Medema MH, van Raaphorst R, Takano E, Breitling R: Computational tools for the synthetic design of biochemical pathways. Nat Rev Microbiol. 2012, 10 (3): 191-202. 10.1038/nrmicro2717.
Article
PubMed
CAS
Google Scholar
Schellenberger J, Que R, Fleming RM, Thiele I, Orth JD, Feist AM, Zielinski DC, Bordbar A, Lewis NE, Rahmanian S, Kang J, Hyduke DR, Palsson BØ: Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0. Nat Protoc. 2011, 6 (9): 1290-1307. 10.1038/nprot.2011.308.
Article
PubMed Central
PubMed
CAS
Google Scholar
Selinger DW, Wright MA, Church GM: On the complete determination of biological systems. Trends Biotechnol. 2003, 21 (6): 251-254. 10.1016/S0167-7799(03)00113-6.
Article
PubMed
CAS
Google Scholar
Chikina MD, Huttenhower C, Murphy CT, Troyanskaya OG: Global prediction of tissue-specific gene expression and context-dependent gene networks in Caenorhabditis elegans. PLoS Comput Biol. 2009, 5: e1000417-10.1371/journal.pcbi.1000417.
Article
PubMed Central
PubMed
Google Scholar
Ouyang Z, Zhou Q, Wong WH: ChIP-Seq of transcription factors predicts absolute and differential gene expression in embryonic stem cells. Proc Natl Acad Sci U S A. 2009, 106 (51): 21521-21526. 10.1073/pnas.0904863106.
Article
PubMed Central
PubMed
CAS
Google Scholar
McLeay RC, Lesluyes T, Cuellar Partida G, Bailey TL: Genome-wide in silico prediction of gene expression. Bioinformatics. 2012, 28 (21): 2789-2796. 10.1093/bioinformatics/bts529.
Article
PubMed Central
PubMed
CAS
Google Scholar
Fox JM, Erill I: Relative codon adaptation: a generic codon bias index for prediction of gene expression. DNA Res. 2010, 17: 185-196. 10.1093/dnares/dsq012.
Article
PubMed Central
PubMed
CAS
Google Scholar
Roymondal U, Das S, Sahoo S: Predicting gene expression level from relative codon usage bias: an application to Escherichia coli genome. DNA Res. 2009, 16 (1): 13-30. 10.1093/dnares/dsn029.
Article
PubMed Central
PubMed
CAS
Google Scholar
Das S, Roymondal U, Chottopadhyay B, Sahoo S: Gene expression profile of the cynobacterium synechocystis genome. Gene. 2012, 497: 344-352. 10.1016/j.gene.2012.01.023.
Article
PubMed
CAS
Google Scholar
Menashe I, Grange P, Larsen EC, Banerjee-Basu S, Mitra PP: Co-expression profiling of autism genes in the mouse brain. PLoS Comput Biol. 2013, 9 (7): e1003128-10.1371/journal.pcbi.1003128.
Article
PubMed Central
PubMed
CAS
Google Scholar
Liu R, Liao J, Yang M, Sheng J, Yang H, Wang Y, Pan E, Guo W, Pu Y, Kim SJ, Yin L: The cluster of miR-143 and miR-145 affects the risk for esophageal squamous cell carcinoma through co-regulating fascin homolog 1. PLoS One. 2012, 7 (3): e33987-10.1371/journal.pone.0033987.
Article
PubMed Central
PubMed
CAS
Google Scholar
Moreno-Sanchez N, Rueda J, Carabano MJ, Reverter A, McWilliam S, Gonzalez C, Diaz C: Skeletal muscle specific genes networks in cattle. Funct Integr Genomics. 2010, 10 (4): 609-618. 10.1007/s10142-010-0175-2.
Article
PubMed Central
PubMed
CAS
Google Scholar
Liao BY, Zhang J: Evolutionary conservation of expression profiles between human and mouse orthologous genes. Mol Biol Evol. 2006, 23 (3): 530-540.
Article
PubMed
CAS
Google Scholar
Ling MH, Ban Y, Wen H, Wang SM, Ge SX: Conserved expression of natural antisense transcripts in mammals. BMC Genomics. 2013, 14 (1): 243-10.1186/1471-2164-14-243.
Article
PubMed Central
PubMed
CAS
Google Scholar
Torkamani A, Dean B, Schork NJ, Thomas EA: Coexpression network analysis of neural tissue reveals perturbations in developmental processes in schizophrenia. Genome Res. 2010, 20 (4): 403-412. 10.1101/gr.101956.109.
Article
PubMed Central
PubMed
CAS
Google Scholar
Childs KL, Davidson RM, Buell CR: Gene coexpression network analysis as a source of functional annotation for rice genes. PLoS One. 2011, 6: e22196-10.1371/journal.pone.0022196.
Article
PubMed Central
PubMed
CAS
Google Scholar
Ray M, Zhang W: Analysis of Alzheimer's disease severity across brain regions by topological analysis of gene co-expression networks. BMC Syst Biol. 2010, 4: 136-10.1186/1752-0509-4-136.
Article
PubMed Central
PubMed
Google Scholar
Kadarmideen HN, Watson-Haigh NS: Building gene co-expression networks using transcriptomics data for systems biology investigations: Comparison of methods using microarray data. Bioinformation. 2012, 8 (18): 855-861. 10.6026/97320630008855.
Article
PubMed Central
PubMed
Google Scholar
Obayashi T, Kinoshita K: Rank of correlation coefficient as a comparable measure for biological significance of gene coexpression. DNA Res. 2009, 16 (5): 249-260. 10.1093/dnares/dsp016.
Article
PubMed Central
PubMed
CAS
Google Scholar
Zhao W, Langfelder P, Fuller T, Dong J, Li A, Hovarth S: Weighted gene coexpression network analysis: state of the art. J Biopharm Stat. 2010, 20 (2): 281-300. 10.1080/10543400903572753.
Article
PubMed
Google Scholar
Furlotte NA, Kang HM, Ye C, Eskin E: Mixed-model coexpression: calculating gene coexpression while accounting for expression heterogeneity. Bioinformatics. 2011, 27: i288-i294. 10.1093/bioinformatics/btr221.
Article
PubMed Central
PubMed
CAS
Google Scholar
Jupiter D, Chen H, VanBuren V: STARNET 2: a web-based tool for accelerating discovery of gene regulatory networks using microarray co-expression data. BMC Bioinformatics. 2009, 10: 332-10.1186/1471-2105-10-332.
Article
PubMed Central
PubMed
Google Scholar
Wada M, Takahashi H, Altaf-Ul-Amin M, Nakamura K, Hirai MY, Ohta D, Kanaya S: Prediction of operon-like gene clusters in the Arabidopsis thaliana genome based on co-expression analysis of neighboring genes. Gene. 2012, 503 (1): 56-64. 10.1016/j.gene.2012.04.043.
Article
PubMed
CAS
Google Scholar
Chay ZE, Lee CH, Lee KC, Oon JS, Ling MH: Russel and Rao coefficient is a suitable substitute for Dice coefficient in studying restriction mapped genetic distances of Escherichia coli. Comput Math Biol. 2010, 1: 1-
Google Scholar
Park SJ, Nakai K: A regression analysis of gene expression in ES cells reveals two gene classes that are significantly different in epigenetic patterns. BMC Bioinformatics. 2011, 12 (Suppl 1): S50-10.1186/1471-2105-12-S1-S50.
Article
PubMed Central
PubMed
Google Scholar
Oeder S, Mages J, Flicek P, Lang R: Uncovering information on expression of natural antisense transcripts in Affymetrix MOE430 datasets. BMC Genomics. 2007, 8: 200-10.1186/1471-2164-8-200.
Article
PubMed Central
PubMed
Google Scholar
Reverter A, Barris W, Moreno-Sanchez N, McWilliam S, Wang YH, Harper GS, Lehnert SA, Dalrymple BP: Construction of gene interaction and regulatory networks in bovine skeletal muscle from expression data. Aust J Exp Agric. 2005, 45: 821-829. 10.1071/EA05039.
Article
CAS
Google Scholar
Shi W, Banerjee A, Ritchie ME, Gerondakis S, Smyth GK: Illumina WG-6 BeadChip strips should be normalized separately. BMC Bioinformatics. 2009, 10: 372-10.1186/1471-2105-10-372.
Article
PubMed Central
PubMed
Google Scholar
Chain B, Bowen H, Hammond J, Posch W, Rasaiyaah J, Tsang J, Noursadeghi M: Error, reproducibility and sensitivity: a pipeline for data processing of Agilent oligonucleotide expression arrays. BMC Bioinformatics. 2010, 11: 344-10.1186/1471-2105-11-344.
Article
PubMed Central
PubMed
Google Scholar
Anderson T, Wulfkuhle J, Liotta L, Winslow RL, Petricoin E: Improved reproducibility of reverse-phase protein microarrays using array microenvironment normalization. Proteomics. 2009, 9 (24): 5562-5566. 10.1002/pmic.200900505.
Article
PubMed Central
PubMed
CAS
Google Scholar
Gyorffy B, Molnar B, Lage H, Szallasi Z, Eklund AC: Evaluation of microarray preprocessing algorithms based on concordance with RT-PCR in clinical samples. PLoS One. 2009, 4: e5645-10.1371/journal.pone.0005645.
Article
PubMed Central
PubMed
Google Scholar
Wu D, Hu Y, Tong S, Williams BR, Smyth GK, Gantier MP: The use of miRNA microarrays for the analysis of cancer samples with global miRNA decrease. RNA. 2013, 19 (7): 876-888. 10.1261/rna.035055.112.
Article
PubMed Central
PubMed
Google Scholar
Porcar M, Danchin A, de Lorenzo V, Dos Santos VA, Krasnogor N, Rasmussen S, Moya A: The ten grand challenges of synthetic life. Syst Synthetic Biol. 2011, 5 (1–2): 1-9.
Article
Google Scholar
Alteri CJ, Lindner JR, Reiss DJ, Smith SN, Mobley HL: The broadly conserved regulator PhoP links pathogen virulence and membrane potential in Escherichia coli. Mol Microbiol. 2011, 82 (1): 145-163. 10.1111/j.1365-2958.2011.07804.x.
Article
PubMed Central
PubMed
CAS
Google Scholar
Bansal T, Jesudhasan P, Pillai S, Wood TK, Jayaraman A: Temporal regulation of enterohemorrhagic Escherichia coli virulence mediated by autoinducer-2. Appl Microbiol Biotechnol. 2008, 78 (5): 811-819. 10.1007/s00253-008-1359-8.
Article
PubMed
CAS
Google Scholar
Bansal T, Kim DN, Slininger T, Wood TK, Jayaraman A: Human intestinal epithelial cell-derived molecule(s) increase enterohemorrhagic Escherichia coli virulence. FEMS Immunol Med Microbiol. 2012, 66 (3): 399-410. 10.1111/1574-695X.12004.
Article
PubMed Central
PubMed
CAS
Google Scholar
Chattopadhyay MK, Chen W, Tabor H: Escherichia coli glutathionylspermidine synthetase/amidase: phylogeny and effect on regulation of gene expression. FEMS Microbiol Lett. 2013, 338 (2): 132-140. 10.1111/1574-6968.12035.
Article
PubMed
CAS
Google Scholar
Chen T, Wang J, Zeng L, Li R, Li J, Chen Y, Lin Z: Significant rewiring of the transcriptome and proteome of an Escherichia coli strain harboring a tailored exogenous global regulator IrrE. PLoS One. 2012, 7 (7): e37126-10.1371/journal.pone.0037126.
Article
PubMed Central
PubMed
CAS
Google Scholar
Cho BK, Federowicz SA, Embree M, Park YS, Kim D, Palsson BO: The PurR regulon in Escherichia coli K-12 MG1655. Nucleic Acids Res. 2011, 39 (15): 6456-6464. 10.1093/nar/gkr307.
Article
PubMed Central
PubMed
CAS
Google Scholar
Chu W, Zere TR, Weber MM, Wood TK, Whiteley M, Hidalgo-Romano B, Valenzuela E, McLean RJ: Indole production promotes Escherichia coli mixed-culture growth with Pseudomonas aeruginosa by inhibiting quorum signaling. Appl Environ Microbiol. 2012, 78 (2): 411-419. 10.1128/AEM.06396-11.
Article
PubMed Central
PubMed
CAS
Google Scholar
Durand S, Storz G: Reprogramming of anaerobic metabolism by the FnrS small RNA. Mol Microbiol. 2010, 75 (5): 1215-1231. 10.1111/j.1365-2958.2010.07044.x.
Article
PubMed Central
PubMed
CAS
Google Scholar
Habdas BJ, Smart J, Kaper JB, Sperandio V: The LysR-type transcriptional regulator QseD alters type three secretion in enterohemorrhagic Escherichia coli and motility in K-12 Escherichia coli. J Bacteriol. 2010, 192 (14): 3699-3712. 10.1128/JB.00382-10.
Article
PubMed Central
PubMed
CAS
Google Scholar
Hensley MP, Gunasekera TS, Easton JA, Sigdel TK, Sugarbaker SA, Klingbeil L, Breece RM, Tierney DL, Crowder MW: Characterization of Zn(II)-responsive ribosomal proteins YkgM and L31 in E. coli. J Inorg Biochem. 2012, 111: 164-172.
Article
PubMed Central
PubMed
CAS
Google Scholar
Hidalgo G, Ponton A, Fatisson J, O'May C, Asadishad B, Schinner T, Tufenkji N: Induction of a state of iron limitation in uropathogenic Escherichia coli CFT073 by cranberry-derived proanthocyanidins as revealed by microarray analysis. Appl Environ Microbiol. 2011, 77 (4): 1532-1535. 10.1128/AEM.02201-10.
Article
PubMed Central
PubMed
CAS
Google Scholar
Kendall MM, Rasko DA, Sperandio V: Global effects of the cell-to-cell signaling molecules autoinducer-2, autoinducer-3, and epinephrine in a luxS mutant of enterohemorrhagic Escherichia coli. Infect Immun. 2007, 75 (10): 4875-4884. 10.1128/IAI.00550-07.
Article
PubMed Central
PubMed
CAS
Google Scholar
Kim Y, Wang X, Zhang XS, Grigoriu S, Page R, Peti W, Wood TK: Escherichia coli toxin/antitoxin pair MqsR/MqsA regulate toxin CspD. Environ Microbiol. 2010, 12 (5): 1105-1121. 10.1111/j.1462-2920.2009.02147.x.
Article
PubMed Central
PubMed
CAS
Google Scholar
Lee J, Zhang XS, Hegde M, Bentley WE, Jayaraman A, Wood TK: Indole cell signaling occurs primarily at low temperatures in Escherichia coli. ISME J. 2008, 2 (10): 1007-1023. 10.1038/ismej.2008.54.
Article
PubMed
CAS
Google Scholar
Lee J, Hiibel SR, Reardon KF, Wood TK: Identification of stress-related proteins in Escherichia coli using the pollutant cis-dichloroethylene. J Appl Microbiol. 2010, 108 (6): 2088-2102.
PubMed
CAS
Google Scholar
Li Y, Zhang Y: PhoU is a persistence switch involved in persister formation and tolerance to multiple antibiotics and stresses in Escherichia coli. Antimicrob Agents Chemother. 2007, 51 (6): 2092-2099. 10.1128/AAC.00052-07.
Article
PubMed Central
PubMed
CAS
Google Scholar
Ma Q, Wood TK: OmpA influences Escherichia coli biofilm formation by repressing cellulose production through the CpxRA two-component system. Environ Microbiol. 2009, 11 (10): 2735-2746. 10.1111/j.1462-2920.2009.02000.x.
Article
PubMed
CAS
Google Scholar
Moon K, Gottesman S: A PhoQ/P-regulated small RNA regulates sensitivity of Escherichia coli to antimicrobial peptides. Mol Microbiol. 2009, 74 (6): 1314-1330. 10.1111/j.1365-2958.2009.06944.x.
Article
PubMed Central
PubMed
CAS
Google Scholar
Nakanishi Y, Fukuda S, Chikayama E, Kimura Y, Ohno H, Kikuchi J: Dynamic omics approach identifies nutrition-mediated microbial interactions. J Proteome Res. 2011, 10 (2): 824-836. 10.1021/pr100989c.
Article
PubMed
CAS
Google Scholar
Nobre LS, Al-Shahrour F, Dopazo J, Saraiva LM: Exploring the antimicrobial action of a carbon monoxide-releasing compound through whole-genome transcription profiling of Escherichia coli. Microbiology. 2009, 155 (Pt 3): 813-824.
Article
PubMed
CAS
Google Scholar
Reading NC, Rasko D, Torres AG, Sperandio V: A transcriptome study of the QseEF two-component system and the QseG membrane protein in enterohaemorrhagic Escherichia coli O157: H7. Microbiology. 2010, 156 (Pt 4): 1167-1175.
Article
PubMed Central
PubMed
CAS
Google Scholar
Strader MB, Costantino N, Elkins CA, Chen CY, Patel I, Makusky AJ, Choy JS, Court DL, Markey SP, Kowalak JA: A proteomic and transcriptomic approach reveals new insight into beta-methylthiolation of Escherichia coli ribosomal protein S12. Mol Cell Proteomics. 2011, 10 (3): M110 005199-10.1074/mcp.M110.005199.
Article
PubMed Central
PubMed
Google Scholar
Traxler MF, Zacharia VM, Marquardt S, Summers SM, Nguyen HT, Stark SE, Conway T: Discretely calibrated regulatory loops controlled by ppGpp partition gene induction across the 'feast to famine' gradient in Escherichia coli. Mol Microbiol. 2011, 79 (4): 830-845. 10.1111/j.1365-2958.2010.07498.x.
Article
PubMed Central
PubMed
CAS
Google Scholar
Waters LS, Sandoval M, Storz G: The Escherichia coli MntR miniregulon includes genes encoding a small protein and an efflux pump required for manganese homeostasis. J Bacteriol. 2011, 193 (21): 5887-5897. 10.1128/JB.05872-11.
Article
PubMed Central
PubMed
Google Scholar
Yang C, Huang TW, Wen SY, Chang CY, Tsai SF, Wu WF, Chang CH: Genome-wide PhoB binding and gene expression profiles reveal the hierarchical gene regulatory network of phosphate starvation in Escherichia coli. PLoS One. 2012, 7 (10): e47314-10.1371/journal.pone.0047314.
Article
PubMed Central
PubMed
CAS
Google Scholar
Abadia E, Zhang J, Ritacco V, Kremer K, Ruimy R, Rigouts L, Gomes HM, Elias AR, Fauville-Dufaux M, Stoffels K, Rasolofo-Razanamparany V, de Garcia Viedma D, Herranz M, Al-Hajoj S, Rastogi N, Garzelli C, Tortoli E, Suffys PN, Van Soolingen D, Refrégier G, Sola C: The use of microbead-based spoligotyping for Mycobacterium tuberculosis complex to evaluate the quality of the conventional method: providing guidelines for Quality Assurance when working on membranes. BMC Infect Dis. 2011, 11: 110-10.1186/1471-2334-11-110.
Article
PubMed Central
PubMed
Google Scholar
Hermida L, Poussin C, Stadler MB, Gubian S, Sewer A, Gaidatzis D, Hotz HR, Martin F, Belcastro V, Cano S, Peitsch MC, Hoeng J: Confero: an integrated contrast data and gene set platform for computational analysis and biological interpretation of omics data. BMC Genomics. 2013, 14: 514-10.1186/1471-2164-14-514.
Article
PubMed Central
PubMed
Google Scholar
Tomlinson C, Thimma M, Alexandrakis S, Castillo T, Dennis JL, Brooks A, Bradley T, Turnbull C, Blaveri E, Barton G, Chiba N, Maratou K, Soutter P, Aitman T, Game L: MiMiR–an integrated platform for microarray data sharing, mining and analysis. BMC Bioinformatics. 2008, 9: 379-10.1186/1471-2105-9-379.
Article
PubMed Central
PubMed
Google Scholar
Tseng GC, Ghosh D, Feingold E: Comprehensive literature review and statistical considerations for microarray meta-analysis. Nucleic Acids Res. 2012, 40 (9): 3785-3799. 10.1093/nar/gkr1265.
Article
PubMed Central
PubMed
CAS
Google Scholar
Chia CY, Lim CW, Leong WT, Ling MH: High expression stability of microtubule affinity regulating kinase 3 (MARK3) makes it a reliable reference gene. IUBMB Life. 2010, 62 (3): 200-203. 10.1002/iub.295.
Article
PubMed
CAS
Google Scholar
Heng SS, Chan OY, Keng BM, Ling MH: Glucan Biosynthesis Protein G Is a Suitable Reference Gene in Escherichia coli K-12. ISRN Microbiol. 2011, 2011: 469053-
Article
PubMed Central
PubMed
Google Scholar
Hira ZM, Trigeorgis G, Gillies DF: An algorithm for finding biologically significant features in microarray data based on a priori manifold learning. PLoS One. 2014, 9 (3): e90562-10.1371/journal.pone.0090562.
Article
PubMed Central
PubMed
Google Scholar
Wilczynski B, Liu YH, Yeo ZX, Furlong EE: Predicting Spatial and Temporal Gene Expression Using an Integrative Model of Transcription Factor Occupancy and Chromatin State. PLoS Comput Biol. 2012, 8 (12): e1002798-10.1371/journal.pcbi.1002798.
Article
PubMed Central
PubMed
CAS
Google Scholar
Kesseler KJ, Blinov ML, Elston TC, Kaufmann WK, Simpson DA: A predictive mathematical model of the DNA damage G2 checkpoint. J Theor Biol. 2013, 320: 159-169.
Article
PubMed
CAS
Google Scholar
Escudero JM, Haller JL, Clay CM, Escudero KW: Microarray analysis of Foxl2 mediated gene regulation in the mouse ovary derived KK1 granulosa cell line: Over-expression of Foxl2 leads to activation of the gonadotropin releasing hormone receptor gene promoter. J Ovarian Res. 2010, 3: 4-10.1186/1757-2215-3-4.
Article
PubMed Central
PubMed
Google Scholar
Jiang SY, Bhalla R, Ramamoorthy R, Luan HF, Venkatesh PN, Cai M, Ramachandran S: Over-expression of OSRIP18 increases drought and salt tolerance in transgenic rice plants. Transgenic Res. 2012, 21: 785-795. 10.1007/s11248-011-9568-9.
Article
PubMed
CAS
Google Scholar
Zheng Q, Wang XJ: GOEAST: a web-based software toolkit for Gene Ontology enrichment analysis. Nucleic Acids Res. 2008, 36 (Web Server issue): W358-W363.
Article
PubMed Central
PubMed
CAS
Google Scholar
Maeda T, Sanchez-Torres V, Wood TK: Enhanced hydrogen production from glucose by metabolically engineered Escherichia coli. Appl Microbiol Biotechnol. 2007, 77 (4): 879-890. 10.1007/s00253-007-1217-0.
Article
PubMed
CAS
Google Scholar
Trchounian K, Soboh B, Sawers RG, Trchounian A: Contribution of Hydrogenase 2 to stationary phase H(2) production by Escherichia coli during fermentation of glycerol. Cell Biochem Biophys. 2012, 66 (1): 103-108.
Article
Google Scholar