Reconstruction of large-scale regulatory networks based on perturbation graphs and transitive reduction: Improved methods and their evaluation

BMC Systems Biology

Volumn 7, Issue , 2013, Pages

  Pinna, Andrea ^a   Heise, Sandra ^b   Flassig, Robert J ^b   Fuente, Alberto D L ^c   Klamt, Steffen ^b  

^a CENTER FOR ADVANCED STUDIES   (Italy)

^b MAX PLANCK INSTITUTE FOR DYNAMICS OF COMPLEX TECHNICAL SYSTEMS   (Germany)

^c LEIBNIZ INSTITUTE FOR FARM ANIMAL BIOLOGY FBN   (Germany)

Author keywords

Causal networks; Gene network inference; Graph theory; Interaction graphs; Perturbation experiments; Reverse engineering; Saccharomyces cerevisiae; Transcriptional regulation; Transitive reduction; Yeast

Indexed keywords

SACCHAROMYCES CEREVISIAE;

ARTICLE; COMPUTER GRAPHICS; EVALUATION STUDY; GENE INACTIVATION; GENE REGULATORY NETWORK; GENETICS; METHODOLOGY; SACCHAROMYCES CEREVISIAE; SYSTEMS BIOLOGY; PROCEDURES;

COMPUTER GRAPHICS; GENE KNOCKOUT TECHNIQUES; GENE REGULATORY NETWORKS; SACCHAROMYCES CEREVISIAE; SYSTEMS BIOLOGY;

EID: 84881178444     PISSN: None     EISSN: 17520509     Source Type: Journal    
DOI: 10.1186/1752-0509-7-73     Document Type: Article

References (50)

1. Markowetz F, Spang R. Inferring cellular networks-a review. BMC Bioinformatics 2007, 8(Suppl 6):S5. 10.1186/1471-2105-8-S6-S5, 2230506, 18269699.
2. Gardner T, Faith J. Reverse-engineering transcription control networks. Phys Life Rev 2005, 2:65-88. 10.1016/j.plrev.2005.01.001, 20416858.
3. Bansal M, Belcastro V, Ambesi-Impiombato A, di Bernardo D. How to infer gene networks from expression profiles. Mol Syst Biol 2007, 3:78. 1828749, 17299415.
4. Schlitt T, Brazma A. Current approaches to gene regulatory network modelling. BMC Bioinformatics 2007, 8(Suppl 6):S9. 10.1186/1471-2105-8-S6-S9, 2099501, 18047732.
5. De Smet R, Marchal K. Advantages and limitations of current network inference methods. Nat Rev Microbiol 2010, 8(10):717-729.
6. Marbach D, Costello JC, Kuffner R, Vega NM, Prill RJ, Camacho DM, Allison KR, Kellis M, Collins JJ, Stolovitzky G, et al. Wisdom of crowds for robust gene network inference. Nat Methods 2012, 9(8):796-804. 10.1038/nmeth.2016, 3512113, 22796662.
7. Tibshirani R. Regression shrinkage and selection via the lasso. J R Stat Soc, Ser B 1994, 58:267-288.
8. de la Fuente A, Bing N, Hoeschele I, Mendes P. Discovery of meaningful associations in genomic data using partial correlation coefficients. Bioinformatics 2004, 20:3565-3574. 10.1093/bioinformatics/bth445, 15284096.
9. Prill R, Marbach D, Saez-Rodriguez J, Sorger P, Alexopoulos L, Xue X, Clarke N, Altan-Bonnet G, Stolovitzky G. Towards a rigorous assessment of systems biology models: the DREAM3 challenges. PLoS ONE 2010, 5:e9202. 10.1371/journal.pone.0009202, 2826397, 20186320.
10. Watkinson J, Lian K, Wang X, Zheng T, Anastassiou D. Inference of regulatory gene interactions from expression data using three-way mutual information. Ann New York Acad Sci 2009, 1158:302-313.
11. Margolin AA, Nemenman I, Basso K, Wiggins C, Stolovitzky G, Favera RD, Califano A. ARACNE: an algorithm for the reconstruction of gene regulatory networks in a mammalian cellular context. BMC Bioinformatics 2006, 7(Suppl 1):S7. 10.1186/1471-2105-7-S1-S7, 1764484, 17254312.
12. Kueffner R, Petri T, Tavakkolkhah P, Windhager L, Zimmer R. Inferring Gene Regulatory Networks by ANOVA. Bioinformatics 2012, 28:1376-1382. 10.1093/bioinformatics/bts143, 22467911.
13. Friedman N, Linial M, Nachman I, Pe'er D. Using Bayesian networks to analyze expression data. J Comput Biol 2000, 7:601-620. 10.1089/106652700750050961, 11108481.
14. Chiquet J, Grandvalet Y, Ambroise C. Inferring multiple graphical structures. Stat Comput 2011, 21(4):537-553.
15. Huynh-Thu V, Irrthum A, Wehenkel L, Geurts P. Inferring regulatory networks from expression data using tree-based methods. PLoS ONE 2010, 5(9):e12776. 10.1371/journal.pone.0012776, 2946910, 20927193.
16. Nelander S, Wang W, Nilsson B, She QB, Pratilas C, Rosen N, Gennemark P, Sander C. Models from experiments: combinatorial drug perturbations of cancer cells. Mol Syst Biol 2008, 4:216. 2564730, 18766176.
17. Durzinsky M, Wagler A, Weismantel R, Marwan W. Automatic reconstruction of molecular and genetic networks from discrete time series data. BioSystems 2008, 93(3):181-90. 10.1016/j.biosystems.2008.04.001, 18524471.
18. Akutsu T, Kuhara S, Maruyama O, Miyano S. Identification of genetic networks by strategic gene disruptions and gene overexpressions under a boolean model. Theor Comput Sci 2003, 298:235-251.
19. Rodriguez JS, Alexopoulos L, Epperlein J, Samaga R, Lauffenburger D, Klamt S, Sorger P. Discrete logic modelling as a means to link protein signalling networks with functional analysis of mammalian signal transduction. Mol Syst Biol 2009, 5:331. 2824489, 19953085.
20. The DREAM Project. http://www.the-dream-project.org.
21. Marbach D, Prill RJ, Schaffter T, Mattiussi C, Floreano D, Stolovitzky G. Revealing strengths and weaknesses of methods for gene network inference. Proc Natl Acad Sci 2010, 107(14):6286-6291. 10.1073/pnas.0913357107, 2851985, 20308593.
22. Meyer P, Alexopoulos L, Bonk T, Califano A, Cho C, de la F, de Graaf D, Hartemink A, Hoeng J, Ivanov N, Koeppl H, Linding R, Marbach D, Norel R, Peitsch M, Rice J, Royyuru A, Schacherer F, Sprengel J, Stolle K, Vitkup D, Stolovitzky G. Verification of systems biology research in the age of collaborative competition. Nat Biotechnol 2011, 29:811-815. 10.1038/nbt.1968, 21904331.
23. Stumpf MP, Thorne T, de Silva E, Stewart R, An HJ, Lappe M, Wiuf C. Estimating the size of the human interactome. Proc Natl Acad Sci 2008, 105(19):6959-6964. 10.1073/pnas.0708078105, 2383957, 18474861.
24. de la Fuente A, Brazhnik P, Mendes P. Linking the genes: inferring quantitative gene networks from microarray data. Trends Genet 2002, 18(8):395-398. 10.1016/S0168-9525(02)02692-6, 12142007.
25. Kholodenko BN, Kiyatkin A, Bruggeman FJ, Sontag E, Westerhoff HV, Hoek JB. Untangling the wires: a strategy to trace functional interactions in signaling and gene networks. Proc Natl Acad Sci 1284, 99(20):1-12846.
26. van Someren EP, Wessels LF, Reinders MJ. Linear modeling of genetic networks from experimental data. Proc Int Conf Intell Syst Mol Biol 2000, 8:355-366.
27. Smith VA, Jarvis ED, Hartemink AJ. Evaluating functional network inference using simulations of complex biological systems. Bioinformatics 2002, 18(Suppl 1):S216-S224. 10.1093/bioinformatics/18.suppl_1.S216, 12169550.
28. Mendes P, Sha W, Ye K. Artificial gene networks for objective comparison of analysis algorithms. Bioinformatics 2003, 19(Suppl 2):ii122-ii129. 10.1093/bioinformatics/btg1069, 14534181.
29. Soranzo N, Bianconi G, Altafini C. Comparing association network algorithms for reverse engineering of large-scale gene regulatory networks: synthetic versus real data. Bioinformatics 2007, 23(13):1640-1647. 10.1093/bioinformatics/btm163, 17485431.
30. Pinna A, Soranzo N, de la F. From knockouts to networks: establishing direct cause-effect relationships through graph analysis. PLoS ONE 2010, 5(10):e12912. 10.1371/journal.pone.0012912, 2952592, 20949005.
31. Klamt S, Flassig RJ, Sundmacher K. TRANSWESD: inferring cellular networks with transitive reduction. Bioinformatics 2010, 26(17):2160-2168. 10.1093/bioinformatics/btq342, 2922889, 20605927.
32. Winzeler EA, Shoemaker DD, Astromoff A, Liang H, Anderson K, Andre B, Bangham R, Benito R, Boeke JD, Bussey H, Chu AM, Connelly C, Davis K, Dietrich F, Dow SW, El Bakkoury M, Foury F, Friend SH, Gentalen E, Giaever G, Hegemann JH, Jones T, Laub M, Liao H, Liebundguth N, Lockhart DJ, Lucau-Danila A, Lussier M, M'Rabet N, Menard P, Mittmann M, Pai C, Rebischung C, Revuelta JL, Riles L, Roberts CJ, Ross-MacDonald P, Scherens B, Snyder M, Sookhai-Mahadeo S, Storms RK, Veronneau S, Voet M, Volckaert G, Ward TR, Wysocki R, Yen GS, Yu K, Zimmermann K, Philippsen P, Johnston M, Davis RW. Functional characterization of the S. cerevisiae genome by gene deletion and parallel analysis. Science 1999, 285(5429):901-906. 10.1126/science.285.5429.901, 10436161.
33. Dolgin E. Mouse library set to be knockout. Nature 2011, 474(7351):262-263. 10.1038/474262a, 21677718.
34. Hu Z, Killion PJ, Iyer VR. Genetic reconstruction of a functional transcriptional regulatory network. Nat Genet 2007, 39(5):683-687. 10.1038/ng2012, 17417638.
35. Reimand J, Vaquerizas JM, Todd AE, Vilo J, Luscombe NM. Comprehensive reanalysis of transcription factor knockout expression data in Saccharomyces cerevisiae reveals many new targets. Nucleic Acid Res 2010, 38(14):4768-4777. 10.1093/nar/gkq232, 2919724, 20385592.
36. Bošnački D, Odenbrett MR, Wijs A, Ligtenberg W, Hilbers P. Efficient reconstruction of biological networks via transitive reduction on general purpose graphics processors. BMC Bioinformatics 2012, 13:281. 10.1186/1471-2105-13-281, 3583792, 23110660.
37. Tresch A, Beissbarth T, Sültmann H, Kuner R, Poustka A, Buness A. Discrimination of direct and indirect interactions in a network of regulatory effects. J Comput Biol 2007, 14(9):1217-1228. 10.1089/cmb.2007.0085, 17990974.
38. Wagner A. How to reconstruct a large genetic network from n gene perturbations in fewer than n2 easy steps. Bioinformatics 2001, 17(12):1183-1197. 10.1093/bioinformatics/17.12.1183, 11751227.
39. Kachalo S, Zhang R, Sontag E, Albert R, DasGupta B. NET-SYNTHESIS: a software for synthesis, inference and simplification of signal transduction networks. Bioinformatics 2008, 24(2):293-295. 10.1093/bioinformatics/btm571, 18033793.
40. Klamt S, Kamp AV. Computing paths and cycles in biological interaction graphs. BMC Bioinformatics 2009, 10:181. 10.1186/1471-2105-10-181, 2708159, 19527491.
41. Pinna A, Soranzo N, Hoeschele I, de la F. Simulating systems genetics data with SysGenSIM. Bioinformatics 2011, 27(17):2459-2462. 10.1093/bioinformatics/btr407, 3157927, 21737438.
42. DREAM4 In Silico Network Challenge. http://wiki.c2b2.columbia.edu/dream/index.php/D4c2.
43. Evaluation script for the DREAM4 In Silico Network Challenge. http://wiki.c2b2.columbia.edu/dream/results/DREAM4.
44. Schaffter T, Marbach D, Floreano D. GeneNetWeaver: in silico benchmark generation and performance profiling of network inference methods. Bioinformatics 2011, 27(16):2263-2270. 10.1093/bioinformatics/btr373, 21697125.
45. Wang Y, Zhou T. A relative variation-based method to unraveling gene regulatory networks. PLoS ONE 2012, 7(2):e31194. 10.1371/journal.pone.0031194, 3282721, 22363578.
46. Guelzim N, Bottani S, Bourgine P, Kepes F. Topological and causal structure of the yeast transcriptional regulatory network. Nat Genet 2002, 31:60-63. 10.1038/ng873, 11967534.
47. Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, et al. Bioconductor: open software development for computational biology and bioinformatics. Genome Biol 2004, 5(10):R80. 10.1186/gb-2004-5-10-r80, 545600, 15461798.
48. Kaplan N, Moore IK, Fondufe-Mittendorf Y, Gossett AJ, Tillo D, Field Y, LeProust EM, Hughes TR, Lieb JD, Widom J, et al. The DNA-encoded nucleosome organization of a eukaryotic genome. Nature 2008, 458(7236):362-366. 2658732, 19092803.
49. Luscombe NM, Babu MM, Yu H, Snyder M, Teichmann SA, Gerstein M. Genomic analysis of regulatory network dynamics reveals large topological changes. Nature 2004, 431(7006):308-312. 10.1038/nature02782, 15372033.
50. Flassig RJ, Heise S, Sundmacher K, Klamt S. An effective framework for reconstructing gene regulatory networks from genetical genomics data. Bioinformatics 2013, 29(2):246-254. 10.1093/bioinformatics/bts679, 23175757.