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Libros sobre el tema "Very high throughput sequencing"

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Publicado: 7 de julio de 2024

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1

Kwon, Young Min y Steven C. Ricke, eds. High-Throughput Next Generation Sequencing. Totowa, NJ: Humana Press, 2011. http://dx.doi.org/10.1007/978-1-61779-089-8.

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2

Rodríguez-Ezpeleta, Naiara, Michael Hackenberg y Ana M. Aransay, eds. Bioinformatics for High Throughput Sequencing. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-0782-9.

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3

Rodríguez-Ezpeleta, Naiara, Michael Hackenberg y Ana M. Aransay. Bioinformatics for high throughput sequencing. New York, NY: Springer, 2012.

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4

High-throughput next generation sequencing: Methods and applications. New York: Springer, 2011.

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5

Aransay, Ana M. y José Luis Lavín Trueba, eds. Field Guidelines for Genetic Experimental Designs in High-Throughput Sequencing. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-31350-4.

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6

Mäkinen, Veli. Genome-scale algorithm design: Biological sequence analysis in the era of high-throughput sequencing. Cambridge, United Kingdom: University Printing House, 2015.

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7

Cunha, Monica V. y João Inácio. Veterinary infection biology: Molecular diagnostics and high-throughput strategies. New York: Humana Press, 2015.

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8

Rodríguez-Ezpeleta, Naiara, Ana M. Aransay y Michael Hackenberg. Bioinformatics for High Throughput Sequencing. Springer, 2014.

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9

Rodríguez-Ezpeleta, Naiara, Ana M. Aransay y Michael Hackenberg. Bioinformatics for High Throughput Sequencing. Springer, 2011.

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10

Lee, Eric y T. W. Tan. Beginners Guide to Bioinformatics for High Throughput Sequencing. WORLD SCIENTIFIC, 2018. http://dx.doi.org/10.1142/10720.

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11

Ball, Madeleine Price. Sequencing-based high-throughput profiling of DNA methylation. 2010.

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12

Tan, Hugh T. W. y Eric Lee. Beginners Guide to Bioinformatics for High Throughput Sequencing. World Scientific Publishing Co Pte Ltd, 2018.

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13

Kwon, Young Min y Steven C. Ricke. High-Throughput Next Generation Sequencing: Methods and Applications. Humana Press, 2016.

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14

New High Throughput Technologies for DNA Sequencing and Genomics. Elsevier, 2007. http://dx.doi.org/10.1016/s1871-0069(06)x0200-8.

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15

R, Mitchelson Keith, ed. New high throughput technologies for DNA sequencing and genomics. Amsterdam: Elsevier, 2007.

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16

Joly, Dominique y Denis Faure. Insight on Environmental Genomics: The High-Throughput Sequencing Revolution. Elsevier, 2016.

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17

Mitchelson, Keith R. New High Throughput Technologies for DNA Sequencing and Genomics. Elsevier Science & Technology Books, 2011.

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18

Joly, Dominique y Denis Faure. Insight on Environmental Genomics: The High-Throughput Sequencing Revolution. Elsevier, 2016.

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19

Aransay, Ana M. y José Luis Lavín Trueba. Field Guidelines for Genetic Experimental Designs in High-Throughput Sequencing. Springer, 2016.

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20

Aransay, Ana M. y José Luis Lavín Trueba. Field Guidelines for Genetic Experimental Designs in High-Throughput Sequencing. Springer, 2018.

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21

Aransay, Ana M. y José Luis Lavín Trueba. Field Guidelines for Genetic Experimental Designs in High-Throughput Sequencing. Springer London, Limited, 2016.

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22

Li, Hua, Wen-Lian Chen, Yuriy L. Orlov y Guoshuai Cai, eds. High-throughput Sequencing-based Investigation of Chronic Disease Markers and Mechanisms. Frontiers Media SA, 2022. http://dx.doi.org/10.3389/978-2-88976-559-1.

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23

In Loeffler’s Footsteps – Viral Genomics in the Era of High-Throughput Sequencing. Elsevier, 2017. http://dx.doi.org/10.1016/s0065-3527(17)x0003-1.

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24

Beer, Martin y Dirk Höper. In Loeffler's Footsteps: Viral Genomics in the Era of High-Throughput Sequencing. Elsevier Science & Technology Books, 2017.

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25

Beer, Martin y Dirk Höper. In Loeffler's Footsteps - Viral Genomics in the Era of High-Throughput Sequencing. Elsevier Science & Technology Books, 2017.

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26

Next-generation sequencing : current technologies and applications. Caister Academic Press, 2014.

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27

Tomescu, Alexandru I., Veli Mäkinen, Djamal Belazzougui y Fabio Cunial. Genome-Scale Algorithm Design: Biological Sequence Analysis in the Era of High-Throughput Sequencing. Cambridge University Press, 2015.

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28

Tomescu, Alexandru I., Veli Mäkinen, Djamal Belazzougui y Fabio Cunial. Genome-Scale Algorithm Design: Biological Sequence Analysis in the Era of High-Throughput Sequencing. Cambridge University Press, 2015.

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29

DeKosky, Brandon. Decoding the Antibody Repertoire: High Throughput Sequencing of Multiple Transcripts from Single B Cells. Springer, 2018.

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30

DeKosky, Brandon. Decoding the Antibody Repertoire: High Throughput Sequencing of Multiple Transcripts from Single B Cells. Springer International Publishing AG, 2017.

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31

Shomron, Noam. Deep Sequencing Data Analysis. Springer, 2022.

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32

Shomron, Noam. Deep Sequencing Data Analysis. Humana Press, 2016.

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33

Shomron, Noam. Deep Sequencing Data Analysis. Springer, 2020.

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34

Deep Sequencing Data Analysis. Humana Press Inc., 2013.

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35

Chandran, Anandhakumar. Advancing Development of Synthetic Gene Regulators: With the Power of High-Throughput Sequencing in Chemical Biology. Springer, 2017.

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36

Chandran, Anandhakumar. Advancing Development of Synthetic Gene Regulators: With the Power of High-Throughput Sequencing in Chemical Biology. Springer, 2017.

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37

Chandran, Anandhakumar. Advancing Development of Synthetic Gene Regulators: With the Power of High-Throughput Sequencing in Chemical Biology. Springer, 2019.

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38

Mitchelson, Keith. New High Throughput Technologies for DNA Sequencing and Genomics, Volume 2 (Perspectives in Bioanalysis) (Perspectives in Bioanalysis). Elsevier Science, 2007.

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39

Applications Of Next Generation Sequencing In Cancer Research Vol 1 Decoding The Cancer Genome. Springer-Verlag New York Inc., 2013.

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40

Mifsud, Borbala y Anais Bardet. Practical Guide to Chip-Seq Data Analysis. Taylor & Francis Group, 2018.

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41

Mifsud, Borbala, Kathi Zarnack y Anaïs F. Bardet. Practical Guide to ChIP-Seq Data Analysis. Taylor & Francis Group, 2018.

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42

Mifsud, Borbala, Kathi Zarnack y Anais Bardet. Practical Guide to Chip-Seq Data Analysis. Taylor & Francis Group, 2021.

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43

Mifsud, Borbala, Kathi Zarnack y Anaïs F. Bardet. Practical Guide to ChIP-Seq Data Analysis. Taylor & Francis Group, 2018.

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44

Mifsud, Borbala, Kathi Zarnack y Anaïs F. Bardet. Practical Guide to ChIP-Seq Data Analysis. Taylor & Francis Group, 2018.

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45

Lamari, Foudil y Jean-Marie Saudubray. Disorders of Complex Lipids Synthesis and Remodeling. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199972135.003.0066.

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Defective lipid catabolic pathways are involved in numerous inherited metabolic diseases such as lysosomal storage diseases and peroxisome biogenesis disorders. We recently described a new classification of a rapidly growing group of inherited metabolic disorders involving biosynthesis and remodeling of complex lipids including phospholipids and sphingolipids. The remarkable progress achieved over the last decade in high throughput gene sequencing and in lipid analysis technologies have enabled the description of more than 40 diseases linked to defects in enzymes involved in these pathways. Some of these defects present in infancy or childhood but most of them are diagnosed in adolescence or adulthood. In this review we focus on those with adult presentation.
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46

Ayala, Francisco J. y Camilo J. Cela-Conde. Neanderthals and modern humans. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198739906.003.0011.

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This chapter deals with the similarities and differences between Homo neanderthalensis and Homo sapiens, by considering genetic, brain, and cognitive evidence. The genetic differentiation emerges from fossil genetic evidence obtained first from mtDNA and later from nuclear DNA. With high throughput whole genome sequencing, sequences have been obtained from the Denisova Cave (Siberia) fossils. Nuclear DNA of a third species (“Denisovans”) has been obtained from the same cave and used to define the phylogenetic relationships among the three species during the Upper Palaeolithic. Archaeological comparisons make it possible to advance a four-mode model of the evolution of symbolism. Neanderthals and modern humans would share a “modern mind” as defined up to Symbolic Mode 3. Whether the Neanderthals reached symbolic Mode 4 remains unsettled.
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47

Haiman, Christopher y David J. Hunter. Genetic Epidemiology of Cancer. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190676827.003.0004.

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This chapter explores the genetic epidemiology of cancer: the identification and quantification of inherited genetic factors, and their potential interaction with the environment, in the etiology of cancer in human populations. It also describes the techniques used to identify genetic variants that contribute to cancer susceptibility. It describes the older research methods for identifying the chromosomal localization of high-risk predisposing genes, such as linkage analysis within pedigrees and allele-sharing methods, as it is important to understand the foundations of the field. It also reviews the epidemiologic study designs that can be helpful in identifying low-risk alleles in candidate gene and genome-wide association studies, as well as gene–environment interactions. Finally, it describes some of the genotyping and sequencing platforms commonly employed for high-throughput genome analysis, and the concept of Mendelian randomization and how it may be useful in the study of biomarkers and environmental causes of cancer.
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48

Taberlet, Pierre, Aurélie Bonin, Lucie Zinger y Eric Coissac. Environmental DNA. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198767220.001.0001.

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Environmental DNA (eDNA), i.e. DNA released in the environment by any living form, represents a formidable opportunity to gather high-throughput and standard information on the distribution or feeding habits of species. It has therefore great potential for applications in ecology and biodiversity management. However, this research field is fast-moving, involves different areas of expertise and currently lacks standard approaches, which calls for an up-to-date and comprehensive synthesis. Environmental DNA for biodiversity research and monitoring covers current methods based on eDNA, with a particular focus on “eDNA metabarcoding”. Intended for scientists and managers, it provides the background information to allow the design of sound experiments. It revisits all steps necessary to produce high-quality metabarcoding data such as sampling, metabarcode design, optimization of PCR and sequencing protocols, as well as analysis of large sequencing datasets. All these different steps are presented by discussing the potential and current challenges of eDNA-based approaches to infer parameters on biodiversity or ecological processes. The last chapters of this book review how DNA metabarcoding has been used so far to unravel novel patterns of diversity in space and time, to detect particular species, and to answer new ecological questions in various ecosystems and for various organisms. Environmental DNA for biodiversity research and monitoring constitutes an essential reading for all graduate students, researchers and practitioners who do not have a strong background in molecular genetics and who are willing to use eDNA approaches in ecology and biomonitoring.
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49

Rowley, Andrew F., Christopher J. Coates y Miranda W. Whitten, eds. Invertebrate Pathology. Oxford University Press, 2022. http://dx.doi.org/10.1093/oso/9780198853756.001.0001.

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Many invertebrates are serious pests of agriculture (e.g., mites and locusts), vectors of disease (e.g., mosquitoes and aquatic snails) and venomous (e.g., scorpions), whilst others are beneficial to humans as pollinators, food sources, and detritivores. Despite their obvious ecological, medical, and economic importance, this is the first comprehensive review of invertebrate diseases to be available within a single volume. Concurrent molecular and bioinformatics developments over the last decade have catalyzed a renaissance in invertebrate pathology. High-throughput sequencing, handheld diagnostic kits and the move to new technologies have rapidly increased our understanding of invertebrate diseases, generating a large volume of fundamental and applied research on the topic. An overview is now timely, and this authoritative reference assembles an international team of the leading specialists in the field to review the main diseases and pathologic manifestations of all the major invertebrate groups. Each chapter adopts a common plan in terms of its scope and approach to achieve a succinct and coherent synthesis.
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50

Pezzella, Francesco, Mahvash Tavassoli y David J. Kerr, eds. Oxford Textbook of Cancer Biology. Oxford University Press, 2019. http://dx.doi.org/10.1093/med/9780198779452.001.0001.

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The study of the biology of tumours has grown to become markedly interdisciplinary, involving chemists, statisticians, epidemiologists, mathematicians, bioinformaticians, and computer scientists alongside medical scientists. Oxford Textbook of Cancer Biology brings together the developments from different branches of research into one volume. Structured in seven sections, the book starts with a review of the development and biology of multicellular organisms, how they maintain a healthy homeostasis in an individual, and a description of the molecular basis of cancer development. The book then illustrates how, once cells become neoplastic, their signalling network is altered and pathological behaviour follows. Changes that cancer cells can induce in nearby normal tissue are explored, and the new relationship established between them and the stroma is explicated. Finally, the authors illustrate the contribution provided by high throughput techniques to map cancer at different levels, from genomic sequencing to cellular metabolic functions, and how information technology with its vast amounts of data are integrated with traditional cell biology to provide a global view of the disease. The book concludes by summarizing what we know to date about cancer, and in what direction our understanding of cancer is moving.
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