Beyond protein expression, MOPED goes multi-omics

Nucleic Acids Research

Volumn 43, Issue D1, 2015, Pages D1145-D1151

  Montague, Elizabeth ^a,b,c   Janko, Imre ^a,b,c   Stanberry, Larissa ^a,b,c   Lee, Elaine ^a,b,c   Choiniere, John ^a,c   Anderson, Nathaniel ^a,c   Stewart, Elizabeth ^a,c   Broomall, William ^a,b,c   Higdon, Roger ^a,b,c   Kolker, Natali ^a,b,c   Kolker, Eugene ^a,b,c,d,e  

^a SEATTLE CHILDREN S RESEARCH INSTITUTE   (United States)

^b CDO Analytics   (United States)

^c Data Enabled Life Sciences Alliance International DELSA Global   (United States)

^d UNIVERSITY OF WASHINGTON   (United States)

^e NORTHEASTERN UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; COMPUTER INTERFACE; DATA BASE; GENE EXPRESSION; INFORMATION SERVICE; INTERNET; ONLINE SYSTEM; PRIORITY JOURNAL; PROTEIN EXPRESSION; PROTEOMICS; ANIMAL; GENE EXPRESSION PROFILING; GENETIC DATABASE; GENETICS; HUMAN; METABOLISM; MOUSE;

PROTEIN;

ANIMALS; DATABASES, GENETIC; GENE EXPRESSION PROFILING; HUMANS; INTERNET; MICE; PROTEINS; PROTEOMICS;

EID: 84941042092     PISSN: 03051048     EISSN: 13624962     Source Type: Journal    
DOI: 10.1093/nar/gku1175     Document Type: Article

References (55)

1. Higdon, R., Stewart, E., Stanberry, L., Haynes, W., Choiniere, J., Montague, E., Anderson, N., Yandl, G., Janko, I., Broomall, W. et al. (2014) MOPED enables discoveries through consistently processed proteomics data. J. Proteome Res., 13, 107-113.
2. Kolker, E., Higdon, R., Haynes, W., Welch, D., Broomall, W., Lancet, D., Stanberry, L. and Kolker, N. (2012) MOPED: Model Organism Protein Expression Database. Nucleic Acids Res., 40, D1093-D1099.
3. Higdon, R., Haynes, W., Stanberry, L., Stewart, E., Yandl, G., Howard, C., Broomall, W., Kolker, N. and Kolker, E. (2013) Unraveling the complexities of life sciences data. Big Data, 1, 42-50.
4. Zhang, W., Li, F. and Nie, L. (2010) Integrating multiple 'omics' analysis for microbial biology: application and methodologies. Microbiol. Read. Engl., 156, 287-301.
5. Sikaroodi, M., Galachiantz, Y. and Baranova, A. (2010) Tumor markers: the potential of 'omics' approach. Curr. Mol. Med., 10, 249-257.
6. Stanberry, L., Mias, G. I., Haynes, W., Higdon, R., Snyder, M. and Kolker, E. (2013) Integrative analysis of longitudinal metabolomics data from a personal multi-omics profile. Metabolites, 3, 741-760.
7. Chen, R., Mias, G. I., Li-Pook-Than, J., Jiang, L., Lam, H. Y. K., Chen, R., Miriami, E., Karczewski, K. J., Hariharan, M., Dewey, F. E. et al. (2012) Personal omics profiling reveals dynamic molecular and medical phenotypes. Cell, 148, 1293-1307.
8. Montague, E., Stanberry, L., Higdon, R., Janko, I., Lee, E., Anderson, N., Choiniere, J., Stewart, E., Yandl, G., Broomall, W. et al. (2014) MOPED 2.5-an integrated multi-omics resource: Multi-Omics Profiling Expression Database now includes transcriptomics data. Omics J. Integr. Biol., 18, 335-343.
9. Kolker, E., Özdemir, V., Martens, L., Hancock, W., Anderson, G., Anderson, N., Aynacioglu, S., Baranova, A., Campagna, S. R., Chen, R. et al. (2014) Toward more transparent and reproducible omics studies through a common metadata checklist and data publications. Omics J. Integr. Biol., 18, 10-14.
10. Dumbill, E. and Kolker, E. (2013) Introducing a metadata checklist for omics data. Big Data, 1, 195-195.
11. Announcement: Reducing our irreproducibility (2013) Nature, 496, 398-398.
12. Khatri, P., Sirota, M. and Butte, A. J. (2012) Ten years of pathway analysis: current approaches and outstanding challenges. PLoS Comput. Biol., 8, e1002375.
13. The UniProt Consortium (2014) Activities at the Universal Protein Resource (UniProt). Nucleic Acids Res., 42, D191-D198.
14. Flicek, P., Amode, M. R., Barrell, D., Beal, K., Billis, K., Brent, S., Carvalho-Silva, D., Clapham, P., Coates, G., Fitzgerald, S. et al. (2014) Ensembl 2014. Nucleic Acids Res., 42, D749-D755.
15. Maglott, D., Ostell, J., Pruitt, K. D. and Tatusova, T. (2011) Entrez Gene: gene-centered information at NCBI. Nucleic Acids Res., 39, D52-D57.
16. Caspi, R., Altman, T., Billington, R., Dreher, K., Foerster, H., Fulcher, C. A., Holland, T. A., Keseler, I. M., Kothari, A., Kubo, A. et al. (2014) The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of Pathway/Genome Databases. Nucleic Acids Res., 42, D459-D471.
17. Mi, H., Muruganujan, A. and Thomas, P. D. (2013) PANTHER in 2013: modeling the evolution of gene function, and other gene attributes, in the context of phylogenetic trees. Nucleic Acids Res., 41, D377-D386.
18. Croft, D., Mundo, A. F., Haw, R., Milacic, M., Weiser, J., Wu, G., Caudy, M., Garapati, P., Gillespie, M., Kamdar, M. R. et al. (2014) The Reactome pathway knowledgebase. Nucleic Acids Res., 42, D472-D477.
19. Vizcaíno, J. A., Côté, R. G., Csordas, A., Dianes, J. A., Fabregat, A., Foster, J. M., Griss, J., Alpi, E., Birim, M., Contell, J. et al. (2013) The PRoteomics IDEntifications (PRIDE) database and associated tools: status in 2013. Nucleic Acids Res., 41, D1063-D1069.
20. Desiere, F. (2006) The PeptideAtlas project. Nucleic Acids Res., 34, D655-D658.
21. Barrett, T., Wilhite, S. E., Ledoux, P., Evangelista, C., Kim, I. F., Tomashevsky, M., Marshall, K. A., Phillippy, K. H., Sherman, P. M., Holko, M. et al. (2013) NCBI GEO: archive for functional genomics data sets-update. Nucleic Acids Res., 41, D991-D995.
22. Kolker, E., Higdon, R., Welch, D., Bauman, A., Stewart, E., Haynes, W., Broomall, W. and Kolker, N. (2011) SPIRE: systematic protein investigative research environment. J. Proteomics, 75, 122-126.
23. Higdon, Roger, Van Belle, Gerald and Kolker, Eugene (2008) A note on the false discovery rate and inconsistent comparisons between experiments. Bioinformatics (Oxford, England), 24, 1225-1228. [PubMed]
24. Hather, G., Higdon, R., Bauman, A., Von Haller, P. D. and Kolker, E. (2010) Estimating false discovery rates for peptide and protein identification using randomized databases. Proteomics, 10, 2369-2376.
25. Higdon, R., Reiter, L., Hather, G., Haynes, W., Kolker, N., Stewart, E., Bauman, A. T., Picotti, P., Schmidt, A., Van Belle, G. et al. (2011) IPM: an integrated protein model for false discovery rate estimation and identification in high-throughput proteomics. J. Proteomics, 75, 116-121.
26. Holzman, T. and Kolker, E. (2004) Statistical analysis of global gene expression data: some practical considerations. Curr. Opin. Biotechnol., 15, 52-57.
27. Smyth, G. K. (2005) Limma: linear models for microarray data. In: Gentleman, R., Carey, V., Dudoit, S., Irizarry, R. and Huber, W. (eds). Bioinformatics and Computational Biology Solutions using R and Bioconductor. Springer, NY, pp. 397-420.
28. Kim, M.-S., Pinto, S. M., Getnet, D., Nirujogi, R. S., Manda, S. S., Chaerkady, R., Madugundu, A. K., Kelkar, D. S., Isserlin, R., Jain, S. et al. (2014) A draft map of the human proteome. Nature, 509, 575-581.
29. Wilhelm, M., Schlegl, J., Hahne, H., Moghaddas Gholami, A., Lieberenz, M., Savitski, M. M., Ziegler, E., Butzmann, L., Gessulat, S., Marx, H. et al. (2014) Mass-spectrometry-based draft of the human proteome. Nature, 509, 582-587.
30. Geiger, T., Madden, S. F., Gallagher, W. M., Cox, J. and Mann, M. (2012) Proteomic portrait of human breast cancer progression identifies novel prognostic markers. Cancer Res., 72, 2428-2439.
31. Moghaddas Gholami, A., Hahne, H., Wu, Z., Auer, F. J., Meng, C., Wilhelm, M. and Kuster, B. (2013) Global proteome analysis of the NCI-60 cell line panel. Cell Rep., 4, 609-620.
32. Pfister, T. D., Reinhold, W. C., Agama, K., Gupta, S., Khin, S. A., Kinders, R. J., Parchment, R. E., Tomaszewski, J. E., Doroshow, J. H. and Pommier, Y. (2009) Topoisomerase I levels in the NCI-60 cancer cell line panel determined by validated ELISA and microarray analysis and correlation with indenoisoquinoline sensitivity. Mol. Cancer Ther., 8, 1878-1884.
33. Stelzer, G., Dalah, I., Stein, T. I., Satanower, Y., Rosen, N., Nativ, N., Oz-Levi, D., Olender, T., Belinky, F., Bahir, I. et al. (2011) In-silico human genomics with GeneCards. Hum. Genomics, 5, 709-717.
34. Pruitt, K. D., Brown, G. R., Hiatt, S. M., Thibaud-Nissen, F., Astashyn, A., Ermolaeva, O., Farrell, C. M., Hart, J., Landrum, M. J., McGarvey, K. M. et al. (2014) RefSeq: an update on mammalian reference sequences. Nucleic Acids Res., 42, D756-D763.
35. Pakseresht, N., Alako, B., Amid, C., Cerdeño-Tárraga, A., Cleland, I., Gibson, R., Goodgame, N., Gur, T., Jang, M., Kay, S. et al. (2014) Assembly information services in the European Nucleotide Archive. Nucleic Acids Res., 42, D38-D43.
36. Harris, T. W., Baran, J., Bieri, T., Cabunoc, A., Chan, J., Chen, W. J., Davis, P., Done, J., Grove, C., Howe, K. et al. (2014) WormBase 2014: new views of curated biology. Nucleic Acids Res., 42, D789-D793.
37. Blake, J. A., Bult, C. J., Eppig, J. T., Kadin, J. A., Richardson, J. E. and Mouse Genome Database Group. (2014) The Mouse Genome Database: integration of and access to knowledge about the laboratory mouse. Nucleic Acids Res., 42, D810-D817.
38. Kanehisa, M., Goto, S., Sato, Y., Kawashima, M., Furumichi, M. and Tanabe, M. (2014) Data, information, knowledge and principle: back to metabolism in KEGG. Nucleic Acids Res., 42, D199-D205.
39. Gray, K. A., Daugherty, L. C., Gordon, S. M., Seal, R. L., Wright, M. W. and Bruford, E. A. (2013) Genenames.org: the HGNC resources in 2013. Nucleic Acids Res., 41, D545-D552.
40. Costanzo, M. C., Engel, S. R., Wong, E. D., Lloyd, P., Karra, K., Chan, E. T., Weng, S., Paskov, K. M., Roe, G. R., Binkley, G. et al. (2014) Saccharomyces genome database provides new regulation data. Nucleic Acids Res., 42, D717-D725.
41. Rose, P. W., Bi, C., Bluhm, W. F., Christie, C. H., Dimitropoulos, D., Dutta, S., Green, R. K., Goodsell, D. S., Prlic, A., Quesada, M. et al. (2013) The RCSB Protein Data Bank: new resources for research and education. Nucleic Acids Res., 41, D475-D482.
42. Gutmanas, A., Alhroub, Y., Battle, G. M., Berrisford, J. M., Bochet, E., Conroy, M. J., Dana, J. M., Fernandez Montecelo, M. A., Van Ginkel, G., Gore, S. P. et al. (2014) PDBe: Protein Data Bank in Europe. Nucleic Acids Res., 42, D285-D291.
43. Benson, D. A., Cavanaugh, M., Clark, K., Karsch-Mizrachi, I., Lipman, D. J., Ostell, J. and Sayers, E. W. (2013) GenBank. Nucleic Acids Res., 41, D36-D42.
44. Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T. et al. (2000) Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat. Genet., 25, 25-29.
45. Snyder, M., Mias, G., Stanberry, L. and Kolker, E. (2014) Metadata checklist for the integrated personal OMICS study: proteomics and metabolomics experiments. Omics J. Integr. Biol., 18, 81-85.
46. Xue, J., Wijeratne, S. S. K. and Zempleni, J. (2013) Holocarboxylase synthetase synergizes with methyl CpG binding protein 2 and DNA methyltransferase 1 in the transcriptional repression of long-terminal repeats. Epigenetics, 8, 504-511.
47. Staneva, R., Rukova, B., Hadjidekova, S., Nesheva, D., Antonova, O., Dimitrov, P., Simeonov, V., Stamenov, G., Cukuranovic, R., Cukuranovic, J. et al. (2013) Whole genome methylation array analysis reveals new aspects in Balkan endemic nephropathy etiology. BMC Nephrol., 14, 225.
48. Wilhelm, T. (2014) Phenotype prediction based on genome-wide DNA methylation data. BMC Bioinformatics, 15, 193.
49. Blacker, T. S., Mann, Z. F., Gale, J. E., Ziegler, M., Bain, A. J., Szabadkai, G. and Duchen, M. R. (2014) Separating NADH and NADPH fluorescence in live cells and tissues using FLIM. Nat. Commun., 5, 3936.
50. Williams, B. C., Filter, J. J., Blake-Hodek, K. A., Wadzinski, B. E., Fuda, N. J., Shalloway, D. and Goldberg, M. L. (2014) Greatwall-phosphorylated Endosulfine is both an inhibitor and a substrate of PP2A-B55 heterotrimers. eLife, 3, e01695.
51. Chen, M. and Penning, T. M. (2014) 5β-reduced steroids and human Δ (4)-3-ketosteroid 5β-reductase (AKR1D1). Steroids, 83, 17-26.
52. Delgado, A. P., Brandao, P. and Narayanan, R. (2014) Diabetes associated genes from the dark matter of the human proteome. MOJ Proteomics Bioinform., 1, 00020.
53. Delgado, A. P., Brandao, P., Chapado, M. J., Hamid, S. and Narayanan, R. (2014) Open reading frames associated with cancer in the dark matter of the human genome. Cancer Genomics Proteomics, 11, 201-213.
54. Haynes, W. A., Higdon, R., Stanberry, L., Collins, D. and Kolker, E. (2013) Differential expression analysis for pathways. PLoS Comput. Biol., 9, e1002967.
55. Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S. et al. (2005) Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. U. S. A., 102, 15545-15550.