim; Seong Yeon Hong; Taesun Park; Sang Gyu Lee; Myung-Sook Choi; Mi-Kyung Sung
Journal:  Genes Nutr       Date:  2016-11-22       Impact factor: 5.523

  5 in total

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