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Готові списки джерел за темами / High Throughput Phenotypic Data / Книги

Книги з теми "High Throughput Phenotypic Data"

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Автор: Grafiati

Опубліковано: 10 грудня 2022

Оновлено: 28 січня 2023

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Ознайомтеся з топ-36 книг для дослідження на тему "High Throughput Phenotypic Data".

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1

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

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2

Geurts, Werner, Francky Catthoor, Serge Vernalde, and Hugo de Man. Accelerator Data-Path Synthesis for High-Throughput Signal Processing Applications. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4419-8720-4.

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3

Werner, Geurts, ed. Accelerator data-path synthesis for high-throughput signal processing applications. Dordrecht: Kluwer Academic Publishers, 1997.

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4

library, Wiley online, ed. Systems biology in psychiatric research: From high-throughput data to mathematical modeling. Weinheim: Wiley-VCH, 2010.

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5

Yang, Po-sŏk. Twaeji yujŏnch'e taeryang yŏmgi sŏyŏl punsŏk mit yuyong yujŏnja palgul =: High-throughput DNA sequence analysis and identification of trait genes in pigs. [Kyŏnggi-do Suwŏn-si]: Nongch'on Chinhŭngch'ŏng, 2009.

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6

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

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7

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

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8

A, Ravishankar Rao, and Cecchi Guillermo A, eds. High-throughput image reconstruction and analysis. Norwood, MA: Artech House, 2009.

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9

Catthoor, Francky, Hugo De Man, Werner Geurts, and Serge Vernalde. Accelerator Data-Path Synthesis for High-Throughput Signal Processing Applications. Springer, 1996.

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10

Catthoor, Francky, Hugo De Man, Werner Geurts, and Serge Vernalde. Accelerator Data-Path Synthesis for High-Throughput Signal Processing Applications. Springer, 2012.

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11

Accelerator Data-Path Synthesis for High-Throughput Signal Processing Applications. Boston, MA: Springer US, 1997.

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12

Tseng, George C., Zhiguang Huo, and Tianzhou Ma. Foundations for High-Throughput Omics Data Analysis: Methods, Theories and Applications. Taylor & Francis Group, 2023.

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13

Maleki, Farhad, Renee Menezes, Sorin Draghici, and Anthony Kusalik, eds. Advancement in Gene Set Analysis: Gaining Insight From High-throughput Data. Frontiers Media SA, 2022. http://dx.doi.org/10.3389/978-2-88976-423-5.

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14

Advances in Statistical Bioinformatics: Models and Integrative Inference for High-Throughput Data. University of Cambridge ESOL Examinations, 2013.

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15

Do, Kim-Anh, Marina Vannucci, and Zhaohui Steve Qin. Advances in Statistical Bioinformatics: Models and Integrative Inference for High-Throughput Data. Cambridge University Press, 2013.

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16

Do, Kim-Anh, Marina Vannucci, and Zhaohui Steve Qin. Advances in Statistical Bioinformatics: Models and Integrative Inference for High-Throughput Data. Cambridge University Press, 2013.

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17

International Union of Pure and Applied Chemistry (Corporate Author) and P. W. Erhardt (Editor), eds. Drug Metabolism: Databases and High-Throughput Testing During Drug Design and Development (IUPAC Chemical Data). Blackwell Science Inc, 1999.

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18

Zhang, Xiaohua Douglas. Optimal High-Throughput Screening: Practical Experimental Design and Data Analysis for Genome-Scale RNAi Research. Cambridge University Press, 2011.

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19

Zhang, Xiaohua Douglas. Optimal High-Throughput Screening: Practical Experimental Design and Data Analysis for Genome-Scale RNAi Research. Cambridge University Press, 2011.

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20

Zhang, Xiaohua Douglas. Optimal High-Throughput Screening: Practical Experimental Design and Data Analysis for Genome-Scale RNAi Research. Cambridge University Press, 2011.

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21

Zhang, Xiaohua Douglas. Optimal High-Throughput Screening: Practical Experimental Design and Data Analysis for Genome-Scale Rnai Research. Cambridge University Press, 2011.

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22

Zhang, Xiaohua Douglas. Optimal High-Throughput Screening: Practical Experimental Design and Data Analysis for Genome-Scale RNAi Research. Cambridge University Press, 2011.

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23

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

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24

Optimal Highthroughput Screening Practical Experimental Design And Data Analysis For Genomescale Rnai Research. Cambridge University Press, 2011.

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25

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

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26

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

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27

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

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28

Lattman, Eaton E., Thomas D. Grant, and Edward H. Snell. Distinct Instrumental Approaches to SAXS. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199670871.003.0010.

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Анотація:

There are more specialized applications of SAXS and SANS which require specific experimental considerations. This chapter covers size exclusion chromatography which has proven to be useful to study both soluble and membrane bound proteins allowing the study of samples that show time and concentration dependent dynamics. It also describes iime-resolved techniques for SAXS and in a few cases, SANS. Finally, with improved X-ray sources, detectors, sample handling, and compute power, the ability to perform SAXS data in high-throughput is available. This is discussed in enabling the use of SAXS to study protein interactions, map macromolecular conformation, and rapidly characterize samples amongst other applications.

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29

Wagenlehner, Florian M. E., Adrian Pilatz, Thomas Bschleipfer, Thorsten Diemer, and Wolfgang Weidner. Inflammation. Edited by Rob Pickard. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199659579.003.0007.

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There is a consensus on the diagnostic and therapeutic manage¬ment of bacterial prostatitis (acute and chronic). However, increas¬ing antimicrobial resistance rates for quinolones pose problems for the future, especially for therapy of chronic bac¬terial prostatitis. In chronic prostatitis/chronic pelvic pain syndrome, the diag¬nostic approach currently points more and more to an individu¬alized phenotypic assessment, in an effort to direct multimodal management towards improvement of specific symptom domains. Most therapy trials for single agents in CP/CPPS have been nega¬tive, therefore stratification by phenotype followed by individu¬alized multimodal treatment seems to be a promising strategy, although good evidence-based data are not available currently to substantiate this. Consensus regarding the need and option for treatment of asymptomatic prostatitis is far from being achieved. Therefore, taking the high prevalence of infections and inflammations in different asymptomatic conditions into consideration, further research is urgently needed to address this important field.

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30

Patisaul, Heather B., and Scott M. Belcher. The Path Forward. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780199935734.003.0008.

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This chapter focuses on the contemporary approaches of research being used to understand the actions of EDCs and emerging high-throughput screening approaches to examine new and existing chemicals for endocrine-disrupting activities. Concepts arising from the 2007 NRC report “Toxicity Testing in the 21st Century: A Vision and a Strategy” are delineated and the ongoing development of predictive computational toxicology approaches are addressed. The screening strategies being developed under the Tox21 and Toxicity Forecaster (ToxCast) programs are described, with a review of advantages, challenges, and progress to date. There is a brief overview of the EPA’s Interactive Chemical Safety for Sustainability (iCSS) Dashboard as a portal for accessing the ToxCast data through ToxCastDB, and the EPA’s Aggregated Computational Toxicology data warehouse (ACToR), which contains all publicly available EPA chemical toxicity data. Additional challenges related to the inability of current screening approaches to address complex physiology involved in neuroendocrine disruption are addressed.

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31

Grunert, Marcel, Andreas Perrot, and Silke Rickert-Sperling. Complex network interactions: cardiovascular systems biology. Edited by José Maria Pérez-Pomares, Robert G. Kelly, Maurice van den Hoff, José Luis de la Pompa, David Sedmera, Cristina Basso, and Deborah Henderson. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198757269.003.0033.

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A large quantity of molecular information on heart development, function, and disease has been generated over recent decades. However, most recent studies have been dominated by reductionistic approaches, and thus many aspects remain unclear, particularly regarding the primary causes of complex cardiovascular diseases such as congenital heart malformations. With the advent of high-throughput technologies, systems-based approaches have developed rapidly in biology and medicine. In the biology of cardiovascular systems complex data within or across different molecular levels of biological systems or pathways can be integrated and combined to identify the causes underlying cardiac diseases, which might not be possible otherwise. This is in agreement with data suggesting that biological molecules in individual regulatory layers, such as transcripts, proteins, and metabolites, act within networksrather than independently of each other. Thus systems biology provides a promising approach to fully addressing the complexities of congenital heart disease.

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32

Patisaul, Heather B., and Scott M. Belcher. Risk Assessment and Chemical Regulatory Policy in the United States and Abroad. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780199935734.003.0007.

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This chapter presents an overview of the risk assessment process with an in-depth description of the related terminology. Critical study features that should be included to maximize utility of data for risk assessment for any experimental study are presented as an aid for academic scientists interested in designing studies with utility in the risk assessment process. The second half of this chapter summarizes the current state of regulatory policy regarding EDCs in the United States and abroad. Topics addressed include the Toxic Substances Control Act (TSCA) and a detailed accounting of the changes enacted by the recent 2016 revisions to TSCA. These policies are compared to the Registration Evaluation Authorization and Restriction of Chemicals (REACH) laws that govern chemical safety assessment in the European Union. The Endocrine Disruptor Screening Program (EDSP) and current efforts toward developing high-throughput methods for screening chemicals for endocrine-disrupting activity are also summarized.

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33

Ward, Elizabeth. Cancer. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190662677.003.0024.

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This chapter provides an overview of the mechanisms by which cancer develops and the importance of exogenous exposures in cancer causation. It describes the magnitude of cancer as a public health problem in the United States and globally, highlights temporal trends in cancer rates in the United States and variations in global cancer burden by country, income level, and region. Laboratory methods for identification of potential carcinogens are reviewed with emphasis on recent developments in toxicogenomics and high-throughput screening. The classification system used by the International Agency for Research on Cancer (IARC) in evaluation of potential carcinogens is described, and data are presented on occupational and environmental agents classified as “carcinogenic to humans” or “probably carcinogenic to humans.” Specific occupational and environmental carcinogens are discussed in greater detail. Topics of interest to clinicians and public health practicioners include the evaluation of occupational and community cancer clusters, primary and secondary prevention of occupational cancer, and four case studies related to cancer prevention and control and risk communication in diverse occupational settings.

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34

Pezzella, Francesco, Mahvash Tavassoli, and 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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35

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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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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36

Taberlet, Pierre, Aurélie Bonin, Lucie Zinger, and 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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