Functional interpretation of microarray experiments

被引:55
作者
Dopazo, Joaquin [1 ]
机构
[1] CIPF, INB, Dept Bioinformat, E-46013 Valencia, Spain
关键词
D O I
10.1089/omi.2006.10.398
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Over the past few years, due to the popularisation of high-throughput methodologies such as DNA microarrays, the possibility of obtaining experimental data has increased significantly. Nevertheless, the interpretation of the results, which involves translating these data into useful biological knowledge, still remains a challenge. The methods and strategies used for this interpretation are in continuous evolution and new proposals are constantly arising. Initially, a two-step approach was used in which genes of interest were initially selected, based on thresholds that consider only experimental values, and then in a second, independent step the enrichment of these genes in biologically relevant terms, was analysed. For different reasons, these methods are relatively poor in terms of performance and a new generation of procedures, which draw inspiration from systems biology criteria, are currently under development. Such procedures, aim to directly test the behaviour of blocks of functionally related genes, instead of focusing on single genes.
引用
收藏
页码:398 / 410
页数:13
相关论文
共 68 条
[21]  
DRAGHICL S, 2003, DATA ANAL TOOLS DNA
[22]   Cluster analysis and display of genome-wide expression patterns [J].
Eisen, MB ;
Spellman, PT ;
Brown, PO ;
Botstein, D .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 1998, 95 (25) :14863-14868
[23]   Integrating 'omic' information: a bridge between genomics and systems biology [J].
Ge, H ;
Walhout, AJM ;
Vidal, M .
TRENDS IN GENETICS, 2003, 19 (10) :551-560
[24]   Testing association of a pathway with survival using gene expression data [J].
Goeman, JJ ;
Oosting, J ;
Cleton-Jansen, AM ;
Anninga, JK ;
van Houwelingen, HC .
BIOINFORMATICS, 2005, 21 (09) :1950-1957
[25]   A global test for groups of genes: testing association with a clinical outcome [J].
Goeman, JJ ;
van de Geer, SA ;
de Kort, F ;
van Houwelingen, HC .
BIOINFORMATICS, 2004, 20 (01) :93-99
[26]   Molecular classification of cancer: Class discovery and class prediction by gene expression monitoring [J].
Golub, TR ;
Slonim, DK ;
Tamayo, P ;
Huard, C ;
Gaasenbeek, M ;
Mesirov, JP ;
Coller, H ;
Loh, ML ;
Downing, JR ;
Caligiuri, MA ;
Bloomfield, CD ;
Lander, ES .
SCIENCE, 1999, 286 (5439) :531-537
[27]   Genome-wide prediction of mammalian enhancers based on analysis of transcription-factor binding affinity [J].
Hallikas, O ;
Palin, K ;
Sinjushina, N ;
Rautiainen, R ;
Partanen, J ;
Ukkonen, E ;
Taipale, J .
CELL, 2006, 124 (01) :47-59
[28]   New challenges in gene expression data analysis and the extended GEPAS [J].
Herrero, J ;
Vaquerizas, JM ;
Al-Shahrour, F ;
Conde, L ;
Mateos, A ;
Santoyo, J ;
Díaz-Uriarte, R ;
Dopazo, J .
NUCLEIC ACIDS RESEARCH, 2004, 32 :W485-W491
[29]   GEPAS:: a web-based resource for microarray gene expression data analysis [J].
Herrero, J ;
Al-Shahrour, F ;
Díaz-Uriarte, R ;
Mateos, A ;
Vaquerizas, JM ;
Santoyo, J ;
Dopazo, J .
NUCLEIC ACIDS RESEARCH, 2003, 31 (13) :3461-3467
[30]   Identifying biological themes within lists of genes with EASE [J].
Hosack, DA ;
Dennis, G ;
Sherman, BT ;
Lane, HC ;
Lempicki, RA .
GENOME BIOLOGY, 2003, 4 (10)