In-silico identification of phenotype-biased functional modules

Proteome Science

Volumn 10, Issue , 2012, Pages

  Padmanabhan, Kanchana ^a,b   Wilson, Kevin ^e   Rocha, Andrea M ^c   Wang, Kuangyu ^d   Mihelcic, James R ^c   Samatova, Nagiza F ^a,b  

^a North Carolina State University   (United States)

^b OAK RIDGE NATIONAL LABORATORY   (United States)

^c UNIVERSITY OF SOUTH FLORIDA   (United States)

^d NORTH CAROLINA STATE UNIVERSITY   (United States)

^e RTI INTERNATIONAL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACONITATE HYDRATASE; CITRATE SYNTHASE; GLUTAMATE AMMONIA LIGASE; HYDROGEN; ISOCITRATE LYASE; MALATE DEHYDROGENASE; MALATE SYNTHASE; SORTASE;

AEROBIC METABOLISM; ALGORITHM; ANAEROBIC METABOLISM; BACTERIAL CELL WALL; CHEMOTAXIS; CONFERENCE PAPER; FERMENTATION; GENE CLUSTER; GLNA GENE; GRAM NEGATIVE BACTERIUM; GRAM POSITIVE BACTERIUM; HYDROLYSIS; MICROBIAL RESPIRATION; NONHUMAN; PHENOTYPE; PROTEIN EXPRESSION; PROTEIN PROTEIN INTERACTION; TWITCHING MOTILITY;

EID: 84907693630     PISSN: None     EISSN: 14775956     Source Type: Journal    
DOI: 10.1186/1477-5956-10-S1-S2     Document Type: Conference Paper

References (43)

1. Jensen L, Kuhn M, Stark M, Chaffron S, Creevey C, Muller J, Doerks T, Julien P, Roth A, Simonovic M, Bork P, von Mering C: STRING 8-a global view on proteins and their functional interactions in 630 organisms. Nucleic Acids Res 2009, 37:D412-D416
2. Schmidt M, Rocha A, Padmanabhan K, Chen Z, Scott K, Mihelcic J, Samatova N: Efficient alpha, beta-motif finder for identification of phenotype-related functional modules. BMC Bioinformatics 2011, 12:440
3. Yan B, Gregory S: Finding missing edges and communities in incomplete networks. J Phys A 2011, 44:495102
4. Paccanaro A, Trifonov V, Yu H, Gerstein M: Inferrng protein-protein interactions using interaction network topologies. Proceedings of the International Joint Conference on Neural Networks 2005
5. Hendrix W, Rocha A, Padmanabhan K, Choudhary A, Scott K, Mihelcic J, Samatova N: DENSE: Efficient and prior knowledge-driven discovery of phenotype-associated protein functional modules. BMC Systems Biology 2011, 5:172
6. Spirin V, Mirny L: Protein complexes and functional modules in molecular networks. Proc Natl Acad Sci 2003, 100:12123-12128
7. Hwang W, Cho Y, Zhang A, Ramanathan M: A novel functional module detection algorithm for protein-protein interaction networks. Algorithms Mol Biol 2006, 1:24
8. Habibi M, Eslahchi C, Wong L: Protein complex prediction based on kconnected subgraphs in protein interaction network. BMC Syst Biol 2010, 4:129
9. Stark C, Breitkreutz B, Reguly T, Boucher L, Breitkreutz A, Tyers M: BioGRID: A general repository for interaction datasets. Nucleic Acids Res 2006, 34: D535-D539
10. Krogan N, Peng W, Cagney G, Robinson M, Haw R, Zhong G, Guo X, Zhang X, Canadien V, Richards D, Beattie B, Lalev A, Zhang W, Davierwala A, Mnaimneh S, Starostine A, Tikuisis A, Grigull J, Datta N, Bray J, Hughes T, Emili A, Greenblatt J: High-definition macromolecular composition of yeast RNA-processing complexes. Mol Cell 2004, 13:225-239
11. Ho Y, Gruhler A, Heilbut A, Bader G, Moore L, Adams S, Millar A, Taylor P, Bennett K, Boutilier K, Yang L, Wolting C, Donaldson I, Schandorff S, Shewnarane J, Vo M, Taggart J, Goudreault M, Muskat B, Alfarano C, Dewar D, Lin Z, Michalickova K, Willems A, Sassi H, Nielsen P, Rasmussen K, Andersen J, Johansen L, Hansen L, Jespersen H, Podtelejnikov A, Nielsen E, Crawford J, Poulsen V, Sorensen B, Matthiesen J, Hendrickson R, Gleeson F, Pawson T, Moran M, Durocher D, Mann M, Hogue C, Figeys D, Tyers M: Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry. Nature 2002, 415:180-183
12. Gavin A, Bosche M, Krause R, Grandi P, Marzioch M, Bauer A, Schultz J, Rick J, Michon A, Cruciat C, Remor M, Hofert C, Schelder M, Brajenovic M, Ruffner H, Merino A, Klein K, Hudak M, Dickson D, Rudi T, Gnau V, Bauch A, Bastuck S, Huhse B, Leutwein C, Heurtier M, Copley R, Edelmann A, Querfurth E, Rybin V, Drewes G, Raida M, Bouwmeester T, Bork P, Seraphin B, Kuster B, Neubauer G, Superti-Furga G: Functional organization of the yeast proteome by systematic analysis of protein complexes. Nature 2002, 415:141-147
13. Gavin A, Aloy P, P G, Krause R, Boesche M, Marzioch M, Rau C, Jensen L, Bastuck S, Dmpelfeld B, Edelmann A, Heurtier M, Hoffman V, Hoefert C, Klein K, Hudak M, Michon A, Schelder M, Schirle M, Remor M, Rudi T, Hooper S, Bauer A, Bouwmeester T, Casari G, Drewes G, Neubauer G, Rick J, Kuster B, Bork P, Russell R, Superti-Furga G: Proteome survey reveals modularity of the yeast cell machinery. Nature 2006, 440:631-636
14. Wilson K, Rocha A, Padmanabhan K, Wang K, Chen Z, Jin Y, Mihelcic J, Samatova N: Detecting pathway cross-talks by analyzing conserved functional modules across multiple phenotype-expressing organisms. Proceedings of the IEEE International Conference Bioinformatics & Biomedicine 2011, 443-449
15. Kastenmuller G, Schenk M, Gasteiger J, Mewes H: Uncovering metabolic pathways relevant to phenotypic traits of microbial genomes. Genome Biol 2009, 10:R28
16. Slonim N, Elemento O, Tavazoie S: Ab initio genotype-phenotype association reveals intrinsic modularity in genetic networks. Mol Syst Biol 2006, 2:2006.0005
17. Nath K, Das D: Improvement of fermentative hydrogen production: Various approaches. Appl Microbiol Biotechnol 2004, 65:520-529
18. Kapdan FI, Kargi: Bio-hydrogen production from waste materials. Enzyme Microb Technol 2006, 38:569-582
19. Brentner L, Peccia J, Zimmerman J: Challenges in developing biohydrogen as a sustainable energy source: Implications for a research agenda. Environ Sci Technol 2010, 44:2243-2254
20. Rey F, Heiniger E, Harwood C: Redirection of metabolism for biological hydrogen production. Appl Environ Microbiol 2007, 73:1665-1671
21. Rey F, Oda Y, Harwood C: Regulation of uptake hydrogenase and effects of hydrogen utilization on gene expression in Rhodopseudomonas palustris. J Bacteriol 2006, 188:6143-6152
22. Lathe W, Williams J, Mangan M, Karolchik D: Genomic data resources: Challenges and promises. Nature Edu 2008, 1(3)
23. Lopez-Gomollón S, Hernández J, Pellicer S, Angarica V, Peleato M, Fillat M: Cross-talk between iron and nitrogen regulatory networks in Anabaena (Nostoc) sp. PCC 7120: Identification of overlapping genes in FurA and NtcA regulons. J Mol Biol 2007, 374:267-281
24. Kovacs KL, Bagi Z, Balint B, Fodor Bd, Scnadi G, Csaki R, Hanczar T, Kovacs AT, Maroti G, Perei K, Toth A, Rakhely G: Novel approaches to exploit microbial hydrogen metabolism Biohydrogen III. USA: Elsevier Inc; Miyake J, Igarashi Y, Rogner M 2004
25. Vignais P, Billoud B, Meyer J: Classification and phylogeny of hydrogenases. FEMS Microbiol Rev 2001, 25:455-501
26. Miyake J: Biohydrogen New York, USA: Plenum Press; 1998
27. Shima S, Thauer R: A third type of hydrogenase catalyzing H2 activation. Chem Rec 2007, 7:37-46
28. White D: The physiology and biochemistry of prokaryotes Oxford, England: Oxford University Press, Inc; 2000
29. Butland G, Zhang J, Yang W, Sheung A, Wong P, Greenbalt J, Emili A, Zamble D: Interactions of the Es-cherichia coli hydrogenase biosynthetic proteins: HybG complex formation. FEBS Lett 2006, 580:677-681
30. Guerrini O, Soucaille P, Girbal L, Guigliarelli B, Leger C, Burlat B, Léger C: Characterization of Two 2[4Fe4S] Ferredoxins from Clostridium acetobutylicum. Curr Microbiol 2008, 56:261-267
31. Yu J, Takahashi P: Biophotolysis-based hydrogen production by Cyanobacteria and green microalgae. In Communicating Current Research and Educational Topics and Trends in Applied Microbiology. Mendez-Vilas A 2007, 1:79-89
32. Thomaz A, Pozzo L, Fontes A, Almeida D, Stahl C, Santos-Mallet J, Gomes S, Feder D, Ayres D, Giorgio S, Cesar C: Optical tweezers force measurements to study parasites chemotaxis. Adv Micro Tech 2009, 7367
33. Liu Y, Li J, Sam L, Goh C, Gerstein M, Lussier Y: An integrative genomic approach to uncover molecular mechanisms of prokaryotic traits. PLoS Comput Biol 2006, 2(11):e159
34. Gross R, Beier D: PLoS Comput Biol Caister Academic Press; 2011
35. Tamura M, D'haeseleer P: Microbial genotypephenotype mapping by class association rule mining. Bioinformatics 2008, 24:1523-1529
36. Tamura M, D'haeseler P: Comparative genome content analysis with respect to basic microbial phenotypes by class association rule mining. Proceedings of the International Conference on Systems Biology 2007
37. Goh C, Gianoulis T, Liu J Yand Li, Paccanaro A, Lussier Y, Gerstein M: Integration of curated databases to identify genotype-phenotype associations. BMC Genomics 2006, 7:257
38. Vitreschak AG, Mironov A, Lyubetsky V, Gelfand M: Comparative genomic analysis of T-box regulatory systems in bacteria. RNA 2008, 14:717-735
39. Jensen L, Kuhn M, Stark M, Chaffron S, Creevey C, Muller J, Doerks T, Julien P, Roth A, Simonovic M, Bork P, von Mering C: STRING 8-a global view on proteins and their functional interactions in 630 organisms. Nucleic Acids Res 2009, 37:D412-416
40. Tatusov R, Galperin M, Natale D, Koonin E: The COG database: A tool for genome-scale analysis of protein functions and evolution. Nucleic Acids Res 2000, 28:33-36
41. Prelic A, Bleuler S, Zimmermann P, Wille A, Bühlmann P, Gruissem W, Hennig L, Thiele L, Zitzler E: A systematic comparison and evaluation of biclustering methods for gene expression data. Bioinformatics 2006, 22:1122-1129
42. North B, Curtis D, Sham P: A note on the calculation of empirical p-values from Monte Carlo procedures. Am J Hum Genet 2002, 71:439-441
43. Zhang B, Park B, Karpinets T, Samatova N: From pull-down data to protein interaction networks and complexes with biological relevance. Bioinformatics 2008, 24(7):979-986