Proteome Informatics
Proteome Informatics

Author: Conrad Bessant

Publisher: Royal Society of Chemistry

Published: 2016-11-15

Total Pages: 429

ISBN-13: 1782626735

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The field of proteomics has developed rapidly over the past decade nurturing the need for a detailed introduction to the various informatics topics that underpin the main liquid chromatography tandem mass spectrometry (LC-MS/MS) protocols used for protein identification and quantitation. Proteins are a key component of any biological system, and monitoring proteins using LC-MS/MS proteomics is becoming commonplace in a wide range of biological research areas. However, many researchers treat proteomics software tools as a black box, drawing conclusions from the output of such tools without considering the nuances and limitations of the algorithms on which such software is based. This book seeks to address this situation by bringing together world experts to provide clear explanations of the key algorithms, workflows and analysis frameworks, so that users of proteomics data can be confident that they are using appropriate tools in suitable ways.

Mass Spectrometry and Genomic Analysis
Mass Spectrometry and Genomic Analysis

Author: J.N. Housby

Publisher: Springer Science & Business Media

Published: 2005-12-20

Total Pages: 161

ISBN-13: 0306475952

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76 2. Short Oligonucleotide Mass Analysis 76 2. 1. Method Outline 76 2. 2. Design of PCR Primers and Fragments for Analysis 78 2. 3. Typical PCR Reaction Conditions 79 3. Electrospray Ionisation Mass Spectrometry 79 Formation of Ions 3. 1. 79 3. 2. Tandem Mass Spectrometry 79 3. 3. Typical ESI-MS Settings for SOMA 80 4. Purification Procedures 80 4. 1. Phenol/Chloroform Extraction and Ethanol Precipitation 80 4. 2. In-line HPLC Purification 81 5. Genotyping Using SOMA 81 5. 1. APC Genotyping in Human Subjects 81 5. 2. APC Genotyping in Min Mice 85 5. Mutation Detection Using SOMA 86 6. 1. Analysis of p53 Mutations in Liver Cancer Patients 86 6. 1. 1. p53 Mutations in Liver Tumours 87 6. 1. 2. p53 Mutations in Plasma Samples 88 7. Advantages and Disadvantages of SOMA 89 8. Future Perspectives 90 9. Acknowledgements 91 10. References 91 CHAPTER 7 WV. Bienvenut, M. Müller, PM. Palagi, E. Gasteiger, M. Heller, E. Jung, M. Giron, R. Gras, S. Gay, PA. Binz, G J. Hughes, JC. Sanchez, RD. Appel, DF. Hochstrasser Proteomics and Mass Spectrometry: Some Aspects and Recent Developments 1. Introduction to Proteomics 93 2. Protein Biochemical and Chemical Processing Followed by Mass Spectrometric Analysis 94 2. 1. 2-DE Gel Protein Separation 95 Protein Identification Using Peptide Mass Fingerprinting and Robots 96 2. 2. 2. 2. 1. MALDI-MS Analysis 98 2. 2. 2. MS/MS Analysis 102 Improvement of the Identification by Chemical Modification of Peptides 106 2. 2. 3.

Fundamentals of Data Mining in Genomics and Proteomics
Fundamentals of Data Mining in Genomics and Proteomics

Author: Werner Dubitzky

Publisher: Springer Science & Business Media

Published: 2007-04-13

Total Pages: 300

ISBN-13: 0387475095

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This book presents state-of-the-art analytical methods from statistics and data mining for the analysis of high-throughput data from genomics and proteomics. It adopts an approach focusing on concepts and applications and presents key analytical techniques for the analysis of genomics and proteomics data by detailing their underlying principles, merits and limitations.

Evolution of Translational Omics
Evolution of Translational Omics

Author: Institute of Medicine

Publisher: National Academies Press

Published: 2012-09-13

Total Pages: 354

ISBN-13: 0309224187

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Technologies collectively called omics enable simultaneous measurement of an enormous number of biomolecules; for example, genomics investigates thousands of DNA sequences, and proteomics examines large numbers of proteins. Scientists are using these technologies to develop innovative tests to detect disease and to predict a patient's likelihood of responding to specific drugs. Following a recent case involving premature use of omics-based tests in cancer clinical trials at Duke University, the NCI requested that the IOM establish a committee to recommend ways to strengthen omics-based test development and evaluation. This report identifies best practices to enhance development, evaluation, and translation of omics-based tests while simultaneously reinforcing steps to ensure that these tests are appropriately assessed for scientific validity before they are used to guide patient treatment in clinical trials.

Applications of Toxicogenomic Technologies to Predictive Toxicology and Risk Assessment
Applications of Toxicogenomic Technologies to Predictive Toxicology and Risk Assessment

Author: National Research Council

Publisher: National Academies Press

Published: 2007-12-19

Total Pages: 300

ISBN-13: 0309112982

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The new field of toxicogenomics presents a potentially powerful set of tools to better understand the health effects of exposures to toxicants in the environment. At the request of the National Institute of Environmental Health Sciences, the National Research Council assembled a committee to identify the benefits of toxicogenomics, the challenges to achieving them, and potential approaches to overcoming such challenges. The report concludes that realizing the potential of toxicogenomics to improve public health decisions will require a concerted effort to generate data, make use of existing data, and study data in new waysâ€"an effort requiring funding, interagency coordination, and data management strategies.

Reaping the Benefits of Genomic and Proteomic Research
Reaping the Benefits of Genomic and Proteomic Research

Author: National Research Council

Publisher: National Academies Press

Published: 2006-04-09

Total Pages: 189

ISBN-13: 0309100674

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The patenting and licensing of human genetic material and proteins represents an extension of intellectual property (IP) rights to naturally occurring biological material and scientific information, much of it well upstream of drugs and other disease therapies. This report concludes that IP restrictions rarely impose significant burdens on biomedical research, but there are reasons to be apprehensive about their future impact on scientific advances in this area. The report recommends 13 actions that policy-makers, courts, universities, and health and patent officials should take to prevent the increasingly complex web of IP protections from getting in the way of potential breakthroughs in genomic and proteomic research. It endorses the National Institutes of Health guidelines for technology licensing, data sharing, and research material exchanges and says that oversight of compliance should be strengthened. It recommends enactment of a statutory exception from infringement liability for research on a patented invention and raising the bar somewhat to qualify for a patent on upstream research discoveries in biotechnology. With respect to genetic diagnostic tests to detect patient mutations associated with certain diseases, the report urges patent holders to allow others to perform the tests for purposes of verifying the results.

Proteomics Data Analysis
Proteomics Data Analysis

Author: Daniela Cecconi

Publisher:

Published: 2021

Total Pages: 326

ISBN-13: 9781071616413

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This thorough book collects methods and strategies to analyze proteomics data. It is intended to describe how data obtained by gel-based or gel-free proteomics approaches can be inspected, organized, and interpreted to extrapolate biological information. Organized into four sections, the volume explores strategies to analyze proteomics data obtained by gel-based approaches, different data analysis approaches for gel-free proteomics experiments, bioinformatic tools for the interpretation of proteomics data to obtain biological significant information, as well as methods to integrate proteomics data with other omics datasets including genomics, transcriptomics, metabolomics, and other types of data. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detailed implementation advice that will ensure high quality results in the lab. Authoritative and practical, Proteomics Data Analysis serves as an ideal guide to introduce researchers, both experienced and novice, to new tools and approaches for data analysis to encourage the further study of proteomics.

Quantitative Proteome Analysis
Quantitative Proteome Analysis

Author: Kazuhiro Imai

Publisher: CRC Press

Published: 2013-08-05

Total Pages: 314

ISBN-13: 9814316512

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This book focuses on the advantages and disadvantages of each of the commonly used quantitative proteomic methods in terms of accuracy, sensitivity, and reproducibility. It also concentrates on the effective applications of these methods that resulted in many discoveries of the role of the proteins expressed in living cells and biological fluids. The first part of the book focuses on the description of advantages and disadvantages of each of the commonly used quantitative proteomic methods in terms of accuracy, sensitivity, and, especially, reproducibility. The second part of the book focuses on providing concise descriptions of the effective applications of these methods to demonstrate how they have resulted in many important discoveries of the roles of the proteins expressed in living cells.

Data Mining for Genomics and Proteomics
Data Mining for Genomics and Proteomics

Author: Darius M. Dziuda

Publisher: John Wiley & Sons

Published: 2010-07-16

Total Pages: 348

ISBN-13: 0470593407

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Data Mining for Genomics and Proteomics uses pragmatic examples and a complete case study to demonstrate step-by-step how biomedical studies can be used to maximize the chance of extracting new and useful biomedical knowledge from data. It is an excellent resource for students and professionals involved with gene or protein expression data in a variety of settings.

Topological Data Analysis for Genomics and Evolution
Topological Data Analysis for Genomics and Evolution

Author: Raúl Rabadán

Publisher: Cambridge University Press

Published: 2019-10-31

Total Pages: 521

ISBN-13: 1108753396

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Biology has entered the age of Big Data. The technical revolution has transformed the field, and extracting meaningful information from large biological data sets is now a central methodological challenge. Algebraic topology is a well-established branch of pure mathematics that studies qualitative descriptors of the shape of geometric objects. It aims to reduce questions to a comparison of algebraic invariants, such as numbers, which are typically easier to solve. Topological data analysis is a rapidly-developing subfield that leverages the tools of algebraic topology to provide robust multiscale analysis of data sets. This book introduces the central ideas and techniques of topological data analysis and its specific applications to biology, including the evolution of viruses, bacteria and humans, genomics of cancer and single cell characterization of developmental processes. Bridging two disciplines, the book is for researchers and graduate students in genomics and evolutionary biology alongside mathematicians interested in applied topology.