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Relevant bibliographies by topics / Proteomics and metabolomics / Books

Books on the topic 'Proteomics and metabolomics'

To see the other types of publications on this topic, follow the link: Proteomics and metabolomics.

Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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1

Arjmand, Babak, ed. Genomics, Proteomics, and Metabolomics. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-27727-7.

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2

Martins-de-Souza, Daniel. Proteomics and metabolomics in psychiatry. Basel: Karger, 2014.

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3

Winkler, Robert, ed. Processing Metabolomics and Proteomics Data with Open Software. Cambridge: Royal Society of Chemistry, 2020. http://dx.doi.org/10.1039/9781788019880.

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4

Bagchi, Debasis. Genomics, proteomics, and metabolomics in nutraceuticals and functional foods. Ames, Iowa: Wiley-Blackwell, 2010.

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5

Bagchi, Debasis, Anand Swaroop, and Manashi Bagchi. Genomics, proteomics and metabolomics in nutraceuticals and functional foods. Chichester, West Sussex: John Wiley & Sons, Inc., 2015.

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6

Debasis, Bagchi, Lau Francis, and Bagchi Manashi, eds. Genomics, proteomics, and metabolomics in nutraceuticals and functional foods. Ames, Iowa: Wiley-Blackwell, 2010.

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7

Bagchi, Debasis, Francis C. Lau, and Manashi Bagchi, eds. Genomics, Proteomics, and Metabolomics in Nutraceuticals and Functional Foods. Oxford, UK: Wiley-Blackwell, 2010. http://dx.doi.org/10.1002/9780813821474.

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8

Bagchi, Debasis, Anand Swaroop, and Manashi Bagchi, eds. Genomics, Proteomics and Metabolomics in Nutraceuticals and Functional Foods. Chichester, UK: John Wiley & Sons, Ltd, 2015. http://dx.doi.org/10.1002/9781118930458.

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9

Datta, Susmita, and Bart J. A. Mertens, eds. Statistical Analysis of Proteomics, Metabolomics, and Lipidomics Data Using Mass Spectrometry. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-45809-0.

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10

Sensen, C. W. Handbook of genome research: Genomics, proteomics, metabolomics, bioinformatics, ethical, and legal issues. Weinheim: Wiley-VCH, 2005.

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11

Design of human nutrigenomics studies. Wageningen, the Netherlands: Wageningen Academic Publishers, 2009.

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12

Bhargava, Atul. Biotechnology: New ideas, new developments. Hauppauge, N.Y: Nova Science Publishers, 2011.

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13

Molecular analysis and genome discovery. 2nd ed. Chichester, West Sussex: John Wiley & Sons, 2011.

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14

Agrawal, Ganesh K. Seed Development: OMICS Technologies toward Improvement of Seed Quality and Crop Yield: OMICS in Seed Biology. Dordrecht: Springer Netherlands, 2012.

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15

Martins-de-Souza, D., ed. Proteomics and Metabolomics in Psychiatry. S. Karger AG, 2014. http://dx.doi.org/10.1159/isbn.978-3-318-02600-9.

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16

Husen, Azamal, and Altaf Ahmad. Genomics, Transcriptomics, Proteomics and Metabolomics of Crop Plants. Elsevier Science & Technology Books, 2023.

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17

Ramautar, Rawi, and David D. Y. Chen, eds. Capillary Electrophoresis‐Mass Spectrometry for Proteomics and Metabolomics. Wiley, 2022. http://dx.doi.org/10.1002/9783527833092.

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18

J, Griffiths William, ed. Metabolomics, metabonomics and metabolite profiling. Cambridge: RSC Publishing, 2008.

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19

Bagchi, Debasis, Manashi Bagchi, and Francis Lau. Genomics, Proteomics and Metabolomics in Nutraceuticals and Functional Foods. Wiley & Sons, Incorporated, John, 2010.

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20

Bagchi, Debasis, Anand Swaroop, and Manashi Bagchi. Genomics, Proteomics and Metabolomics in Nutraceuticals and Functional Foods. Wiley & Sons, Incorporated, John, 2015.

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21

Bagchi, Debasis, Anand Swaroop, and Manashi Bagchi. Genomics, Proteomics and Metabolomics in Nutraceuticals and Functional Foods. Wiley & Sons, Incorporated, John, 2015.

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22

Bagchi, Debasis, Anand Swaroop, and Manashi Bagchi. Genomics, Proteomics and Metabolomics in Nutraceuticals and Functional Foods. Wiley & Sons, Limited, John, 2015.

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23

Arjmand, Babak. Genomics, Proteomics, and Metabolomics: Stem Cells Monitoring in Regenerative Medicine. Springer, 2019.

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24

Arjmand, Babak. Genomics, Proteomics, and Metabolomics: Stem Cells Monitoring in Regenerative Medicine. Springer International Publishing AG, 2020.

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25

Winkler, Robert. Processing Metabolomics and Proteomics Data with Open Software: A Practical Guide. Royal Society of Chemistry, The, 2020.

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26

Chen, David D. Y., and Rawi Ramautar. Capillary Electrophoresis Mass Spectrometry for Proteomics and Metabolomics: Principles and Applications. Wiley & Sons, Incorporated, John, 2022.

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27

Datta, Susmita, and Bart J. a. Mertens. Statistical Analysis of Proteomics, Metabolomics, and Lipidomics Data Using Mass Spectrometry. Springer, 2016.

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28

Chen, David, and Rawi Ramautar. Capillary Electrophoresis Mass Spectrometry for Proteomics and Metabolomics: Principles and Applications. Wiley & Sons, Limited, John, 2022.

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29

Winkler, Robert. Processing Metabolomics and Proteomics Data with Open Software: A Practical Guide. Royal Society of Chemistry, The, 2020.

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30

Chen, David D. Y., and Rawi Ramautar. Capillary Electrophoresis Mass Spectrometry for Proteomics and Metabolomics: Principles and Applications. Wiley & Sons, Incorporated, John, 2022.

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31

Handbook of Genome Research: Genomics, Proteomics, Metabolomics, Bioinformatics, Ethical & Legal Issues. Wiley, 2005.

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32

Datta, Susmita, and Bart J. a. Mertens. Statistical Analysis of Proteomics, Metabolomics, and Lipidomics Data Using Mass Spectrometry. Springer International Publishing AG, 2016.

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33

Datta, Susmita, and Bart J. A. Mertens. Statistical Analysis of Proteomics, Metabolomics, and Lipidomics Data Using Mass Spectrometry. Springer, 2018.

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34

Chen, David D. Y., and Rawi Ramautar. Capillary Electrophoresis Mass Spectrometry for Proteomics and Metabolomics: Principles and Applications. Wiley & Sons, Incorporated, John, 2022.

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35

Processing Metabolomics and Proteomics Data with Open Software: A Practical Guide. Royal Society of Chemistry, The, 2020.

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36

Griffiths, W. Metabolomics, Metabonomics and Metabolite Profiling (RSC Biomolecular Sciences) (RSC Biomolecular Sciences). Royal Society of Chemistry, 2007.

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37

Macha, Muzafar A., Tariq A. masoodi, and Ajaz A. bhat. Multi-Omics Technology in Human Health and Diseases: Genomics, Epigenomics, Transcriptomics, Proteomics, Metabolomics, Radiomics, Multi-Omic. Elsevier Science & Technology Books, 2024.

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38

Munro, Carol A., and Duncan Wilson. Fungal genomics and transcriptomics. Edited by Christopher C. Kibbler, Richard Barton, Neil A. R. Gow, Susan Howell, Donna M. MacCallum, and Rohini J. Manuel. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780198755388.003.0006.

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Abstract:

The advent of whole-genome sequencing has resulted in a range of platforms for large-scale analysis of the DNA (genomics), RNA (transcriptomics), protein (proteomics), and metabolite (metabolomics) content of cells. These inclusive ‘omics’ approaches have allowed for unparalleled insights into fungal biology. In this chapter we will discuss how genomics and transcriptomics have been used to broaden our understanding of the biology of human pathogenic fungi and their interactions with their hosts.

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39

Vermeulen, Roel, Douglas A. Bell, Dean P. Jones, Montserrat Garcia-Closas, Avrum Spira, Teresa W. Wang, Martyn T. Smith, Qing Lan, and Nathaniel Rothman. Application of Biomarkers in Cancer Epidemiology. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190238667.003.0006.

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Abstract:

Advancements in OMICs are now enabling investigators to explore comprehensively the biological consequences of exogenous and endogenous exposures by detecting molecular signatures of exposure, early signs of adverse biological effects, preclinical disease, and molecularly defined cancer subtypes. These new technologies have proven invaluable for assembling a comprehensive portrait of human exposure, health, and disease. This includes hypothesis-driven biomarkers, as well as platforms that can agnostically analyze entire biologic processes and “compartments,” including the measurement of small molecules (metabolomics), DNA polymorphisms and rarer inherited variants (genomics), methylation and microRNA (epigenomics), chromosome-wide alterations, mRNA (transcriptomics), proteins (proteomics), and the microbiome (microbiomics). Although the implementation of these technologies in epidemiologic studies has already shown great promise, some challenges of particular importance must be addressed. Non-genetic OMIC markers vary over time due to both random variation and physiologic changes. Therefore, there is an urgent need for cohorts to collect repeat biological samples over time.

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40

zbiorowa, praca. Proteomika i metabolomika. Wydawnictwa Uniwersytetu Warszawskiego, 2010.

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41

Kraj, Agnieszka, Anna Drabik, and Jerzy Silberring, eds. Proteomika i metabolomika. Warsaw University Press, 2010. http://dx.doi.org/10.31338/uw.9788323533399.

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42

Rakwal, Randeep, and Ganesh K. Agrawal. Seed Development : OMICS Technologies toward Improvement of Seed Quality and Crop Yield: OMICS in Seed Biology. Springer, 2015.

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43

Rakwal, Randeep, and Ganesh K. Agrawal. Seed Development : OMICS Technologies toward Improvement of Seed Quality and Crop Yield: OMICS in Seed Biology. Springer, 2012.

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44

Suffredini, Anthony F., and J. Perren Cobb. Genetic and molecular expression patterns in critical illness. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199600830.003.0031.

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Abstract:

Investigators who study RNA, proteins, or metabolites use analytic platforms that simultaneously measure changes in the relative abundance of thousands of molecules in a single biological sample. Over the last decade, the application of these high-throughput, genome-wide platforms to study critical illness and injury has generated huge quantities of data that require specialized computational skills for analysis. These investigations hold promise for improving our understanding of the host response, thereby transforming the practice of intensive care. This chapter summarizes recent technological and computational approaches used in genomics, proteomics, and metabolomics. While major advances have been made with these approaches when applied to chronic diseases, the acute nature of critical illness and injury has unique challenges. The rapidity of initiating events, the trajectory of inflammation that follows injury or infection and the interplay of host responses to a replicating infection, all have major effects on changes in gene and molecular expression. This complexity is further accentuated by measurement that may vary with the timing and type of tissue sampled after the critical event. In addition, the hunt for novel molecular markers holds promise for identifying patients at risk for severe illness and for enabling more individualized therapy.

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45

Issaq, Haleem J. Proteomic and Metabolomic Approaches to Biomarker Discovery. Elsevier Science & Technology, 2013.

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46

Issaq, Haleem J., and Timothy D. Veenstra. Proteomic and Metabolomic Approaches to Biomarker Discovery. Elsevier Science & Technology, 2019.

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47

Proteomic and Metabolomic Approaches to Biomarker Discovery. Elsevier Science & Technology Books, 2013.

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48

Issaq, Haleem J., and Timothy D. Veenstra. Proteomic and Metabolomic Approaches to Biomarker Discovery. Elsevier Science & Technology Books, 2019.

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49

Proteomic and Metabolomic Approaches to Biomarker Discovery. Elsevier, 2013. http://dx.doi.org/10.1016/c2011-0-06994-6.

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50

Proteomic and Metabolomic Approaches to Biomarker Discovery. Elsevier, 2020. http://dx.doi.org/10.1016/c2018-0-03967-5.

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