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Firmiana: towards a one-stop proteomic cloud platform for data processing and analysis.

Nature biotechnology

Feng J, Ding C, Qiu N, Ni X, Zhan D, Liu W, Xia X, Li P, Lu B, Zhao Q, Nie P, Song L, Zhou Q, Lai M, Guo G, Zhu W, Ren J, Shi T, Qin J.
PMID: 28486446
Nat Biotechnol. 2017 May 09;35(5):409-412. doi: 10.1038/nbt.3825.

No abstract available.

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Feng J, Ding C, Qiu N, et al. Firmiana: towards a one-stop proteomic cloud platform for data processing and analysis. Nat Biotechnol. 2017;35(5):409-412doi: 10.1038/nbt.3825.
Feng, J., Ding, C., Qiu, N., Ni, X., Zhan, D., Liu, W., Xia, X., Li, P., Lu, B., Zhao, Q., Nie, P., Song, L., Zhou, Q., Lai, M., Guo, G., Zhu, W., Ren, J., Shi, T., & Qin, J. (2017). Firmiana: towards a one-stop proteomic cloud platform for data processing and analysis. Nature biotechnology, 35(5), 409-412. https://doi.org/10.1038/nbt.3825
Feng, Jinwen, et al. "Firmiana: towards a one-stop proteomic cloud platform for data processing and analysis." Nature biotechnology vol. 35,5 (2017): 409-412. doi: https://doi.org/10.1038/nbt.3825
Feng J, Ding C, Qiu N, Ni X, Zhan D, Liu W, Xia X, Li P, Lu B, Zhao Q, Nie P, Song L, Zhou Q, Lai M, Guo G, Zhu W, Ren J, Shi T, Qin J. Firmiana: towards a one-stop proteomic cloud platform for data processing and analysis. Nat Biotechnol. 2017 May 09;35(5):409-412. doi: 10.1038/nbt.3825. PMID: 28486446.
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Using SEQUEST with theoretically complete sequence databases.

Journal of the American Society for Mass Spectrometry

Sadygov RG.
PMID: 26238326
J Am Soc Mass Spectrom. 2015 Nov;26(11):1858-64. doi: 10.1007/s13361-015-1228-5. Epub 2015 Aug 04.

SEQUEST has long been used to identify peptides/proteins from their tandem mass spectra and protein sequence databases. The algorithm has proven to be hugely successful for its sensitivity and specificity in identifying peptides/proteins, the sequences of which are present...

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Sadygov RG. Using SEQUEST with theoretically complete sequence databases. J Am Soc Mass Spectrom. 2015;26(11):1858-64doi: 10.1007/s13361-015-1228-5.
Sadygov, R. G. (2015). Using SEQUEST with theoretically complete sequence databases. Journal of the American Society for Mass Spectrometry, 26(11), 1858-64. https://doi.org/10.1007/s13361-015-1228-5
Sadygov, Rovshan G. "Using SEQUEST with theoretically complete sequence databases." Journal of the American Society for Mass Spectrometry vol. 26,11 (2015): 1858-64. doi: https://doi.org/10.1007/s13361-015-1228-5
Sadygov RG. Using SEQUEST with theoretically complete sequence databases. J Am Soc Mass Spectrom. 2015 Nov;26(11):1858-64. doi: 10.1007/s13361-015-1228-5. Epub 2015 Aug 04. PMID: 26238326; PMCID: PMC4607654.
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Integrative omics for health and disease.

Nature reviews. Genetics

Karczewski KJ, Snyder MP.
PMID: 29479082
Nat Rev Genet. 2018 May;19(5):299-310. doi: 10.1038/nrg.2018.4. Epub 2018 Feb 26.

Advances in omics technologies - such as genomics, transcriptomics, proteomics and metabolomics - have begun to enable personalized medicine at an extraordinarily detailed molecular level. Individually, these technologies have contributed medical advances that have begun to enter clinical practice....

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Karczewski KJ, Snyder MP. Integrative omics for health and disease. Nat Rev Genet. 2018;19(5):299-310doi: 10.1038/nrg.2018.4.
Karczewski, K. J., & Snyder, M. P. (2018). Integrative omics for health and disease. Nature reviews. Genetics, 19(5), 299-310. https://doi.org/10.1038/nrg.2018.4
Karczewski, Konrad J, and Snyder, Michael P. "Integrative omics for health and disease." Nature reviews. Genetics vol. 19,5 (2018): 299-310. doi: https://doi.org/10.1038/nrg.2018.4
Karczewski KJ, Snyder MP. Integrative omics for health and disease. Nat Rev Genet. 2018 May;19(5):299-310. doi: 10.1038/nrg.2018.4. Epub 2018 Feb 26. PMID: 29479082; PMCID: PMC5990367.
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Diagnostic proteomics: will this impact the clinic?.

Proteomics. Clinical applications

Sauer S.
PMID: 24323456
Proteomics Clin Appl. 2013 Dec;7(11):725-6. doi: 10.1002/prca.201370063.

No abstract available.

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Sauer S. Diagnostic proteomics: will this impact the clinic?. Proteomics Clin Appl. 2013;7(11):725-6doi: 10.1002/prca.201370063.
Sauer, S. (2013). Diagnostic proteomics: will this impact the clinic?. Proteomics. Clinical applications, 7(11), 725-6. https://doi.org/10.1002/prca.201370063
Sauer, Sascha. "Diagnostic proteomics: will this impact the clinic?." Proteomics. Clinical applications vol. 7,11 (2013): 725-6. doi: https://doi.org/10.1002/prca.201370063
Sauer S. Diagnostic proteomics: will this impact the clinic?. Proteomics Clin Appl. 2013 Dec;7(11):725-6. doi: 10.1002/prca.201370063. PMID: 24323456.
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Paediatrics and proteomics: back to the beginning.

Proteomics. Clinical applications

Everett A, Ignjatovic V.
PMID: 25461013
Proteomics Clin Appl. 2014 Dec;8(11):805-6. doi: 10.1002/prca.201470064.

No abstract available.

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Everett A, Ignjatovic V. Paediatrics and proteomics: back to the beginning. Proteomics Clin Appl. 2014;8(11):805-6doi: 10.1002/prca.201470064.
Everett, A., & Ignjatovic, V. (2014). Paediatrics and proteomics: back to the beginning. Proteomics. Clinical applications, 8(11), 805-6. https://doi.org/10.1002/prca.201470064
Everett, Allen, and Ignjatovic, Vera. "Paediatrics and proteomics: back to the beginning." Proteomics. Clinical applications vol. 8,11 (2014): 805-6. doi: https://doi.org/10.1002/prca.201470064
Everett A, Ignjatovic V. Paediatrics and proteomics: back to the beginning. Proteomics Clin Appl. 2014 Dec;8(11):805-6. doi: 10.1002/prca.201470064. PMID: 25461013.
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Integrative analysis of human omics data using biomolecular networks.

Molecular bioSystems

Robinson JL, Nielsen J.
PMID: 27510223
Mol Biosyst. 2016 Oct 20;12(10):2953-64. doi: 10.1039/c6mb00476h. Epub 2016 Aug 11.

High-throughput '-omics' technologies have given rise to an increasing abundance of genome-scale data detailing human biology at the molecular level. Although these datasets have already made substantial contributions to a more comprehensive understanding of human physiology and diseases, their...

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Robinson JL, Nielsen J. Integrative analysis of human omics data using biomolecular networks. Mol Biosyst. 2016;12(10):2953-64doi: 10.1039/c6mb00476h.
Robinson, J. L., & Nielsen, J. (2016). Integrative analysis of human omics data using biomolecular networks. Molecular bioSystems, 12(10), 2953-64. https://doi.org/10.1039/c6mb00476h
Robinson, Jonathan L, and Nielsen, Jens. "Integrative analysis of human omics data using biomolecular networks." Molecular bioSystems vol. 12,10 (2016): 2953-64. doi: https://doi.org/10.1039/c6mb00476h
Robinson JL, Nielsen J. Integrative analysis of human omics data using biomolecular networks. Mol Biosyst. 2016 Oct 20;12(10):2953-64. doi: 10.1039/c6mb00476h. Epub 2016 Aug 11. PMID: 27510223.
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Pladipus Enables Universal Distributed Computing in Proteomics Bioinformatics.

Journal of proteome research

Verheggen K, Maddelein D, Hulstaert N, Martens L, Barsnes H, Vaudel M.
PMID: 26510693
J Proteome Res. 2016 Mar 04;15(3):707-12. doi: 10.1021/acs.jproteome.5b00850. Epub 2015 Nov 06.

The use of proteomics bioinformatics substantially contributes to an improved understanding of proteomes, but this novel and in-depth knowledge comes at the cost of increased computational complexity. Parallelization across multiple computers, a strategy termed distributed computing, can be used...

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Verheggen K, Maddelein D, Hulstaert N, et al. Pladipus Enables Universal Distributed Computing in Proteomics Bioinformatics. J Proteome Res. 2015;15(3):707-12doi: 10.1021/acs.jproteome.5b00850.
Verheggen, K., Maddelein, D., Hulstaert, N., Martens, L., Barsnes, H., & Vaudel, M. (2016). Pladipus Enables Universal Distributed Computing in Proteomics Bioinformatics. Journal of proteome research, 15(3), 707-12. https://doi.org/10.1021/acs.jproteome.5b00850
Verheggen, Kenneth, et al. "Pladipus Enables Universal Distributed Computing in Proteomics Bioinformatics." Journal of proteome research vol. 15,3 (2016): 707-12. doi: https://doi.org/10.1021/acs.jproteome.5b00850
Verheggen K, Maddelein D, Hulstaert N, Martens L, Barsnes H, Vaudel M. Pladipus Enables Universal Distributed Computing in Proteomics Bioinformatics. J Proteome Res. 2016 Mar 04;15(3):707-12. doi: 10.1021/acs.jproteome.5b00850. Epub 2015 Nov 06. PMID: 26510693.
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FunRich: An open access standalone functional enrichment and interaction network analysis tool.

Proteomics

Pathan M, Keerthikumar S, Ang CS, Gangoda L, Quek CY, Williamson NA, Mouradov D, Sieber OM, Simpson RJ, Salim A, Bacic A, Hill AF, Stroud DA, Ryan MT, Agbinya JI, Mariadason JM, Burgess AW, Mathivanan S.
PMID: 25921073
Proteomics. 2015 Aug;15(15):2597-601. doi: 10.1002/pmic.201400515. Epub 2015 Jun 17.

As high-throughput techniques including proteomics become more accessible to individual laboratories, there is an urgent need for a user-friendly bioinformatics analysis system. Here, we describe FunRich, an open access, standalone functional enrichment and network analysis tool. FunRich is designed...

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Pathan M, Keerthikumar S, Ang CS, et al. FunRich: An open access standalone functional enrichment and interaction network analysis tool. Proteomics. 2015;15(15):2597-601doi: 10.1002/pmic.201400515.
Pathan, M., Keerthikumar, S., Ang, C. S., Gangoda, L., Quek, C. Y., Williamson, N. A., Mouradov, D., Sieber, O. M., Simpson, R. J., Salim, A., Bacic, A., Hill, A. F., Stroud, D. A., Ryan, M. T., Agbinya, J. I., Mariadason, J. M., Burgess, A. W., & Mathivanan, S. (2015). FunRich: An open access standalone functional enrichment and interaction network analysis tool. Proteomics, 15(15), 2597-601. https://doi.org/10.1002/pmic.201400515
Pathan, Mohashin, et al. "FunRich: An open access standalone functional enrichment and interaction network analysis tool." Proteomics vol. 15,15 (2015): 2597-601. doi: https://doi.org/10.1002/pmic.201400515
Pathan M, Keerthikumar S, Ang CS, Gangoda L, Quek CY, Williamson NA, Mouradov D, Sieber OM, Simpson RJ, Salim A, Bacic A, Hill AF, Stroud DA, Ryan MT, Agbinya JI, Mariadason JM, Burgess AW, Mathivanan S. FunRich: An open access standalone functional enrichment and interaction network analysis tool. Proteomics. 2015 Aug;15(15):2597-601. doi: 10.1002/pmic.201400515. Epub 2015 Jun 17. PMID: 25921073.
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Advancing Clinical Proteomics via Analysis Based on Biological Complexes: A Tale of Five Paradigms.

Journal of proteome research

Goh WW, Wong L.
PMID: 27454466
J Proteome Res. 2016 Sep 02;15(9):3167-79. doi: 10.1021/acs.jproteome.6b00402. Epub 2016 Aug 10.

Despite advances in proteomic technologies, idiosyncratic data issues, for example, incomplete coverage and inconsistency, resulting in large data holes, persist. Moreover, because of naïve reliance on statistical testing and its accompanying p values, differential protein signatures identified from such...

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Goh WW, Wong L. Advancing Clinical Proteomics via Analysis Based on Biological Complexes: A Tale of Five Paradigms. J Proteome Res. 2016;15(9):3167-79doi: 10.1021/acs.jproteome.6b00402.
Goh, W. W., & Wong, L. (2016). Advancing Clinical Proteomics via Analysis Based on Biological Complexes: A Tale of Five Paradigms. Journal of proteome research, 15(9), 3167-79. https://doi.org/10.1021/acs.jproteome.6b00402
Goh, Wilson Wen Bin, and Wong, Limsoon. "Advancing Clinical Proteomics via Analysis Based on Biological Complexes: A Tale of Five Paradigms." Journal of proteome research vol. 15,9 (2016): 3167-79. doi: https://doi.org/10.1021/acs.jproteome.6b00402
Goh WW, Wong L. Advancing Clinical Proteomics via Analysis Based on Biological Complexes: A Tale of Five Paradigms. J Proteome Res. 2016 Sep 02;15(9):3167-79. doi: 10.1021/acs.jproteome.6b00402. Epub 2016 Aug 10. PMID: 27454466.
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Multi-mode acquisition (MMA): An MS/MS acquisition strategy for maximizing selectivity, specificity and sensitivity of DIA product ion spectra.

Proteomics

Williams BJ, Ciavarini SJ, Devlin C, Cohn SM, Xie R, Vissers JP, Martin LB, Caswell A, Langridge JI, Geromanos SJ.
PMID: 27296928
Proteomics. 2016 Aug;16(15):2284-301. doi: 10.1002/pmic.201500492.

In proteomics studies, it is generally accepted that depth of coverage and dynamic range is limited in data-directed acquisitions. The serial nature of the method limits both sensitivity and the number of precursor ions that can be sampled. To...

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Williams BJ, Ciavarini SJ, Devlin C, et al. Multi-mode acquisition (MMA): An MS/MS acquisition strategy for maximizing selectivity, specificity and sensitivity of DIA product ion spectra. Proteomics. 2016;16(15):2284-301doi: 10.1002/pmic.201500492.
Williams, B. J., Ciavarini, S. J., Devlin, C., Cohn, S. M., Xie, R., Vissers, J. P., Martin, L. B., Caswell, A., Langridge, J. I., & Geromanos, S. J. (2016). Multi-mode acquisition (MMA): An MS/MS acquisition strategy for maximizing selectivity, specificity and sensitivity of DIA product ion spectra. Proteomics, 16(15), 2284-301. https://doi.org/10.1002/pmic.201500492
Williams, Brad J, et al. "Multi-mode acquisition (MMA): An MS/MS acquisition strategy for maximizing selectivity, specificity and sensitivity of DIA product ion spectra." Proteomics vol. 16,15 (2016): 2284-301. doi: https://doi.org/10.1002/pmic.201500492
Williams BJ, Ciavarini SJ, Devlin C, Cohn SM, Xie R, Vissers JP, Martin LB, Caswell A, Langridge JI, Geromanos SJ. Multi-mode acquisition (MMA): An MS/MS acquisition strategy for maximizing selectivity, specificity and sensitivity of DIA product ion spectra. Proteomics. 2016 Aug;16(15):2284-301. doi: 10.1002/pmic.201500492. PMID: 27296928.
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Chemical proteomics from a nuclear magnetic resonance spectroscopy perspective.

Expert review of proteomics

Sem DS.
PMID: 15966811
Expert Rev Proteomics. 2004 Aug;1(2):165-78. doi: 10.1586/14789450.1.2.165.

Proteomics is the study of the protein complement of a genome and employs a number of newly emerging tools. One such tool is chemical proteomics, which is a branch of proteomics devoted to the exploration of protein function using...

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Sem DS. Chemical proteomics from a nuclear magnetic resonance spectroscopy perspective. Expert Rev Proteomics. 2004;1(2):165-78doi: 10.1586/14789450.1.2.165.
Sem, D. S. (2004). Chemical proteomics from a nuclear magnetic resonance spectroscopy perspective. Expert review of proteomics, 1(2), 165-78. https://doi.org/10.1586/14789450.1.2.165
Sem, Daniel S. "Chemical proteomics from a nuclear magnetic resonance spectroscopy perspective." Expert review of proteomics vol. 1,2 (2004): 165-78. doi: https://doi.org/10.1586/14789450.1.2.165
Sem DS. Chemical proteomics from a nuclear magnetic resonance spectroscopy perspective. Expert Rev Proteomics. 2004 Aug;1(2):165-78. doi: 10.1586/14789450.1.2.165. PMID: 15966811.
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PRIDE and "Database on Demand" as valuable tools for computational proteomics.

Methods in molecular biology (Clifton, N.J.)

Vizcaíno JA, Reisinger F, Côté R, Martens L.
PMID: 21063943
Methods Mol Biol. 2011;696:93-105. doi: 10.1007/978-1-60761-987-1_6.

The Proteomics Identifications Database (PRIDE, http://www.ebi.ac.uk/pride ) provides users with the ability to explore and compare mass spectrometry-based proteomics experiments that reveal details of the protein expression found in a broad range of taxonomic groups, tissues, and disease states....

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Vizcaíno JA, Reisinger F, Côté R, et al. PRIDE and "Database on Demand" as valuable tools for computational proteomics. Methods Mol Biol. 2011;696:93-105doi: 10.1007/978-1-60761-987-1_6.
Vizcaíno, J. A., Reisinger, F., Côté, R., & Martens, L. (2011). PRIDE and "Database on Demand" as valuable tools for computational proteomics. Methods in molecular biology (Clifton, N.J.), 69693-105. https://doi.org/10.1007/978-1-60761-987-1_6
Vizcaíno, Juan Antonio, et al. "PRIDE and "Database on Demand" as valuable tools for computational proteomics." Methods in molecular biology (Clifton, N.J.) vol. 696 (2011): 93-105. doi: https://doi.org/10.1007/978-1-60761-987-1_6
Vizcaíno JA, Reisinger F, Côté R, Martens L. PRIDE and "Database on Demand" as valuable tools for computational proteomics. Methods Mol Biol. 2011;696:93-105. doi: 10.1007/978-1-60761-987-1_6. PMID: 21063943.
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Showing 1 to 12 of 237 entries