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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.

Cite
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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PROTEOMICS Reviews 2016--Part 2.

Proteomics

Dunn MJ.
PMID: 26949073
Proteomics. 2016 Mar;16(5):699. doi: 10.1002/pmic.201670053.

No abstract available.

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Dunn MJ. PROTEOMICS Reviews 2016--Part 2. Proteomics. 2016;16(5):699doi: 10.1002/pmic.201670053.
Dunn, M. J. (2016). PROTEOMICS Reviews 2016--Part 2. Proteomics, 16(5), 699. https://doi.org/10.1002/pmic.201670053
Dunn, Michael J. "PROTEOMICS Reviews 2016--Part 2." Proteomics vol. 16,5 (2016): 699. doi: https://doi.org/10.1002/pmic.201670053
Dunn MJ. PROTEOMICS Reviews 2016--Part 2. Proteomics. 2016 Mar;16(5):699. doi: 10.1002/pmic.201670053. PMID: 26949073.
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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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Metaproteomic analysis of human gut microbiota: where are we heading?.

Journal of biomedical science

Lee PY, Chin SF, Neoh HM, Jamal R.
PMID: 28606141
J Biomed Sci. 2017 Jun 12;24(1):36. doi: 10.1186/s12929-017-0342-z.

The human gut is home to complex microbial populations that change dynamically in response to various internal and external stimuli. The gut microbiota provides numerous functional benefits that are crucial for human health but in the setting of a...

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Lee PY, Chin SF, Neoh HM, et al. Metaproteomic analysis of human gut microbiota: where are we heading?. J Biomed Sci. 2017;24(1):36doi: 10.1186/s12929-017-0342-z.
Lee, P. Y., Chin, S. F., Neoh, H. M., & Jamal, R. (2017). Metaproteomic analysis of human gut microbiota: where are we heading?. Journal of biomedical science, 24(1), 36. https://doi.org/10.1186/s12929-017-0342-z
Lee, Pey Yee, et al. "Metaproteomic analysis of human gut microbiota: where are we heading?." Journal of biomedical science vol. 24,1 (2017): 36. doi: https://doi.org/10.1186/s12929-017-0342-z
Lee PY, Chin SF, Neoh HM, Jamal R. Metaproteomic analysis of human gut microbiota: where are we heading?. J Biomed Sci. 2017 Jun 12;24(1):36. doi: 10.1186/s12929-017-0342-z. PMID: 28606141; PMCID: PMC5469034.
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Computational proteomics in the post-identification era.

Biochimica et biophysica acta

Eisenacher M, Stephan C.
PMID: 24315217
Biochim Biophys Acta. 2014 Jan;1844(1):1. doi: 10.1016/j.bbapap.2013.10.012.

No abstract available.

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Eisenacher M, Stephan C. Computational proteomics in the post-identification era. Biochim Biophys Acta. 2014;1844(1):1doi: 10.1016/j.bbapap.2013.10.012.
Eisenacher, M., & Stephan, C. (2014). Computational proteomics in the post-identification era. Biochimica et biophysica acta, 1844(1), 1. https://doi.org/10.1016/j.bbapap.2013.10.012
Eisenacher, Martin, and Stephan, Christian. "Computational proteomics in the post-identification era." Biochimica et biophysica acta vol. 1844,1 (2014): 1. doi: https://doi.org/10.1016/j.bbapap.2013.10.012
Eisenacher M, Stephan C. Computational proteomics in the post-identification era. Biochim Biophys Acta. 2014 Jan;1844(1):1. doi: 10.1016/j.bbapap.2013.10.012. PMID: 24315217.
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Stem cells as drug delivery methods: application of stem cell secretome for regeneration.

Advanced drug delivery reviews

Tran C, Damaser MS.
PMID: 25451858
Adv Drug Deliv Rev. 2015 Mar;82:1-11. doi: 10.1016/j.addr.2014.10.007. Epub 2014 Oct 15.

Mesenchymal stem cells (MSCs) are a unique cell population defined by their ability to indefinitely self-renew, differentiate into multiple cell lineages, and form clonal cell populations. It was originally thought that this ability for broad plasticity defined the therapeutic...

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Tran C, Damaser MS. Stem cells as drug delivery methods: application of stem cell secretome for regeneration. Adv Drug Deliv Rev. 2014;82:1-11doi: 10.1016/j.addr.2014.10.007.
Tran, C., & Damaser, M. S. (2015). Stem cells as drug delivery methods: application of stem cell secretome for regeneration. Advanced drug delivery reviews, 821-11. https://doi.org/10.1016/j.addr.2014.10.007
Tran, Christine, and Damaser, Margot S. "Stem cells as drug delivery methods: application of stem cell secretome for regeneration." Advanced drug delivery reviews vol. 82 (2015): 1-11. doi: https://doi.org/10.1016/j.addr.2014.10.007
Tran C, Damaser MS. Stem cells as drug delivery methods: application of stem cell secretome for regeneration. Adv Drug Deliv Rev. 2015 Mar;82:1-11. doi: 10.1016/j.addr.2014.10.007. Epub 2014 Oct 15. PMID: 25451858; PMCID: PMC4398586.
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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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Showing 1 to 12 of 628 entries