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4. Gene Ontology annotations and resources

Author

Gene Ontology Consortium, Blake, JA, Dolan, M, Drabkin, H, Hill, DP, Li, Ni, Sitnikov, D, Bridges, S, Burgess, S, Buza, T, McCarthy, F, Peddinti, D, Pillai, L, Carbon, S, Dietze, H, Ireland, A, Lewis, SE, Mungall, CJ, Gaudet, P, Chrisholm, RL, Fey, P, Kibbe, WA, Basu, S, Siegele, DA, McIntosh, BK, Renfro, DP, Zweifel, AE, Hu, JC, Brown, NH, Tweedie, S, Alam-Faruque, Y, Apweiler, R, Auchinchloss, A, Axelsen, K, Bely, B, Blatter, M-C, Bonilla, C, Bouguerleret, L, Boutet, E, Breuza, L, Bridge, A, Chan, WM, Chavali, G, Coudert, E, Dimmer, E, Estreicher, A, Famiglietti, L, Feuermann, M, Gos, A, Gruaz-Gumowski, N, Hieta, R, Hinz, C, Hulo, C, Huntley, R, James, J, Jungo, F, Keller, G, Laiho, K, Legge, D, Lemercier, P, Lieberherr, D, Magrane, M, Martin, MJ, Masson, P, Mutowo-Muellenet, P, O'Donovan, C, Pedruzzi, I, Pichler, K, Poggioli, D, Porras Millán, P, Poux, S, Rivoire, C, Roechert, B, Sawford, T, Schneider, M, Stutz, A, Sundaram, S, Tognolli, M, Xenarios, I, Foulgar, R, Lomax, J, Roncaglia, P, Khodiyar, VK, Lovering, RC, Talmud, PJ, Chibucos, M, Giglio, M Gwinn, Chang, H-Y, Hunter, S, McAnulla, C, Mitchell, A, Sangrador, A, Stephan, R, Harris, MA, Oliver, SG, Rutherford, K, Wood, V, Bahler, J, Lock, A, Kersey, PJ, McDowall, DM, Staines, DM, Dwinell, M, Shimoyama, M, Laulederkind, S, Hayman, T, Wang, S-J, Petri, V, Lowry, T, D'Eustachio, P, Matthews, L, Balakrishnan, R, Binkley, G, Cherry, JM, Costanzo, MC, Dwight, SS, Engel, SR, Fisk, DG, Hitz, BC, Hong, EL, Karra, K, Miyasato, SR, Nash, RS, Park, J, Skrzypek, MS, Weng, S, Wong, ED, Berardini, TZ, Huala, E, Mi, H, Thomas, PD, Chan, J, Kishore, R, Sternberg, P, Van Auken, K, Howe, D, Westerfield, M, Brown, Nicholas [0000-0002-8958-7017], Harris, Midori [0000-0003-4148-4606], Oliver, Stephen [0000-0001-6330-7526], Wood, Valerie [0000-0001-6330-7526], and Apollo - University of Cambridge Repository

Subjects
Internet, Genes, Vocabulary, Controlled, Databases, Genetic, Molecular Sequence Annotation, GeneralLiterature_REFERENCE(e.g.,dictionaries,encyclopedias,glossaries), Phylogeny
Abstract

The Gene Ontology (GO) Consortium (GOC, http://www.geneontology.org) is a community-based bioinformatics resource that classifies gene product function through the use of structured, controlled vocabularies. Over the past year, the GOC has implemented several processes to increase the quantity, quality and specificity of GO annotations. First, the number of manual, literature-based annotations has grown at an increasing rate. Second, as a result of a new 'phylogenetic annotation' process, manually reviewed, homology-based annotations are becoming available for a broad range of species. Third, the quality of GO annotations has been improved through a streamlined process for, and automated quality checks of, GO annotations deposited by different annotation groups. Fourth, the consistency and correctness of the ontology itself has increased by using automated reasoning tools. Finally, the GO has been expanded not only to cover new areas of biology through focused interaction with experts, but also to capture greater specificity in all areas of the ontology using tools for adding new combinatorial terms. The GOC works closely with other ontology developers to support integrated use of terminologies. The GOC supports its user community through the use of e-mail lists, social media and web-based resources.

Published
2020
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5. SBML Level 3: an extensible format for the exchange and reuse of biological models

Author

Keating, S, Waltemath, D, König, M, Zhang, F, Dräger, A, Chaouiya, C, Bergmann, F, Finney, A, Gillespie, C, Helikar, T, Hoops, S, Malik-Sheriff, R, Moodie, S, Moraru, I, Myers, C, Naldi, A, Olivier, B, Sahle, S, Schaff, J, Smith, L, Swat, M, Thieffry, D, Watanabe, L, Wilkinson, D, Blinov, M, Begley, K, Faeder, J, Gómez, H, Hamm, T, Inagaki, Y, Liebermeister, W, Lister, A, Lucio, D, Mjolsness, E, Proctor, C, Raman, K, Rodriguez, N, Shaffer, C, Shapiro, B, Stelling, J, Swainston, N, Tanimura, N, Wagner, J, Meier-Schellersheim, M, Sauro, H, Palsson, B, Bolouri, H, Kitano, H, Funahashi, A, Hermjakob, H, Doyle, J, Hucka, M, Adams, R, Allen, N, Angermann, B, Antoniotti, M, Bader, G, Červený, J, Courtot, M, Cox, C, Dalle Pezze, P, Demir, E, Denney, W, Dharuri, H, Dorier, J, Drasdo, D, Ebrahim, A, Eichner, J, Elf, J, Endler, L, Evelo, C, Flamm, C, Fleming, R, Fröhlich, M, Glont, M, Gonçalves, E, Golebiewski, M, Grabski, H, Gutteridge, A, Hachmeister, D, Harris, L, Heavner, B, Henkel, R, Hlavacek, W, Hu, B, Hyduke, D, Jong, H, Juty, N, Karp, P, Karr, J, Kell, D, Keller, R, Kiselev, I, Klamt, S, Klipp, E, Knüpfer, C, Kolpakov, F, Krause, F, Kutmon, M, Laibe, C, Lawless, C, Li, L, Loew, L, Machne, R, Matsuoka, Y, Mendes, P, Mi, H, Mittag, F, Monteiro, P, Natarajan, K, Nielsen, P, Nguyen, T, Palmisano, A, Jean-Baptiste, P, Pfau, T, Phair, R, Radivoyevitch, T, Rohwer, J, Ruebenacker, O, Saez-Rodriguez, J, Scharm, M, Schmidt, H, Schreiber, F, Schubert, M, Schulte, R, Sealfon, S, Smallbone, K, Soliman, S, Stefan, M, Sullivan, D, Takahashi, K, Teusink, B, Tolnay, D, Vazirabad, I, Kamp, A, Wittig, U, Wrzodek, C, Wrzodek, F, Xenarios, I, Zhukova, A, Zucker, J, Keating, SM, Bergmann, FT, Gillespie, CS, Malik-Sheriff, RS, Moodie, SL, Moraru, II, Myers, CJ, Olivier, BG, Schaff, JC, Smith, LP, Swat, MJ, Wilkinson, DJ, Blinov, ML, Faeder, JR, Gómez, HF, Hamm, TM, Lister, AL, Proctor, CJ, Shaffer, CA, Shapiro, BE, Sauro, HM, Doyle, JC, Adams, RR, Allen, NA, Angermann, BR, Bader, GD, Cox, CD, Denney, WS, Evelo, CT, Fleming, RM, Harris, LA, Heavner, BD, Hlavacek, WS, Hyduke, DR, Karp, PD, Karr, JR, Kell, DB, Loew, LM, Monteiro, PT, Natarajan, KN, Nielsen, PM, Phair, RD, Rohwer, JM, Ruebenacker, OA, Sealfon, SC, Stefan, MI, Sullivan, DP, Keating, S, Waltemath, D, König, M, Zhang, F, Dräger, A, Chaouiya, C, Bergmann, F, Finney, A, Gillespie, C, Helikar, T, Hoops, S, Malik-Sheriff, R, Moodie, S, Moraru, I, Myers, C, Naldi, A, Olivier, B, Sahle, S, Schaff, J, Smith, L, Swat, M, Thieffry, D, Watanabe, L, Wilkinson, D, Blinov, M, Begley, K, Faeder, J, Gómez, H, Hamm, T, Inagaki, Y, Liebermeister, W, Lister, A, Lucio, D, Mjolsness, E, Proctor, C, Raman, K, Rodriguez, N, Shaffer, C, Shapiro, B, Stelling, J, Swainston, N, Tanimura, N, Wagner, J, Meier-Schellersheim, M, Sauro, H, Palsson, B, Bolouri, H, Kitano, H, Funahashi, A, Hermjakob, H, Doyle, J, Hucka, M, Adams, R, Allen, N, Angermann, B, Antoniotti, M, Bader, G, Červený, J, Courtot, M, Cox, C, Dalle Pezze, P, Demir, E, Denney, W, Dharuri, H, Dorier, J, Drasdo, D, Ebrahim, A, Eichner, J, Elf, J, Endler, L, Evelo, C, Flamm, C, Fleming, R, Fröhlich, M, Glont, M, Gonçalves, E, Golebiewski, M, Grabski, H, Gutteridge, A, Hachmeister, D, Harris, L, Heavner, B, Henkel, R, Hlavacek, W, Hu, B, Hyduke, D, Jong, H, Juty, N, Karp, P, Karr, J, Kell, D, Keller, R, Kiselev, I, Klamt, S, Klipp, E, Knüpfer, C, Kolpakov, F, Krause, F, Kutmon, M, Laibe, C, Lawless, C, Li, L, Loew, L, Machne, R, Matsuoka, Y, Mendes, P, Mi, H, Mittag, F, Monteiro, P, Natarajan, K, Nielsen, P, Nguyen, T, Palmisano, A, Jean-Baptiste, P, Pfau, T, Phair, R, Radivoyevitch, T, Rohwer, J, Ruebenacker, O, Saez-Rodriguez, J, Scharm, M, Schmidt, H, Schreiber, F, Schubert, M, Schulte, R, Sealfon, S, Smallbone, K, Soliman, S, Stefan, M, Sullivan, D, Takahashi, K, Teusink, B, Tolnay, D, Vazirabad, I, Kamp, A, Wittig, U, Wrzodek, C, Wrzodek, F, Xenarios, I, Zhukova, A, Zucker, J, Keating, SM, Bergmann, FT, Gillespie, CS, Malik-Sheriff, RS, Moodie, SL, Moraru, II, Myers, CJ, Olivier, BG, Schaff, JC, Smith, LP, Swat, MJ, Wilkinson, DJ, Blinov, ML, Faeder, JR, Gómez, HF, Hamm, TM, Lister, AL, Proctor, CJ, Shaffer, CA, Shapiro, BE, Sauro, HM, Doyle, JC, Adams, RR, Allen, NA, Angermann, BR, Bader, GD, Cox, CD, Denney, WS, Evelo, CT, Fleming, RM, Harris, LA, Heavner, BD, Hlavacek, WS, Hyduke, DR, Karp, PD, Karr, JR, Kell, DB, Loew, LM, Monteiro, PT, Natarajan, KN, Nielsen, PM, Phair, RD, Rohwer, JM, Ruebenacker, OA, Sealfon, SC, Stefan, MI, and Sullivan, DP

Abstract

Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developed SBML Level 3 over the past decade. Its modular form consists of a core suited to representing reaction-based models and packages that extend the core with features suited to other model types including constraint-based models, reaction-diffusion models, logical network models, and rule-based models. The format leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single-cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and how SBML Level 3 provides the foundation needed to support this evolution.

Published
2020

7. Data access: Toward unrestricted use of public genomic data

Author

Amann, RI, Baichoo, S, Blencowe, BJ, Bork, P, Borodovsky, M, Brooksbank, C, Chain, PSG, Colwell, RR, Daffonchio, DG, Danchin, A, De Lorenzo, V, Dorrestein, PC, Finn, RD, Fraser, CM, Gilbert, JA, Hallam, SJ, Hugenholtz, P, Ioannidis, JPA, Jansson, JK, Kim, JF, Klenk, HP, Klotz, MG, Knight, R, Konstantinidis, KT, Kyrpides, NC, Mason, CE, McHardy, AC, Meyer, F, Ouzounis, CA, Patrinos, AAN, Podar, M, Pollard, KS, Ravel, J, Muñoz, AR, Roberts, RJ, Rosselló-Móra, R, Sansone, SA, Schloss, PD, Schriml, LM, Setubal, JC, Sorek, R, Stevens, RL, Tiedje, JM, Turjanski, A, Tyson, GW, Ussery, DW, Weinstock, GM, White, O, Whitman, WB, and Xenarios, I

Subjects
General Science & Technology, MD Multidisciplinary
Published
2019

8. Personalized cancer vaccine effectively mobilizes antitumor T cell immunity in ovarian cancer

Author

Tanyi, J.L. Bobisse, S. Ophir, E. Tuyaerts, S. Roberti, A. Genolet, R. Baumgartner, P. Stevenson, B.J. Iseli, C. Dangaj, D. Czerniecki, B. Semilietof, A. Racle, J. Michel, A. Xenarios, I. Chiang, C. Monos, D.S. Torigian, D.A. Nisenbaum, H.L. Michielin, O. June, C.H. Levine, B.L. Powel, D.J., Jr. Gfeller, D. Mick, R. Dafni, U. Zoete, V. Harari, A. Coukos, G. Kandalaft, L.E.

Abstract

We conducted a pilot clinical trial testing a personalized vaccine generated by autologous dendritic cells (DCs) pulsed with oxidized autologous whole-tumor cell lysate (OCDC), which was injected intranodally in platinum-treated, immunotherapy-naïve, recurrent ovarian cancer patients. OCDC was administered alone (cohort 1, n = 5), in combination with bevacizumab (cohort 2, n = 10), or bevacizumab plus low-dose intravenous cyclophosphamide (cohort 3, n = 10) until disease progression or vaccine exhaustion. A total of 392 vaccine doses were administered without serious adverse events. Vaccination induced T cell responses to autologous tumor antigen, which were associated with significantly prolonged survival. Vaccination also amplified T cell responses against mutated neoepitopes derived from nonsynonymous somatic tumor mutations, and this included priming of T cells against previously unrecognized neoepitopes, as well as novel T cell clones of markedly higher avidity against previously recognized neoepitopes. We conclude that the use of oxidized whole-tumor lysate DC vaccine is safe and effective in eliciting a broad antitumor immunity, including private neoantigens, and warrants further clinical testing. Copyright © 2018, American Association for the Advancement of Science.

Published
2018

9. Systems biology of the IMIDIA biobank from organ donors and pancreatectomised patients defines a novel transcriptomic signature of islets from individuals with type 2 diabetes

Author

Solimena, Michele, Schulte, A., Marselli, L., Ehehalt, F., Richter, D., Kleeberg, M., Mziaut, H., Knoch, K., Parnis, J., Bugliani, M., Siddiq, A., Jörns, A., Burdet, F., Liechti, R., Suleiman, M., Margerie, D., Syed, F., Distler, M., Grützmann, R., Petretto, E., Moreno-Moral, A., Wegbrod, C., Sönmez, A., Pfriem, K., Friedrich, A., Meinel, J., Wollheim, C., Baretton, G., Scharfmann, R., Nogoceke, E., Bonifacio, E., Sturm, D., Meyer-Puttlitz, B., Boggi, U., Saeger, H., Filipponi, F., Lesche, M., Meda, P., Dahl, A., Wigger, L., Xenarios, I., Falchi, M., Thorens, B., Weitz, J., Bokvist, K., Lenzen, S., Rutter, G., Froguel, P., von Bülow, M., Ibberson, M., Marchetti, P., Solimena, Michele, Schulte, A., Marselli, L., Ehehalt, F., Richter, D., Kleeberg, M., Mziaut, H., Knoch, K., Parnis, J., Bugliani, M., Siddiq, A., Jörns, A., Burdet, F., Liechti, R., Suleiman, M., Margerie, D., Syed, F., Distler, M., Grützmann, R., Petretto, E., Moreno-Moral, A., Wegbrod, C., Sönmez, A., Pfriem, K., Friedrich, A., Meinel, J., Wollheim, C., Baretton, G., Scharfmann, R., Nogoceke, E., Bonifacio, E., Sturm, D., Meyer-Puttlitz, B., Boggi, U., Saeger, H., Filipponi, F., Lesche, M., Meda, P., Dahl, A., Wigger, L., Xenarios, I., Falchi, M., Thorens, B., Weitz, J., Bokvist, K., Lenzen, S., Rutter, G., Froguel, P., von Bülow, M., Ibberson, M., and Marchetti, P.

Abstract

© 2017, The Author(s). Aims/hypothesis: Pancreatic islet beta cell failure causes type 2 diabetes in humans. To identify transcriptomic changes in type 2 diabetic islets, the Innovative Medicines Initiative for Diabetes: Improving beta-cell function and identification of diagnostic biomarkers for treatment monitoring in Diabetes (IMIDIA) consortium (www.imidia.org) established a comprehensive, unique multicentre biobank of human islets and pancreas tissues from organ donors and metabolically phenotyped pancreatectomised patients (PPP). Methods: Affymetrix microarrays were used to assess the islet transcriptome of islets isolated either by enzymatic digestion from 103 organ donors (OD), including 84 non-diabetic and 19 type 2 diabetic individuals, or by laser capture microdissection (LCM) from surgical specimens of 103 PPP, including 32 non-diabetic, 36 with type 2 diabetes, 15 with impaired glucose tolerance (IGT) and 20 with recent-onset diabetes (<1 year), conceivably secondary to the pancreatic disorder leading to surgery (type 3c diabetes). Bioinformatics tools were used to (1) compare the islet transcriptome of type 2 diabetic vs non-diabetic OD and PPP as well as vs IGT and type 3c diabetes within the PPP group; and (2) identify transcription factors driving gene co-expression modules correlated with insulin secretion ex vivo and glucose tolerance in vivo. Selected genes of interest were validated for their expression and function in beta cells. Results: Comparative transcriptomic analysis identified 19 genes differentially expressed (false discovery rate =0.05, fold change =1.5) in type 2 diabetic vs non-diabetic islets from OD and PPP. Nine out of these 19 dysregulated genes were not previously reported to be dysregulated in type 2 diabetic islets. Signature genes included TMEM37, which inhibited Ca2+-influx and insulin secretion in beta cells, and ARG2 and PPP1R1A, which promoted insulin secretion. Systems biology approaches identified HNF1A, PDX1 and RE

Published
2018

12. Cooperative development of logical modelling standards and tools with CoLoMoTo

Author

Naldi, A., Monteiro, P.T., Müssel, C., Tools, Kestler, H.A., Thieffry, D., Xenarios, I., Saez-Rodriguez, J., Helikar, T., Chaouiya, C., Consortium for Logical Models, Tools, Albert, R., Barberis, M., Calzone, L., Chaouiya, C., Chasapi, A., Cokelaer, T., Crespo, I., Dorier, J., Dräger, A., Helikar, T., Hernandez, C., Hucka, M., de Jong, H., Keating, SM., Kestler, HA., Klamt, S., Klarner, H., Laubenbacher, R., Novère, NL., Monteiro, PT., Müssel, C., Naldi, A., Niknejad, A., Rodriguez, N., Saez-Rodriguez, J., Siebert, H., Stoll, G., Thieffry, D., Xenarios, I., and Zañudo, JG.

Subjects
Animals, Cells/metabolism, Computer Simulation, Humans, Metabolic Networks and Pathways, Models, Theoretical, Societies, Scientific, Software/standards, Systems Biology/methods
Abstract

The identification of large regulatory and signalling networks involved in the control of crucial cellular processes calls for proper modelling approaches. Indeed, models can help elucidate properties of these networks, understand their behaviour and provide (testable) predictions by performing in silico experiments. In this context, qualitative, logical frameworks have emerged as relevant approaches, as demonstrated by a growing number of published models, along with new methodologies and software tools. This productive activity now requires a concerted effort to ensure model reusability and interoperability between tools. Following an outline of the logical modelling framework, we present the most important achievements of the Consortium for Logical Models and Tools, along with future objectives. Our aim is to advertise this open community, which welcomes contributions from all researchers interested in logical modelling or in related mathematical and computational developments.

Published
2015

13. Updates in Rhea-a manually curated resource of biochemical reactions

Author

Morgat, A., Axelsen, K.B., Lombardot, T., Alcántara, R., Aimo, L., Zerara, M., Niknejad, A., Belda, E., Hyka-Nouspikel, N., Coudert, E., Redaschi, N., Bougueleret, L., Steinbeck, C., Xenarios, I., and Bridge, A.

Abstract

Rhea (http://www.ebi.ac.uk/rhea) is a comprehensive and non-redundant resource of expert-curated biochemical reactions described using species from the ChEBI (Chemical Entities of Biological Interest) ontology of small molecules. Rhea has been designed for the functional annotation of enzymes and the description of genome-scale metabolic networks, providing stoichiometrically balanced enzyme-catalyzed reactions (covering the IUBMB Enzyme Nomenclature list and additional reactions), transport reactions and spontaneously occurring reactions. Rhea reactions are extensively curated with links to source literature and are mapped to other publicly available enzyme and pathway databases such as Reactome, BioCyc, KEGG and UniPathway, through manual curation and computational methods. Here we describe developments in Rhea since our last report in the 2012 database issue of Nucleic Acids Research. These include significant growth in the number of Rhea reactions and the inclusion of reactions involving complex macromolecules such as proteins, nucleic acids and other polymers that lie outside the scope of ChEBI. Together these developments will significantly increase the utility of Rhea as a tool for the description, analysis and reconciliation of genome-scale metabolic models.

Published
2015

14. The SIB Swiss Institute of Bioinformatics' resources: focus on curated databases

Author

Bultet, LA, Aguilar-Rodriguez, J, Ahrens, CH, Ahrne, EL, Ai, N, Aimo, L, Akalin, A, Aleksiev, T, Alocci, D, Altenhoff, A, Alves, I, Ambrosini, G, Pedone, PA, Angelina, P, Anisimova, M, Appel, R, Argoud-Puy, G, Arnold, K, Arpat, B, Artimo, P, Ascencao, K, Auchincloss, A, Axelsen, K, Gerritsen, VB, Bairoch, A, Barisal, P, Baratin, D, Barbato, A, Barbie, V, Barras, D, Barreiro, M, Barret, S, Bastian, F, Batista Neto, TM, Baudis, M, Beaudoing, E, Beckmann, JS, Bekkar, AK, Cammoun, LBH, Benmohammed, S, Bernard, M, Bertelli, C, Bertoni, M, Bienert, S, Bignucolo, O, Bilbao, A, Bilican, A, Blank, D, Blatter, M-C, Blum, L, Bocquet, J, Boeckmann, B, Bolleman, JT, Bordoli, L, Bosshard, L, Boucher, G, Bougueleret, L, Boutet, E, Bovigny, C, Bratulic, S, Breuza, L, Bridge, AJ, Britan, A, Brito, F, Frazao, JB, Bruggmann, R, Bucher, P, Burdet, F, Burger, L, Cabello, EM, Gomez, RMC, Calderon, S, Cannarozzi, G, Carl, S, Casas, CC, Catherinet, S, Perier, RC, Charpilloz, C, Chaskar, PD, Chen, W, Pepe, AC, Chopard, B, Chu, HY, Civic, N, Claassen, M, Clottu, S, Colombo, M, Cosandier, I, Coudert, E, Crespo, I, Creus, M, Cuche, B, Cuendet, MA, Cusin, I, Daga, N, Daina, A, Dauvillier, J, David, F, Davydov, I, Ferreira, MDSRM, de Beer, T, de Castro, E, de Santana, C, Delafontaine, J, Delorenzi, M, Delucinge-Vivier, C, Demirel, O, Derham, R, Dermitzakis, EM, Dib, L, Diene, S, Dilek, N, Dilmi, J, Domagalski, MJ, Dorier, J, Dornevil, D, Dousse, A, Dreos, R, Duchen, P, Roggli, PD, Duperret, ID, Durinx, C, Duvaud, S, Engler, R, Frkek, S, Lopez, PE, Fstreicher, A, Excoffier, L, Fabbretti, R, Falcone, J-L, Falquet, L, Famiglietti, ML, Ferreira, A-M, Feuermann, M, Filliettaz, M, Hegel, V, Foucal, A, Franceschini, A, Fucile, G, Gaidatzis, D, Garcia, V, Gasteiger, E, Gateau, A, Gatti, L, Gaudet, P, Gaudinat, A, Gehant, S, Gfeller, D, Gharib, WH, Ghraichy, M, Gidoin, C, Gil, M, Gleizes, A, Gobeill, J, Gonnet, G, Gos, A, Gotz, L, Gouy, A, Grbic, D, Groux, R, Gruaz-Gumowski, N, Grun, D, Gschwind, A, Guex, N, Gupta, S, Getaz, M, Haake, D, Haas, J, Hatzimanikatis, V, Heckel, G, Gardiol, DFH, Hinard, V, Hinz, U, Homicsko, K, Horlacher, O, Hosseini, S-R, Hotz, H-R, Hulo, C, Hundsrucker, C, Ibberson, M, Ilmjarv, S, Ioannidis, V, Ioannidis, P, Iseli, C, Ivanek, R, Iwaszkiewicz, J, Jacquet, P, Jacquot, M, Jagannathan, V, Jan, M, Jensen, J, Johansson, MU, Johner, N, Jungo, F, Junier, T, Kahraman, A, Katsantoni, M, Keller, G, Kerhornou, A, Khalid, F, Klingbiel, D, Kimljenovic, A, Kriventseva, E, Kryuchkova, N, Kumar, S, Kutalik, Z, Kuznetsov, D, Kuzyakiv, R, Lane, L, Lara, V, Ledesma, L, Leleu, M, Lemercier, P, Lew, D, Lieberherr, D, Liechti, R, Lisacek, F, Fischer, H, Litsios, G, Liu, J, Lombardot, T, Mace, A, Maffioletti, S, Mahi, M-A, Maiolo, M, Majjigapu, SR, Malmstrom, L, Mangold, V, Marek, D, Mariethoz, J, Marin, R, Martin, O, Martin, X, Martin-Campos, T, Mary, C, Masclaux, F, Masson, P, Meier, C, Messina, A, Lenoir, MM, Meyer, X, Michel, P-A, Michielin, O, Milanese, A, Missiaglia, E, Perez, JM, Caria, VM, Moret, P, Moretti, S, Morgat, A, Mottaz, A, Mottin, L, Mouscaz, Y, Mueller, M, Murri, R, Mylonas, R, Neuenschwander, S, Nikitin, F, Niknejad, A, Nouspikel, N, Nso, LN, Okoniewski, M, Omasits, U, Paccaud, B, Pachkov, M, Paesano, SG, Pagni, M, Palagi, PM, Pasche, E, Payne, JL, Pedruzzi, I, Peischl, S, Peitsch, M, Perlini, S, Pilbout, S, Podvinec, M, Pohlmann, R, Polizzi, D, Potter, D, Poux, S, Pozzato, M, Pradervand, S, Praz, V, Pruess, M, Pujadas, E, Racle, J, Raschi, M, Ratib, O, Rausell, A, de Laval, VR, Redaschi, N, Rempfer, C, Ren, G, Vandati, RAR, Rib, L, Grognuz, OR, Altimiras, ER, Rivoire, C, Robin, T, Robinson-Rechavi, M, Rodrigues, J, Roechert, B, Roelli, P, Romano, V, Rossier, G, Roth, A, Rougemont, J, Roux, J, Royo, H, Ruch, P, Ruinelli, M, Rustom, M, Sates, A, Roehrig, UF, Rueeger, S, Salamin, N, Sankar, M, Sarkar, N, Saxenhofer, M, Schaeffer, M, Schaerli, Y, Schaper, E, Schmid, A, Schmid, E, Schmid, C, Schmid, M, Schmidt, S, Schmocker, D, Schneider, M, Schuepbach, T, Schwede, T, Schuetz, F, Sengstag, T, Serrano, M, Sethi, A, Shahmirzadi, O, Sigrist, C, Silvestro, D, Simao Neto, FA, Simillion, C, Simonovic, M, Skunca, N, Sluzek, K, Soneson, C, Sprouffske, K, Stadler, M, Staehli, S, Stevenson, B, Stockinger, H, Straszewski, J, Stricker, T, Studer, G, Stutz, A, Suffiotti, M, Sundaram, S, Szklarczyk, D, Szovenyi, P, Tegenfeldt, F, Teixeira, D, Tellenbach, S, Smith, AAT, Tognolli, M, Topolsky, I, Thuong, VDT, Tsantoulis, P, Tzika, AC, Agote, AU, van Nimwegen, E, von Mering, C, Varadarajan, A, Veranneman, M, Verbregue, L, Veuthey, A-L, Vishnyakova, D, Vyas, R, Wagner, A, Walther, D, Wan, HW, Wang, M, Waterhouse, R, Waterhouse, A, Wicki, A, Wigger, L, Wirapati, P, Witschi, U, Wyder, S, Wyler, K, Wuethrich, D, Xenarios, I, Yamada, K, Yan, Z, Yasrebi, H, Zahn, M, Zangger, N, Zdobnov, E, Zerzion, D, Zoete, V, Zoller, S, Bultet, LA, Aguilar-Rodriguez, J, Ahrens, CH, Ahrne, EL, Ai, N, Aimo, L, Akalin, A, Aleksiev, T, Alocci, D, Altenhoff, A, Alves, I, Ambrosini, G, Pedone, PA, Angelina, P, Anisimova, M, Appel, R, Argoud-Puy, G, Arnold, K, Arpat, B, Artimo, P, Ascencao, K, Auchincloss, A, Axelsen, K, Gerritsen, VB, Bairoch, A, Barisal, P, Baratin, D, Barbato, A, Barbie, V, Barras, D, Barreiro, M, Barret, S, Bastian, F, Batista Neto, TM, Baudis, M, Beaudoing, E, Beckmann, JS, Bekkar, AK, Cammoun, LBH, Benmohammed, S, Bernard, M, Bertelli, C, Bertoni, M, Bienert, S, Bignucolo, O, Bilbao, A, Bilican, A, Blank, D, Blatter, M-C, Blum, L, Bocquet, J, Boeckmann, B, Bolleman, JT, Bordoli, L, Bosshard, L, Boucher, G, Bougueleret, L, Boutet, E, Bovigny, C, Bratulic, S, Breuza, L, Bridge, AJ, Britan, A, Brito, F, Frazao, JB, Bruggmann, R, Bucher, P, Burdet, F, Burger, L, Cabello, EM, Gomez, RMC, Calderon, S, Cannarozzi, G, Carl, S, Casas, CC, Catherinet, S, Perier, RC, Charpilloz, C, Chaskar, PD, Chen, W, Pepe, AC, Chopard, B, Chu, HY, Civic, N, Claassen, M, Clottu, S, Colombo, M, Cosandier, I, Coudert, E, Crespo, I, Creus, M, Cuche, B, Cuendet, MA, Cusin, I, Daga, N, Daina, A, Dauvillier, J, David, F, Davydov, I, Ferreira, MDSRM, de Beer, T, de Castro, E, de Santana, C, Delafontaine, J, Delorenzi, M, Delucinge-Vivier, C, Demirel, O, Derham, R, Dermitzakis, EM, Dib, L, Diene, S, Dilek, N, Dilmi, J, Domagalski, MJ, Dorier, J, Dornevil, D, Dousse, A, Dreos, R, Duchen, P, Roggli, PD, Duperret, ID, Durinx, C, Duvaud, S, Engler, R, Frkek, S, Lopez, PE, Fstreicher, A, Excoffier, L, Fabbretti, R, Falcone, J-L, Falquet, L, Famiglietti, ML, Ferreira, A-M, Feuermann, M, Filliettaz, M, Hegel, V, Foucal, A, Franceschini, A, Fucile, G, Gaidatzis, D, Garcia, V, Gasteiger, E, Gateau, A, Gatti, L, Gaudet, P, Gaudinat, A, Gehant, S, Gfeller, D, Gharib, WH, Ghraichy, M, Gidoin, C, Gil, M, Gleizes, A, Gobeill, J, Gonnet, G, Gos, A, Gotz, L, Gouy, A, Grbic, D, Groux, R, Gruaz-Gumowski, N, Grun, D, Gschwind, A, Guex, N, Gupta, S, Getaz, M, Haake, D, Haas, J, Hatzimanikatis, V, Heckel, G, Gardiol, DFH, Hinard, V, Hinz, U, Homicsko, K, Horlacher, O, Hosseini, S-R, Hotz, H-R, Hulo, C, Hundsrucker, C, Ibberson, M, Ilmjarv, S, Ioannidis, V, Ioannidis, P, Iseli, C, Ivanek, R, Iwaszkiewicz, J, Jacquet, P, Jacquot, M, Jagannathan, V, Jan, M, Jensen, J, Johansson, MU, Johner, N, Jungo, F, Junier, T, Kahraman, A, Katsantoni, M, Keller, G, Kerhornou, A, Khalid, F, Klingbiel, D, Kimljenovic, A, Kriventseva, E, Kryuchkova, N, Kumar, S, Kutalik, Z, Kuznetsov, D, Kuzyakiv, R, Lane, L, Lara, V, Ledesma, L, Leleu, M, Lemercier, P, Lew, D, Lieberherr, D, Liechti, R, Lisacek, F, Fischer, H, Litsios, G, Liu, J, Lombardot, T, Mace, A, Maffioletti, S, Mahi, M-A, Maiolo, M, Majjigapu, SR, Malmstrom, L, Mangold, V, Marek, D, Mariethoz, J, Marin, R, Martin, O, Martin, X, Martin-Campos, T, Mary, C, Masclaux, F, Masson, P, Meier, C, Messina, A, Lenoir, MM, Meyer, X, Michel, P-A, Michielin, O, Milanese, A, Missiaglia, E, Perez, JM, Caria, VM, Moret, P, Moretti, S, Morgat, A, Mottaz, A, Mottin, L, Mouscaz, Y, Mueller, M, Murri, R, Mylonas, R, Neuenschwander, S, Nikitin, F, Niknejad, A, Nouspikel, N, Nso, LN, Okoniewski, M, Omasits, U, Paccaud, B, Pachkov, M, Paesano, SG, Pagni, M, Palagi, PM, Pasche, E, Payne, JL, Pedruzzi, I, Peischl, S, Peitsch, M, Perlini, S, Pilbout, S, Podvinec, M, Pohlmann, R, Polizzi, D, Potter, D, Poux, S, Pozzato, M, Pradervand, S, Praz, V, Pruess, M, Pujadas, E, Racle, J, Raschi, M, Ratib, O, Rausell, A, de Laval, VR, Redaschi, N, Rempfer, C, Ren, G, Vandati, RAR, Rib, L, Grognuz, OR, Altimiras, ER, Rivoire, C, Robin, T, Robinson-Rechavi, M, Rodrigues, J, Roechert, B, Roelli, P, Romano, V, Rossier, G, Roth, A, Rougemont, J, Roux, J, Royo, H, Ruch, P, Ruinelli, M, Rustom, M, Sates, A, Roehrig, UF, Rueeger, S, Salamin, N, Sankar, M, Sarkar, N, Saxenhofer, M, Schaeffer, M, Schaerli, Y, Schaper, E, Schmid, A, Schmid, E, Schmid, C, Schmid, M, Schmidt, S, Schmocker, D, Schneider, M, Schuepbach, T, Schwede, T, Schuetz, F, Sengstag, T, Serrano, M, Sethi, A, Shahmirzadi, O, Sigrist, C, Silvestro, D, Simao Neto, FA, Simillion, C, Simonovic, M, Skunca, N, Sluzek, K, Soneson, C, Sprouffske, K, Stadler, M, Staehli, S, Stevenson, B, Stockinger, H, Straszewski, J, Stricker, T, Studer, G, Stutz, A, Suffiotti, M, Sundaram, S, Szklarczyk, D, Szovenyi, P, Tegenfeldt, F, Teixeira, D, Tellenbach, S, Smith, AAT, Tognolli, M, Topolsky, I, Thuong, VDT, Tsantoulis, P, Tzika, AC, Agote, AU, van Nimwegen, E, von Mering, C, Varadarajan, A, Veranneman, M, Verbregue, L, Veuthey, A-L, Vishnyakova, D, Vyas, R, Wagner, A, Walther, D, Wan, HW, Wang, M, Waterhouse, R, Waterhouse, A, Wicki, A, Wigger, L, Wirapati, P, Witschi, U, Wyder, S, Wyler, K, Wuethrich, D, Xenarios, I, Yamada, K, Yan, Z, Yasrebi, H, Zahn, M, Zangger, N, Zdobnov, E, Zerzion, D, Zoete, V, and Zoller, S

Abstract

The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) provides world-class bioinformatics databases, software tools, services and training to the international life science community in academia and industry. These solutions allow life scientists to turn the exponentially growing amount of data into knowledge. Here, we provide an overview of SIB's resources and competence areas, with a strong focus on curated databases and SIB's most popular and widely used resources. In particular, SIB's Bioinformatics resource portal ExPASy features over 150 resources, including UniProtKB/Swiss-Prot, ENZYME, PROSITE, neXtProt, STRING, UniCarbKB, SugarBindDB, SwissRegulon, EPD, arrayMap, Bgee, SWISS-MODEL Repository, OMA, OrthoDB and other databases, which are briefly described in this article.

Published
2016

15. The Gene Ontology in 2010: extensions and refinements

Author

Berardini, Tz, Li, D, Huala, E, Bridges, S, Burgess, S, Mccarthy, F, Carbon, S, Lewis, Se, Mungall, Cj, Abdulla, A, Wood, V, Feltrin, E, Valle, Giorgio, Chisholm, Rl, Fey, P, Gaudet, P, Kibbe, W, Basu, S, Bushmanova, Y, Eilbeck, K, Siegele, Da, Mcintosh, B, Renfro, D, Zweifel, A, Hu, Jc, Ashburner, M, Tweedie, S, ALAM FARUQUE, Y, Apweiler, R, Auchinchloss, A, Bairoch, A, Barrell, D, Binns, D, Blatter, Mc, Bougueleret, L, Boutet, E, Breuza, L, Bridge, A, Browne, P, Chan, Wm, Coudert, E, Daugherty, L, Dimmer, E, Eberhardt, R, Estreicher, A, Famiglietti, L, FERRO ROJAS, S, Feuermann, M, Foulger, R, GRUAZ GUMOWSKI, N, Hinz, U, Huntley, R, Jimenez, S, Jungo, F, Keller, G, Laiho, K, Legge, D, Lemercier, P, Lieberherr, D, Magrane, M, O'Donovan, C, Pedruzzi, I, Poux, S, Rivoire, C, Roechert, B, Sawford, T, Schneider, M, Stanley, E, Stutz, A, Sundaram, S, Tognolli, M, Xenarios, I, Harris, Ma, Deegan, Ji, Ireland, A, Lomax, J, Jaiswal, P, Chibucos, M, Giglio, Mg, Wortman, J, Hannick, L, Madupu, R, Botstein, D, Dolinski, K, Livstone, Ms, Oughtred, R, Blake, Ja, Bult, C, Diehl, Ad, Dolan, M, Drabkin, H, Eppig, Jt, Hill, Dp, Ni, L, Ringwald, M, Sitnikov, D, Collmer, C, TORTO ALALIBO, T, Laulederkind, S, Shimoyama, M, Twigger, S, D'Eustachio, P, Matthews, L, Balakrishnan, R, Binkley, G, Cherry, Jm, Christie, Kr, Costanzo, Mc, Engel, Sr, Fisk, Dg, Hirschman, Je, Hitz, Bc, Hong, El, Krieger, Cj, Miyasato, Sr, Nash, Rs, Park, J, Skrzypek, Ms, Weng, S, Wong, Ed, Aslett, M, Chan, J, Kishore, R, Sternberg, P, VAN AUKE, K, Khodiyar, Vk, Lovering, Rc, Talmud, Pj, Howe, D, Westerfield, M., Gene Ontology Consortium, Berardini, TZ., Li, D., Huala, E., Bridges, S., Burgess, S., McCarthy, F., Carbon, S., Lewis, SE., Mungall, CJ., Abdulla, A., Wood, V., Feltrin, E., Valle, G., Chisholm, RL., Fey, P., Gaudet, P., Kibbe, W., Basu, S., Bushmanova, Y., Eilbeck, K., Siegele, DA., McIntosh, B., Renfro, D., Zweifel, A., Hu, JC., Ashburner, M., Tweedie, S., Alam-Faruque, Y., Apweiler, R., Auchinchloss, A., Bairoch, A., Barrell, D., Binns, D., Blatter, MC., Bougueleret, L., Boutet, E., Breuza, L., Bridge, A., Browne, P., Chan, WM., Coudert, E., Daugherty, L., Dimmer, E., Eberhardt, R., Estreicher, A., Famiglietti, L., Ferro-Rojas, S., Feuermann, M., Foulger, R., Gruaz-Gumowski, N., Hinz, U., Huntley, R., Jimenez, S., Jungo, F., Keller, G., Laiho, K., Legge, D., Lemercier, P., Lieberherr, D., Magrane, M., O'Donovan, C., Pedruzzi, I., Poux, S., Rivoire, C., Roechert, B., Sawford, T., Schneider, M., Stanley, E., Stutz, A., Sundaram, S., Tognolli, M., Xenarios, I., Harris, MA., Deegan, JI., Ireland, A., Lomax, J., Jaiswal, P., Chibucos, M., Giglio, MG., Wortman, J., Hannick, L., Madupu, R., Botstein, D., Dolinski, K., Livstone, MS., Oughtred, R., Blake, JA., Bult, C., Diehl, AD., Dolan, M., Drabkin, H., Eppig, JT., Hill, DP., Ni, L., Ringwald, M., Sitnikov, D., Collmer, C., Torto-Alalibo, T., Laulederkind, S., Shimoyama, M., Twigger, S., D'Eustachio, P., Matthews, L., Balakrishnan, R., Binkley, G., Cherry, JM., Christie, KR., Costanzo, MC., Engel, SR., Fisk, DG., Hirschman, JE., Hitz, BC., Hong, EL., Krieger, CJ., Miyasato, SR., Nash, RS., Park, J., Skrzypek, MS., Weng, S., Wong, ED., Aslett, M., Chan, J., Kishore, R., Sternberg, P., Van Auke, K., Khodiyar, VK., Lovering, RC., Talmud, PJ., Howe, D., and Westerfield, M.

Subjects
Information Storage and Retrieval, Ontology (information science), Biology, Bioinformatics, World Wide Web, Set (abstract data type), 03 medical and health sciences, Annotation, User-Computer Interface, 0302 clinical medicine, Controlled vocabulary, Databases, Genetic, Genetics, Animals, Humans, Databases, Protein, Computational Biology/methods, Computational Biology/trends, Databases, Nucleic Acid, Genomics, Information Storage and Retrieval/methods, Internet, Software, Vocabulary, Controlled, 030304 developmental biology, Structure (mathematical logic), 0303 health sciences, Gene ontology, business.industry, Computational Biology, Usability, Articles, ComputingMethodologies_GENERAL, business, 030217 neurology & neurosurgery
Abstract

The Gene Ontology (GO) Consortium (http://www.geneontology.org) (GOC) continues to develop, maintain and use a set of structured, controlled vocabularies for the annotation of genes, gene products and sequences. The GO ontologies are expanding both in content and in structure. Several new relationship types have been introduced and used, along with existing relationships, to create links between and within the GO domains. These improve the representation of biology, facilitate querying, and allow GO developers to systematically check for and correct inconsistencies within the GO. Gene product annotation using GO continues to increase both in the number of total annotations and in species coverage. GO tools, such as OBO-Edit, an ontology-editing tool, and AmiGO, the GOC ontology browser, have seen major improvements in functionality, speed and ease of use.

Published
2010

16. Cooperative development of logical modelling standards and tools with CoLoMoTo

Author

Naldi, A., Monteiro, P.T., Müssel, C., Kestler, H.A., Thieffry, D., Xenarios, I., Saez-Rodriguez, J., Helikar, T., Chaouiya, C., Albert, R., Barberis, M., Calzone, L., Chasapi, A., Cokelaer, T., Crespo, I., Dorier, J., Dräger, A., Hernandez, C., Hucka, M., de Jong, H., Keating, S.M., Klamt, S., Klarner, H., Laubenbacher, R., Le Novère, N., Niknejad, A., Rodriguez, N., Siebert, H., Stoll, G., Zañudo, J.G.T., Synthetic Systems Biology (SILS, FNWI), Systems Biology, Faculty of Science, and SILS Other Research (FNWI)

Subjects
Societies, Scientific, Statistics and Probability, Computer science, Cells, Systems biology, Control (management), Interoperability, Context (language use), Biochemistry, 03 medical and health sciences, 0302 clinical medicine, Software, Animals, Humans, Computer Simulation, Molecular Biology, 030304 developmental biology, Reusability, 0303 health sciences, business.industry, Management science, Systems Biology, Models, Theoretical, Computer Science Applications, Computational Mathematics, Identification (information), Computational Theory and Mathematics, Cooperative development, business, Metabolic Networks and Pathways, 030217 neurology & neurosurgery, Logical modelling
Abstract

The identification of large regulatory and signalling networks involved in the control of crucial cellular processes calls for proper modelling approaches. Indeed, models can help elucidate properties of these networks, understand their behaviour and provide (testable) predictions by performing in silico experiments. In this context, qualitative, logical frameworks have emerged as relevant approaches, as demonstrated by a growing number of published models, along with new methodologies and software tools. This productive activity now requires a concerted effort to ensure model reusability and interoperability between tools. Following an outline of the logical modelling framework, we present the most important achievements of the Consortium for Logical Models and Tools, along with future objectives. Our aim is to advertise this open community, which welcomes contributions from all researchers interested in logical modelling or in related mathematical and computational developments. Contact: contact@colomoto.org

Published
2014

19. Animal Toxins: How is Complexity Represented in Databases?

Author

Jungo, F., Estreicher, A., Bairoch, A., Bougueleret, L., and Xenarios, I.

Subjects
animal toxin, ArachnoServer, ATDB, ConoServer, database, Tox-Prot, UniProtKB/Swiss-Prot, venom protein
Abstract

Peptide toxins synthesized by venomous animals have been extensively studied in the last decades. To be useful to the scientific community, this knowledge has been stored, annotated and made easy to retrieve by several databases. The aim of this article is to present what type of information users can access from each database. ArachnoServer and ConoServer focus on spider toxins and cone snail toxins, respectively. UniProtKB, a generalist protein knowledgebase, has an animal toxin-dedicated annotation program that includes toxins from all venomous animals. Finally, the ATDB metadatabase compiles data and annotations from other databases and provides toxin ontology.

Published
2010

20. The mzTab data exchange format: Communicating mass-spectrometry-based proteomics and metabolomics experimental results to a wider audience

Author

University of Cambridge, Griss, J., Jones, A.R., Sachsenberg, T., Walzer, M., Gatto, Laurent, Hartler, J., Thallinger, G.G., Salek, R.M., Steinbeck, C., Neuhauser, N., Cox, J., Neumann, S., Fan, J., Reisinger, F., Xu, Q.-W., Del Toro, N., Pérez-Riverol, Y., Ghali, F., Bandeira, N., Xenarios, I., Kohlbacher, O., Vizcaíno, J.A., Hermjakob, H., University of Cambridge, Griss, J., Jones, A.R., Sachsenberg, T., Walzer, M., Gatto, Laurent, Hartler, J., Thallinger, G.G., Salek, R.M., Steinbeck, C., Neuhauser, N., Cox, J., Neumann, S., Fan, J., Reisinger, F., Xu, Q.-W., Del Toro, N., Pérez-Riverol, Y., Ghali, F., Bandeira, N., Xenarios, I., Kohlbacher, O., Vizcaíno, J.A., and Hermjakob, H.

Published
2014

21. ProteomeXchange provides globally coordinated proteomics data submission and dissemination

Author

University of Cambridge, Vizcaíno, J.A., Deutsch, E.W., Wang, R., Csordas, A., Reisinger, F., Ríos, D., Dianes, J.A., Sun, Z., Farrah, T., Bandeira, N., Binz, P.-A., Xenarios, I., Eisenacher, M., Mayer, G., Gatto, Laurent, Campos, A., Chalkley, R.J., Kraus, H.-J., Albar, J.P., Martinez-Bartolomé, S., Apweiler, R., Omenn, G.S., Martens, L., Jones, A.R., Hermjakob, H., University of Cambridge, Vizcaíno, J.A., Deutsch, E.W., Wang, R., Csordas, A., Reisinger, F., Ríos, D., Dianes, J.A., Sun, Z., Farrah, T., Bandeira, N., Binz, P.-A., Xenarios, I., Eisenacher, M., Mayer, G., Gatto, Laurent, Campos, A., Chalkley, R.J., Kraus, H.-J., Albar, J.P., Martinez-Bartolomé, S., Apweiler, R., Omenn, G.S., Martens, L., Jones, A.R., and Hermjakob, H.

Published
2014

22. Quantifying ChIP-seq data: a spiking method providing an internal reference for sample-to-sample normalization

Author

Bonhoure, N, Bounova, G, Bernasconi, D, Praz, V, Lammers, F, Canella, D, Willis, I M, Herr, W, Hernandez, N, Delorenzi, M, Deplancke, B, Desvergne, B, Guex, N, Naef, F, Rougemont, J, Schibler, U, Andersin, T, Cousin, P, Gilardi, F, Gos, P, Raghav, S, Villeneuve, D, Fabbretti, R, Vlegel, V, Xenarios, I, Migliavacca, E, David, F, Jarosz, Y, Kuznetsov, D, Liechti, R, Martin, O, Delafontaine, J, Cajan, J, Gustafson, K, Krier, I, Leleu, M, Molina, N, Naldi, A, Rib, L, Symul, L, Bonhoure, N, Bounova, G, Bernasconi, D, Praz, V, Lammers, F, Canella, D, Willis, I M, Herr, W, Hernandez, N, Delorenzi, M, Deplancke, B, Desvergne, B, Guex, N, Naef, F, Rougemont, J, Schibler, U, Andersin, T, Cousin, P, Gilardi, F, Gos, P, Raghav, S, Villeneuve, D, Fabbretti, R, Vlegel, V, Xenarios, I, Migliavacca, E, David, F, Jarosz, Y, Kuznetsov, D, Liechti, R, Martin, O, Delafontaine, J, Cajan, J, Gustafson, K, Krier, I, Leleu, M, Molina, N, Naldi, A, Rib, L, and Symul, L

Published
2014

24. Broadening the Horizon - Level 2.5 of the HUPO-PSI Format for Molecular

Author

Samuel Kerrien, Sandra Orchard, Luisa Montecchi-Palazzi, Bruno Aranda, Af Quinn, Vinod, N., Gary Bader, Xenarios, I., Jérôme Wojcik, David James Sherman, Mike Tyers, John Salama, Susan Moore, Arnaud Ceol, Chatr-Aryamontri, A., Oesterheld, M., Stumpflen, V., Lucas Salwinski, Nerothin, J., Cerami, E., Me Cusick, Marc Vidal, Gilson, M., John Armstrong, Woollard, P., Chris Hogue, David Eisenberg, Gianni Cesareni, Rolf Apweiler, Henning Hermjakob, Laboratoire Bordelais de Recherche en Informatique (LaBRI), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB), and Sherman, David James

Subjects
[INFO.INFO-OH] Computer Science [cs]/Other [cs.OH], [INFO.INFO-OH]Computer Science [cs]/Other [cs.OH]
Published
2007

25. The minimum information about a proteomics experiment (MIAPE)

Author

Taylor, C.F., Paton, N.W., Lilley, K.S., Binz, P-A, Julian, R.K., Jones, A.R., Zhu, W., Apweiler, R., Aebersold, R., Deutsch, E.W., Dunn, M.J., Heck, A.J.R., Leitner, A., Macht, M., Mann, M., Martens, L., Neubert, T.A., Patterson, S.D., Ping, P., Seymour, S.L., Souda, P, Tsugita, A., Vandekerckhove, J., Vondriska, T.M., Whitelegge, J.P., Wilkins, M.R., Xenarios, I., Yates, J.R., Hermjakob, H., Biomoleculaire Massaspectrometrie, Massaspectrometrie, Dep Scheikunde, and Dep Farmaceutische wetenschappen

Subjects
Farmacie(FARM)
Published
2007

27. Genome-wide profiling of the cardiac transcriptome after myocardial infarction identifies novel heart-specific long non-coding RNAs

Author

Ounzain, S., primary, Micheletti, R., additional, Beckmann, T., additional, Schroen, B., additional, Alexanian, M., additional, Pezzuto, I., additional, Crippa, S., additional, Nemir, M., additional, Sarre, A., additional, Johnson, R., additional, Dauvillier, J., additional, Burdet, F., additional, Ibberson, M., additional, Guigo, R., additional, Xenarios, I., additional, Heymans, S., additional, and Pedrazzini, T., additional

Published
2014
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28. The EMPRES-i genetic module: a novel tool linking epidemiological outbreak information and genetic characteristics of influenza viruses

Author

Claes, F., primary, Kuznetsov, D., additional, Liechti, R., additional, Von Dobschuetz, S., additional, Dinh Truong, B., additional, Gleizes, A., additional, Conversa, D., additional, Colonna, A., additional, Demaio, E., additional, Ramazzotto, S., additional, Larfaoui, F., additional, Pinto, J., additional, Le Mercier, P., additional, Xenarios, I., additional, and Dauphin, G., additional

Published
2014
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29. Protein interactions: two methods for assessment of the reliability of high throughput observations

Author

Charlotte Deane, Salwiński, L., Xenarios, I., and Eisenberg, D.

Subjects
parasitic diseases
Abstract

High throughput methods for detecting protein interactions require assessment of their accuracy. We present two forms of computational assessment. The first method is the expression profile reliability (EPR) index. The EPR index estimates the biologically relevant fraction of protein interactions detected in a high throughput screen. It does so by comparing the RNA expression profiles for the proteins whose interactions are found in the screen with expression profiles for known interacting and non-interacting pairs of proteins. The second form of assessment is the paralogous verification method (PVM). This method judges an interaction likely if the putatively interacting pair has paralogs that also interact. In contrast to the EPR index, which evaluates datasets of interactions, PVM scores individual interactions. On a test set, PVM identifies correctly 40% of true interactions with a false positive rate of approximately 1%. EPR and PVM were applied to the Database of Interacting Proteins (DIP), a large and diverse collection of protein-protein interactions that contains over 8000 Saccharomyces cerevisiae pairwise protein interactions. Using these two methods, we estimate that approximately 50% of them are reliable, and with the aid of PVM we identify confidently 3003 of them. Web servers for both the PVM and EPR methods are available on the DIP website (dip.doe-mbi.ucla.edu/Services.cgi).

Published
2002

30. Analysis of stop-gain and frameshift variants in human innate immunity genes

Author

Rausell A Mohammadi P McLaren PJ Bartha I Xenarios I Fellay J Telenti A

Abstract

Loss of function variants in innate immunity genes are associated with Mendelian disorders in the form of primary immunodeficiencies. Recent resequencing projects report that stop gains and frameshifts are collectively prevalent in humans and could be responsible for some of the inter individual variability in innate immune response. Current computational approaches evaluating loss of function in genes carrying these variants rely on gene level characteristics such as evolutionary conservation and functional redundancy across the genome. However innate immunity genes represent a particular case because they are more likely to be under positive selection and duplicated. To create a ranking of severity that would be applicable to innate immunity genes we evaluated 17764 stop gain and 13915 frameshift variants from the NHLBI Exome Sequencing Project and 1000 Genomes Project. Sequence based features such as loss of functional domains isoform specific truncation and nonsense mediated decay were found to correlate with variant allele frequency and validated with gene expression data. We integrated these features in a Bayesian classification scheme and benchmarked its use in predicting pathogenic variants against Online Mendelian Inheritance in Man (OMIM) disease stop gains and frameshifts. The classification scheme was applied in the assessment of 335 stop gains and 236 frameshifts affecting 227 interferon stimulated genes. The sequence based score ranks variants in innate immunity genes according to their potential to cause disease and complements existing gene based pathogenicity scores. Specifically the sequence based score improves measurement of functional gene impairment discriminates across different variants in a given gene and appears particularly useful for analysis of less conserved genes.

Published
2014

31. The genome of the fire ant Solenopsis invicta

Author

Wurm, Y., Wang, J., Riba-Grognuz, O., Corona, M., Nygaard, S., Hunt, B. G., Ingram, K. K., Falquet, L., Nipitwattanaphon, M., Gotzek, D., Dijkstra, M. B., Oettler, J., Comtesse, F., Shih, C. J., Wu, W. J., Yang, C. C., Thomas, J., Beaudoing, E., Pradervand, S., Flegel, V., Cook, E. D., Fabbretti, R., Stockinger, H., Long, L., Farmerie, W. G., Oakey, J., Boomsma, J. J., Pamilo, P., Yi, S. V., Heinze, J., Goodisman, M. A. D., Farinelli, L., Harshman, K., Hulo, N., Cerutti, L., Xenarios, I., Shoemaker, D., Keller, L., Wurm, Y., Wang, J., Riba-Grognuz, O., Corona, M., Nygaard, S., Hunt, B. G., Ingram, K. K., Falquet, L., Nipitwattanaphon, M., Gotzek, D., Dijkstra, M. B., Oettler, J., Comtesse, F., Shih, C. J., Wu, W. J., Yang, C. C., Thomas, J., Beaudoing, E., Pradervand, S., Flegel, V., Cook, E. D., Fabbretti, R., Stockinger, H., Long, L., Farmerie, W. G., Oakey, J., Boomsma, J. J., Pamilo, P., Yi, S. V., Heinze, J., Goodisman, M. A. D., Farinelli, L., Harshman, K., Hulo, N., Cerutti, L., Xenarios, I., Shoemaker, D., and Keller, L.

Abstract

Ants have evolved very complex societies and are key ecosystem members. Some ants, such as the fire ant Solenopsis invicta, are also major pests. Here, we present a draft genome of S. invicta, assembled from Roche 454 and Illumina sequencing reads obtained from a focal haploidmale and his brothers.Weused comparative genomic methods to obtain insight into the unique features of the S. invicta genome. For example, we found that this genome harbors four adjacent copies of vitellogenin. A phylogenetic analysis revealed that an ancestral vitellogenin gene first underwent a duplication that was followed by possibly independent duplications of each of the daughter vitellogenins. The vitellogenin genes have undergone subfunctionalization with queen- and worker-specific expression, possibly reflecting differential selection acting on the queen andworker castes. Additionally, we identified more than 400 putative olfactory receptors of which at least 297 are intact. This represents the largest repertoire reported so far in insects. S. invicta also harbors an expansion of a specific family of lipid-processing genes, two putative orthologs to the transformer/feminizer sex differentiation gene, a functional DNA methylation system, and a single putative telomerase ortholog. EST data indicate that this S. invicta telomerase ortholog has at least four spliceforms that differ in their use of two sets ofmutually exclusive exons. Someof these and other unique aspects of the fire ant genome are likely linked to the complex social behavior of this species.

Published
2011

32. The Microbe browser for comparative genomics

Author

Gattiker, A, Dessimoz, C, Schneider, A, Xenarios, I, Pagni, M, Rougemont, J, Gattiker, A, Dessimoz, C, Schneider, A, Xenarios, I, Pagni, M, and Rougemont, J

Abstract

The Microbe browser is a web server providing comparative microbial genomics data. It offers comprehensive, integrated data from GenBank, RefSeq, UniProt, InterPro, Gene Ontology and the Orthologs Matrix Project (OMA) database, displayed along with gene predictions from five software packages. The Microbe browser is daily updated from the source databases and includes all completely sequenced bacterial and archaeal genomes. The data are displayed in an easy-to-use, interactive website based on Ensembl software. The Microbe browser is available at http://microbe.vital-it.ch/. Programmatic access is available through the OMA application programming interface (API) at http://microbe.vital-it.ch/api

Published
2009

33. The minimum information about a proteomics experiment (MIAPE)

Author

Biomoleculaire Massaspectrometrie, Massaspectrometrie, Dep Scheikunde, Dep Farmaceutische wetenschappen, Taylor, C.F., Paton, N.W., Lilley, K.S., Binz, P-A, Julian, R.K., Jones, A.R., Zhu, W., Apweiler, R., Aebersold, R., Deutsch, E.W., Dunn, M.J., Heck, A.J.R., Leitner, A., Macht, M., Mann, M., Martens, L., Neubert, T.A., Patterson, S.D., Ping, P., Seymour, S.L., Souda, P, Tsugita, A., Vandekerckhove, J., Vondriska, T.M., Whitelegge, J.P., Wilkins, M.R., Xenarios, I., Yates, J.R., Hermjakob, H., Biomoleculaire Massaspectrometrie, Massaspectrometrie, Dep Scheikunde, Dep Farmaceutische wetenschappen, Taylor, C.F., Paton, N.W., Lilley, K.S., Binz, P-A, Julian, R.K., Jones, A.R., Zhu, W., Apweiler, R., Aebersold, R., Deutsch, E.W., Dunn, M.J., Heck, A.J.R., Leitner, A., Macht, M., Mann, M., Martens, L., Neubert, T.A., Patterson, S.D., Ping, P., Seymour, S.L., Souda, P, Tsugita, A., Vandekerckhove, J., Vondriska, T.M., Whitelegge, J.P., Wilkins, M.R., Xenarios, I., Yates, J.R., and Hermjakob, H.

Published
2007

35. ExPASy: SIB bioinformatics resource portal

Author

Artimo, P., primary, Jonnalagedda, M., additional, Arnold, K., additional, Baratin, D., additional, Csardi, G., additional, de Castro, E., additional, Duvaud, S., additional, Flegel, V., additional, Fortier, A., additional, Gasteiger, E., additional, Grosdidier, A., additional, Hernandez, C., additional, Ioannidis, V., additional, Kuznetsov, D., additional, Liechti, R., additional, Moretti, S., additional, Mostaguir, K., additional, Redaschi, N., additional, Rossier, G., additional, Xenarios, I., additional, and Stockinger, H., additional

Published
2012
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36. The UniProt-GO Annotation database in 2011

Author

Dimmer, E. C., primary, Huntley, R. P., additional, Alam-Faruque, Y., additional, Sawford, T., additional, O'Donovan, C., additional, Martin, M. J., additional, Bely, B., additional, Browne, P., additional, Mun Chan, W., additional, Eberhardt, R., additional, Gardner, M., additional, Laiho, K., additional, Legge, D., additional, Magrane, M., additional, Pichler, K., additional, Poggioli, D., additional, Sehra, H., additional, Auchincloss, A., additional, Axelsen, K., additional, Blatter, M.-C., additional, Boutet, E., additional, Braconi-Quintaje, S., additional, Breuza, L., additional, Bridge, A., additional, Coudert, E., additional, Estreicher, A., additional, Famiglietti, L., additional, Ferro-Rojas, S., additional, Feuermann, M., additional, Gos, A., additional, Gruaz-Gumowski, N., additional, Hinz, U., additional, Hulo, C., additional, James, J., additional, Jimenez, S., additional, Jungo, F., additional, Keller, G., additional, Lemercier, P., additional, Lieberherr, D., additional, Masson, P., additional, Moinat, M., additional, Pedruzzi, I., additional, Poux, S., additional, Rivoire, C., additional, Roechert, B., additional, Schneider, M., additional, Stutz, A., additional, Sundaram, S., additional, Tognolli, M., additional, Bougueleret, L., additional, Argoud-Puy, G., additional, Cusin, I., additional, Duek- Roggli, P., additional, Xenarios, I., additional, and Apweiler, R., additional

Published
2011
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39. EuroDia: a beta-cell gene expression resource

Author

Liechti, R., primary, Csardi, G., additional, Bergmann, S., additional, Schutz, F., additional, Sengstag, T., additional, Boj, S. F., additional, Servitja, J.-M., additional, Ferrer, J., additional, Van Lommel, L., additional, Schuit, F., additional, Klinger, S., additional, Thorens, B., additional, Naamane, N., additional, Eizirik, D. L., additional, Marselli, L., additional, Bugliani, M., additional, Marchetti, P., additional, Lucas, S., additional, Holm, C., additional, Jongeneel, C. V., additional, and Xenarios, I., additional

Published
2010
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41. Systems biology to battle vascular disease

Author

Dominiczak, A. F., primary, Herget-Rosenthal, S., additional, Delles, C., additional, Fliser, D., additional, Fournier, I., additional, Graber, A., additional, Girolami, M., additional, Holmes, E., additional, Lang, F., additional, Molina, F., additional, Nicholson, J., additional, Remuzzi, G., additional, Rossing, P., additional, Rudolph, K. L., additional, Wolkenhauer, O., additional, Xenarios, I., additional, Zubarev, R., additional, Zubov, D., additional, Vlahou, A., additional, and Schanstra, J. P., additional

Published
2010
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50. Mining literature for protein-protein interactions.

Author

Marcotte, E M, Xenarios, I, and Eisenberg, D

Abstract

A central problem in bioinformatics is how to capture information from the vast current scientific literature in a form suitable for analysis by computer. We address the special case of information on protein-protein interactions, and show that the frequencies of words in Medline abstracts can be used to determine whether or not a given paper discusses protein-protein interactions. For those papers determined to discuss this topic, the relevant information can be captured for the Database of Interacting PROTEINS: Furthermore, suitable gene annotations can also be captured.

Published
2001
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