Building and analysing genome-wide gene disruption networks

被引:51
作者
Rung, J
Schlitt, T
Brazma, A
Freivalds, K
Vilo, J
机构
[1] European Bioinformat Inst, Cambridge CB10 1SD, England
[2] Univ Latvia, Inst Math & Comp Sci, LV-1459 Riga, Latvia
关键词
gene networks; microarrays; yeast; graph visualisation;
D O I
10.1093/bioinformatics/18.suppl_2.S202
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Motivation: Microarray experiments comparing expression levels of all genes in yeast for hundreds of mutants allow us to examine properties of gene regulatory networks on a genomic scale. We can investigate questions such as network modularity, connectivity, and look for genes with particular roles in the network structure. Results: We have built genome-wide disruption networks for yeast, using a representation of gene expression data as directed labelled graphs. Nodes represent genes and arcs connect nodes if the disruption of the source gene significantly alters the expression of the target gene. We are interested in features of the resulting disruption networks that are robust over a range of significance cutoffs. The networks show a significant overlap with analogous networks constructed from scientific literature. In disruption networks the number of arcs adjacent to different nodes are distributed roughly according to a power-law, like in many complex systems where the robustness against perturbations is important. The networks are dominated by a single large component and do not have an obvious modular structure. Genes with the highest outdegrees often encode proteins with regulatory functions, whereas genes with the highest indegrees are predominantly involved in metabolism. The local structure of the networks is meaningful, genes involved in the same cellular processes are close together in the network.
引用
收藏
页码:S202 / S210
页数:9
相关论文
共 19 条
[1]   Statistical mechanics of complex networks [J].
Albert, R ;
Barabási, AL .
REVIEWS OF MODERN PHYSICS, 2002, 74 (01) :47-97
[2]  
[Anonymous], PACIFIC S BIOCOMPUT
[3]  
[Anonymous], P LATVIAN ACAD SCI
[4]   Emergence of scaling in random networks [J].
Barabási, AL ;
Albert, R .
SCIENCE, 1999, 286 (5439) :509-512
[5]   Highly optimized tolerance: A mechanism for power laws in designed systems [J].
Carlson, JM ;
Doyle, J .
PHYSICAL REVIEW E, 1999, 60 (02) :1412-1427
[6]   YPD™, PombePD™ and WormPD™:: model organism volumes of the BioKnowledge™ Library, an integrated resource for protein information [J].
Costanzo, MC ;
Crawford, ME ;
Hirschman, JE ;
Kranz, JE ;
Olsen, P ;
Robertson, LS ;
Skrzypek, MS ;
Braun, BR ;
Hopkins, KL ;
Kondu, P ;
Lengieza, C ;
Lew-Smith, JE ;
Tillberg, M ;
Garrels, JI .
NUCLEIC ACIDS RESEARCH, 2001, 29 (01) :75-79
[7]   Wrestling with pleiotropy: genomic and topological analysis of the yeast gene expression network [J].
Featherstone, DE ;
Broadie, K .
BIOESSAYS, 2002, 24 (03) :267-274
[8]  
FREIVALDS K, 2001, IN PRESS P GRAPH DRA
[9]  
FRIEDMAN N, 2000, RECOMB 2000
[10]   Functional discovery via a compendium of expression profiles [J].
Hughes, TR ;
Marton, MJ ;
Jones, AR ;
Roberts, CJ ;
Stoughton, R ;
Armour, CD ;
Bennett, HA ;
Coffey, E ;
Dai, HY ;
He, YDD ;
Kidd, MJ ;
King, AM ;
Meyer, MR ;
Slade, D ;
Lum, PY ;
Stepaniants, SB ;
Shoemaker, DD ;
Gachotte, D ;
Chakraburtty, K ;
Simon, J ;
Bard, M ;
Friend, SH .
CELL, 2000, 102 (01) :109-126