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Computational approaches for systems metabolomics.

Current opinion in biotechnology

Krumsiek J, Bartel J, Theis FJ.
PMID: 27135552
Curr Opin Biotechnol. 2016 Jun;39:198-206. doi: 10.1016/j.copbio.2016.04.009. Epub 2016 Apr 30.

Systems genetics is defined as the simultaneous assessment and analysis of multi-omics datasets. In the past few years, metabolomics has been established as a robust tool describing an important functional layer in this approach. The metabolome of a biological...

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Krumsiek J, Bartel J, Theis FJ. Computational approaches for systems metabolomics. Curr Opin Biotechnol. 2016;39:198-206doi: 10.1016/j.copbio.2016.04.009.
Krumsiek, J., Bartel, J., & Theis, F. J. (2016). Computational approaches for systems metabolomics. Current opinion in biotechnology, 39198-206. https://doi.org/10.1016/j.copbio.2016.04.009
Krumsiek, Jan, et al. "Computational approaches for systems metabolomics." Current opinion in biotechnology vol. 39 (2016): 198-206. doi: https://doi.org/10.1016/j.copbio.2016.04.009
Krumsiek J, Bartel J, Theis FJ. Computational approaches for systems metabolomics. Curr Opin Biotechnol. 2016 Jun;39:198-206. doi: 10.1016/j.copbio.2016.04.009. Epub 2016 Apr 30. PMID: 27135552.
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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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Metabonomics and intensive care.

Critical care (London, England)

Antcliffe D, Gordon AC.
PMID: 26984158
Crit Care. 2016 Mar 16;20:68. doi: 10.1186/s13054-016-1222-8.

This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency medicine 2016. Other selected articles can be found online at http://www.biomedcentral.com/collections/annualupdate2016. Further information about the Annual Update in Intensive Care and Emergency...

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Antcliffe D, Gordon AC. Metabonomics and intensive care. Crit Care. 2016;20:68doi: 10.1186/s13054-016-1222-8.
Antcliffe, D., & Gordon, A. C. (2016). Metabonomics and intensive care. Critical care (London, England), 2068. https://doi.org/10.1186/s13054-016-1222-8
Antcliffe, David, and Gordon, Anthony C. "Metabonomics and intensive care." Critical care (London, England) vol. 20 (2016): 68. doi: https://doi.org/10.1186/s13054-016-1222-8
Antcliffe D, Gordon AC. Metabonomics and intensive care. Crit Care. 2016 Mar 16;20:68. doi: 10.1186/s13054-016-1222-8. PMID: 26984158; PMCID: PMC4794854.
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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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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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Ambient ionization MS for bioanalysis: recent developments and challenges.

Bioanalysis

Takyi-Williams J, Liu CF, Tang K.
PMID: 26295990
Bioanalysis. 2015;7(15):1901-23. doi: 10.4155/bio.15.116.

Ambient ionization MS has become very popular in analytical science and has now evolved as an effective analytical tool in metabolomics, biological tissue imaging, protein and small molecule drug analysis, where biological samples are probed in a rapid and...

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Takyi-Williams J, Liu CF, Tang K. Ambient ionization MS for bioanalysis: recent developments and challenges. Bioanalysis. 2015;7(15):1901-23doi: 10.4155/bio.15.116.
Takyi-Williams, J., Liu, C. F., & Tang, K. (2015). Ambient ionization MS for bioanalysis: recent developments and challenges. Bioanalysis, 7(15), 1901-23. https://doi.org/10.4155/bio.15.116
Takyi-Williams, John, et al. "Ambient ionization MS for bioanalysis: recent developments and challenges." Bioanalysis vol. 7,15 (2015): 1901-23. doi: https://doi.org/10.4155/bio.15.116
Takyi-Williams J, Liu CF, Tang K. Ambient ionization MS for bioanalysis: recent developments and challenges. Bioanalysis. 2015;7(15):1901-23. doi: 10.4155/bio.15.116. PMID: 26295990.
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Metabonomics: methods and protocols: preface.

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

Bjerrum JT.
PMID: 25821869
Methods Mol Biol. 2015;1277:v.

No abstract available.

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Bjerrum JT. Metabonomics: methods and protocols: preface. Methods Mol Biol. 2015;1277:v
Bjerrum, J. T. (2015). Metabonomics: methods and protocols: preface. Methods in molecular biology (Clifton, N.J.), 1277v.
Bjerrum, Jacob Tveiten. "Metabonomics: methods and protocols: preface." Methods in molecular biology (Clifton, N.J.) vol. 1277 (2015): v.
Bjerrum JT. Metabonomics: methods and protocols: preface. Methods Mol Biol. 2015;1277:v. PMID: 25821869.
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Comparative evaluation of eight software programs for alignment of gas chromatography-mass spectrometry chromatograms in metabolomics experiments.

Journal of chromatography. A

Niu W, Knight E, Xia Q, McGarvey BD.
PMID: 25435458
J Chromatogr A. 2014 Dec 29;1374:199-206. doi: 10.1016/j.chroma.2014.11.005. Epub 2014 Nov 20.

Since retention times of compounds in GC-MS chromatograms always vary slightly from chromatogram to chromatogram, it is necessary to align chromatograms before comparing them in metabolomics experiments. Several software programs have been developed to automate this process. Here we...

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Niu W, Knight E, Xia Q, et al. Comparative evaluation of eight software programs for alignment of gas chromatography-mass spectrometry chromatograms in metabolomics experiments. J Chromatogr A. 2014;1374:199-206doi: 10.1016/j.chroma.2014.11.005.
Niu, W., Knight, E., Xia, Q., & McGarvey, B. D. (2014). Comparative evaluation of eight software programs for alignment of gas chromatography-mass spectrometry chromatograms in metabolomics experiments. Journal of chromatography. A, 1374199-206. https://doi.org/10.1016/j.chroma.2014.11.005
Niu, Weihuan, et al. "Comparative evaluation of eight software programs for alignment of gas chromatography-mass spectrometry chromatograms in metabolomics experiments." Journal of chromatography. A vol. 1374 (2014): 199-206. doi: https://doi.org/10.1016/j.chroma.2014.11.005
Niu W, Knight E, Xia Q, McGarvey BD. Comparative evaluation of eight software programs for alignment of gas chromatography-mass spectrometry chromatograms in metabolomics experiments. J Chromatogr A. 2014 Dec 29;1374:199-206. doi: 10.1016/j.chroma.2014.11.005. Epub 2014 Nov 20. PMID: 25435458.
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Enhancing metabolomic data analysis with Progressive Consensus Alignment of NMR Spectra (PCANS).

BMC bioinformatics

Staab JM, O'Connell TM, Gomez SM.
PMID: 20214818
BMC Bioinformatics. 2010 Mar 09;11:123. doi: 10.1186/1471-2105-11-123.

BACKGROUND: Nuclear magnetic resonance spectroscopy is one of the primary tools in metabolomics analyses, where it is used to track and quantify changes in metabolite concentrations or profiles in response to perturbation through disease, toxicants or drugs. The spectra...

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Staab JM, O'Connell TM, Gomez SM. Enhancing metabolomic data analysis with Progressive Consensus Alignment of NMR Spectra (PCANS). BMC Bioinformatics. 2010;11:123doi: 10.1186/1471-2105-11-123.
Staab, J. M., O'Connell, T. M., & Gomez, S. M. (2010). Enhancing metabolomic data analysis with Progressive Consensus Alignment of NMR Spectra (PCANS). BMC bioinformatics, 11123. https://doi.org/10.1186/1471-2105-11-123
Staab, Jennifer M, et al. "Enhancing metabolomic data analysis with Progressive Consensus Alignment of NMR Spectra (PCANS)." BMC bioinformatics vol. 11 (2010): 123. doi: https://doi.org/10.1186/1471-2105-11-123
Staab JM, O'Connell TM, Gomez SM. Enhancing metabolomic data analysis with Progressive Consensus Alignment of NMR Spectra (PCANS). BMC Bioinformatics. 2010 Mar 09;11:123. doi: 10.1186/1471-2105-11-123. PMID: 20214818; PMCID: PMC2851603.
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Computational mass spectrometry for metabolomics: identification of metabolites and small molecules.

Analytical and bioanalytical chemistry

Neumann S, Böcker S.
PMID: 20936272
Anal Bioanal Chem. 2010 Dec;398(7):2779-88. doi: 10.1007/s00216-010-4142-5. Epub 2010 Oct 09.

The identification of compounds from mass spectrometry (MS) data is still seen as a major bottleneck in the interpretation of MS data. This is particularly the case for the identification of small compounds such as metabolites, where until recently...

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Neumann S, Böcker S. Computational mass spectrometry for metabolomics: identification of metabolites and small molecules. Anal Bioanal Chem. 2010;398(7):2779-88doi: 10.1007/s00216-010-4142-5.
Neumann, S., & Böcker, S. (2010). Computational mass spectrometry for metabolomics: identification of metabolites and small molecules. Analytical and bioanalytical chemistry, 398(7), 2779-88. https://doi.org/10.1007/s00216-010-4142-5
Neumann, Steffen, and Böcker, Sebastian. "Computational mass spectrometry for metabolomics: identification of metabolites and small molecules." Analytical and bioanalytical chemistry vol. 398,7 (2010): 2779-88. doi: https://doi.org/10.1007/s00216-010-4142-5
Neumann S, Böcker S. Computational mass spectrometry for metabolomics: identification of metabolites and small molecules. Anal Bioanal Chem. 2010 Dec;398(7):2779-88. doi: 10.1007/s00216-010-4142-5. Epub 2010 Oct 09. PMID: 20936272.
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[Advance of data collection and analysis in metabonomics research].

Zhongguo Zhong xi yi jie he za zhi Zhongguo Zhongxiyi jiehe zazhi = Chinese journal of integrated traditional and Western medicine

Zhang C, Mao JY, Hou YZ.
PMID: 20073231
Zhongguo Zhong Xi Yi Jie He Za Zhi. 2009 Oct;29(10):949-52.

No abstract available.

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Zhang C, Mao JY, Hou YZ. [Advance of data collection and analysis in metabonomics research]. Zhongguo Zhong Xi Yi Jie He Za Zhi. 2009;29(10):949-52
Zhang, C., Mao, J. Y., & Hou, Y. Z. (2009). [Advance of data collection and analysis in metabonomics research]. Zhongguo Zhong xi yi jie he za zhi Zhongguo Zhongxiyi jiehe zazhi = Chinese journal of integrated traditional and Western medicine, 29(10), 949-52.
Zhang, Chuan, et al. "[Advance of data collection and analysis in metabonomics research]." Zhongguo Zhong xi yi jie he za zhi Zhongguo Zhongxiyi jiehe zazhi = Chinese journal of integrated traditional and Western medicine vol. 29,10 (2009): 949-52.
Zhang C, Mao JY, Hou YZ. [Advance of data collection and analysis in metabonomics research]. Zhongguo Zhong Xi Yi Jie He Za Zhi. 2009 Oct;29(10):949-52. Chinese. PMID: 20073231.
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Application of NMR spectroscopy in metabolomics.

Journal of biomolecular NMR

Sykes BD.
PMID: 21340669
J Biomol NMR. 2011 Apr;49(3):163-4. doi: 10.1007/s10858-011-9479-3.

No abstract available.

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Sykes BD. Application of NMR spectroscopy in metabolomics. J Biomol NMR. 2011;49(3):163-4doi: 10.1007/s10858-011-9479-3.
Sykes, B. D. (2011). Application of NMR spectroscopy in metabolomics. Journal of biomolecular NMR, 49(3), 163-4. https://doi.org/10.1007/s10858-011-9479-3
Sykes, Brian D. "Application of NMR spectroscopy in metabolomics." Journal of biomolecular NMR vol. 49,3 (2011): 163-4. doi: https://doi.org/10.1007/s10858-011-9479-3
Sykes BD. Application of NMR spectroscopy in metabolomics. J Biomol NMR. 2011 Apr;49(3):163-4. doi: 10.1007/s10858-011-9479-3. PMID: 21340669.
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Showing 1 to 12 of 163 entries