Gene Quantification

Gene Quantification

Author: Francois Ferre

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 379

ISBN-13: 1461241642

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Geneticists and molecular biologists have been interested in quantifying genes and their products for many years and for various reasons (Bishop, 1974). Early molecular methods were based on molecular hybridization, and were devised shortly after Marmur and Doty (1961) first showed that denaturation of the double helix could be reversed - that the process of molecular reassociation was exquisitely sequence dependent. Gillespie and Spiegelman (1965) developed a way of using the method to titrate the number of copies of a probe within a target sequence in which the target sequence was fixed to a membrane support prior to hybridization with the probe - typically a RNA. Thus, this was a precursor to many of the methods still in use, and indeed under development, today. Early examples of the application of these methods included the measurement of the copy numbers in gene families such as the ribosomal genes and the immunoglo bulin family. Amplification of genes in tumors and in response to drug treatment was discovered by this method. In the same period, methods were invented for estimating gene num bers based on the kinetics of the reassociation process - the so-called Cot analysis. This method, which exploits the dependence of the rate of reassociation on the concentration of the two strands, revealed the presence of repeated sequences in the DNA of higher eukaryotes (Britten and Kohne, 1968). An adaptation to RNA, Rot analysis (Melli and Bishop, 1969), was used to measure the abundance of RNAs in a mixed population.


Book Synopsis Gene Quantification by : Francois Ferre

Download or read book Gene Quantification written by Francois Ferre and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: Geneticists and molecular biologists have been interested in quantifying genes and their products for many years and for various reasons (Bishop, 1974). Early molecular methods were based on molecular hybridization, and were devised shortly after Marmur and Doty (1961) first showed that denaturation of the double helix could be reversed - that the process of molecular reassociation was exquisitely sequence dependent. Gillespie and Spiegelman (1965) developed a way of using the method to titrate the number of copies of a probe within a target sequence in which the target sequence was fixed to a membrane support prior to hybridization with the probe - typically a RNA. Thus, this was a precursor to many of the methods still in use, and indeed under development, today. Early examples of the application of these methods included the measurement of the copy numbers in gene families such as the ribosomal genes and the immunoglo bulin family. Amplification of genes in tumors and in response to drug treatment was discovered by this method. In the same period, methods were invented for estimating gene num bers based on the kinetics of the reassociation process - the so-called Cot analysis. This method, which exploits the dependence of the rate of reassociation on the concentration of the two strands, revealed the presence of repeated sequences in the DNA of higher eukaryotes (Britten and Kohne, 1968). An adaptation to RNA, Rot analysis (Melli and Bishop, 1969), was used to measure the abundance of RNAs in a mixed population.


Gene Expression Analysis

Gene Expression Analysis

Author: Nalini Raghavachari

Publisher: Humana

Published: 2018-05-17

Total Pages: 0

ISBN-13: 9781493978335

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This volume provides experimental and bioinformatics approaches related to different aspects of gene expression analysis. Divided in three sections chapters detail wet-lab protocols, bioinformatics approaches, single-cell gene expression, highly multiplexed amplicon sequencing, multi-omics techniques, and targeted sequencing. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Gene Expression Analysis: Methods and Protocols aims provide useful information to researchers worldwide.


Book Synopsis Gene Expression Analysis by : Nalini Raghavachari

Download or read book Gene Expression Analysis written by Nalini Raghavachari and published by Humana. This book was released on 2018-05-17 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume provides experimental and bioinformatics approaches related to different aspects of gene expression analysis. Divided in three sections chapters detail wet-lab protocols, bioinformatics approaches, single-cell gene expression, highly multiplexed amplicon sequencing, multi-omics techniques, and targeted sequencing. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Gene Expression Analysis: Methods and Protocols aims provide useful information to researchers worldwide.


Techniques in Quantification and Localization of Gene Expression

Techniques in Quantification and Localization of Gene Expression

Author: Bruce K. Patterson

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 157

ISBN-13: 1461213428

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Can the son or daughter of a baseball pitcher or cricket bowler throw a ball 100 miles an hour? Is the son or daughter of an opera singer also an opera singer? Is a house with functional light switches lit? The line of thinking in these rhetorical questions also applies to human genetics. What do baseball pitchers, opera sing ers, light switches, and the Human Genome Project have in common? These questions address the issue of potential versus realization of function. Although sons and daughters of baseball pitchers and opera singers may have inherited the mechanical attributes to be baseball pitchers and opera singers, they may not, at any point in time, be baseball pitchers or opera singers. A house with functional light switches is not lit unless the light switches are on. Similarly, all of the genes discovered and sequenced as a result of the Human Genome Project are not expressed at the same time. Genome project information will allow us to deter mine the repertoire of genes in an individual, which is analogous to determining where the light switches in a house are located and whether they are functional (a mutation or deletion in the Genome Project Model). The pattern of "on" light switches in a house gives us functional information as to what the family inside is doing (e. g. , eating, reading, sleeping). Similarly, the pattern of gene expression (RNA) gives us information on what our bodies are doing (e. g.


Book Synopsis Techniques in Quantification and Localization of Gene Expression by : Bruce K. Patterson

Download or read book Techniques in Quantification and Localization of Gene Expression written by Bruce K. Patterson and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 157 pages. Available in PDF, EPUB and Kindle. Book excerpt: Can the son or daughter of a baseball pitcher or cricket bowler throw a ball 100 miles an hour? Is the son or daughter of an opera singer also an opera singer? Is a house with functional light switches lit? The line of thinking in these rhetorical questions also applies to human genetics. What do baseball pitchers, opera sing ers, light switches, and the Human Genome Project have in common? These questions address the issue of potential versus realization of function. Although sons and daughters of baseball pitchers and opera singers may have inherited the mechanical attributes to be baseball pitchers and opera singers, they may not, at any point in time, be baseball pitchers or opera singers. A house with functional light switches is not lit unless the light switches are on. Similarly, all of the genes discovered and sequenced as a result of the Human Genome Project are not expressed at the same time. Genome project information will allow us to deter mine the repertoire of genes in an individual, which is analogous to determining where the light switches in a house are located and whether they are functional (a mutation or deletion in the Genome Project Model). The pattern of "on" light switches in a house gives us functional information as to what the family inside is doing (e. g. , eating, reading, sleeping). Similarly, the pattern of gene expression (RNA) gives us information on what our bodies are doing (e. g.


Rapid Cycle Real-Time PCR — Methods and Applications

Rapid Cycle Real-Time PCR — Methods and Applications

Author: W. Dietmaier

Publisher: Springer Science & Business Media

Published: 2013-06-29

Total Pages: 200

ISBN-13: 3642593976

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Rapid-Cycle Real-Time PCR is a powerful technique for nucleic acid amplification and analysis that often requires less than half an hour to perform. Samples are amplified by rapid-cycle PCR followed by immediate melting curve analysis in the same instrument. Melting curve analysis of PCR products with SYBR Green I often allows product identification without gel electrophoresis. Furthermore, in the presence of fluorescent hybridization probes, melting curves provide "dynamic dot blots" for fine sequence analysis, including single nucleotide polymorphisms (SNPs). The method is often cited as the most versatile, efficient method for nucleic acid analysis in research and diagnostics in the fields of genetics and oncology. Molecular diagnostics has never been easier!


Book Synopsis Rapid Cycle Real-Time PCR — Methods and Applications by : W. Dietmaier

Download or read book Rapid Cycle Real-Time PCR — Methods and Applications written by W. Dietmaier and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: Rapid-Cycle Real-Time PCR is a powerful technique for nucleic acid amplification and analysis that often requires less than half an hour to perform. Samples are amplified by rapid-cycle PCR followed by immediate melting curve analysis in the same instrument. Melting curve analysis of PCR products with SYBR Green I often allows product identification without gel electrophoresis. Furthermore, in the presence of fluorescent hybridization probes, melting curves provide "dynamic dot blots" for fine sequence analysis, including single nucleotide polymorphisms (SNPs). The method is often cited as the most versatile, efficient method for nucleic acid analysis in research and diagnostics in the fields of genetics and oncology. Molecular diagnostics has never been easier!


The Analysis of Gene Expression Data

The Analysis of Gene Expression Data

Author: Giovanni Parmigiani

Publisher: Springer Science & Business Media

Published: 2006-04-11

Total Pages: 511

ISBN-13: 0387216790

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This book presents practical approaches for the analysis of data from gene expression micro-arrays. It describes the conceptual and methodological underpinning for a statistical tool and its implementation in software. The book includes coverage of various packages that are part of the Bioconductor project and several related R tools. The materials presented cover a range of software tools designed for varied audiences.


Book Synopsis The Analysis of Gene Expression Data by : Giovanni Parmigiani

Download or read book The Analysis of Gene Expression Data written by Giovanni Parmigiani and published by Springer Science & Business Media. This book was released on 2006-04-11 with total page 511 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents practical approaches for the analysis of data from gene expression micro-arrays. It describes the conceptual and methodological underpinning for a statistical tool and its implementation in software. The book includes coverage of various packages that are part of the Bioconductor project and several related R tools. The materials presented cover a range of software tools designed for varied audiences.


Techniques in Quantification and Localization of Gene Expression

Techniques in Quantification and Localization of Gene Expression

Author: Bruce K. Patterson

Publisher: Springer Science & Business Media

Published: 2000-01-24

Total Pages: 174

ISBN-13: 9780817640347

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"Sensitive detection of gene expression is hindered by poor recovery or preservation of target sequences. This book emphasizes methods that are optimized to ensure full recovery and preservation of gene expression targets from specimen acquisition through to detection and final analysis." "Researchers and students in cellular biology will find this book a very useful guide to gene localizing techniques."--BOOK JACKET.


Book Synopsis Techniques in Quantification and Localization of Gene Expression by : Bruce K. Patterson

Download or read book Techniques in Quantification and Localization of Gene Expression written by Bruce K. Patterson and published by Springer Science & Business Media. This book was released on 2000-01-24 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Sensitive detection of gene expression is hindered by poor recovery or preservation of target sequences. This book emphasizes methods that are optimized to ensure full recovery and preservation of gene expression targets from specimen acquisition through to detection and final analysis." "Researchers and students in cellular biology will find this book a very useful guide to gene localizing techniques."--BOOK JACKET.


Gene Expression Data Analysis

Gene Expression Data Analysis

Author: Pankaj Barah

Publisher: CRC Press

Published: 2021-11-21

Total Pages: 379

ISBN-13: 1000425738

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Development of high-throughput technologies in molecular biology during the last two decades has contributed to the production of tremendous amounts of data. Microarray and RNA sequencing are two such widely used high-throughput technologies for simultaneously monitoring the expression patterns of thousands of genes. Data produced from such experiments are voluminous (both in dimensionality and numbers of instances) and evolving in nature. Analysis of huge amounts of data toward the identification of interesting patterns that are relevant for a given biological question requires high-performance computational infrastructure as well as efficient machine learning algorithms. Cross-communication of ideas between biologists and computer scientists remains a big challenge. Gene Expression Data Analysis: A Statistical and Machine Learning Perspective has been written with a multidisciplinary audience in mind. The book discusses gene expression data analysis from molecular biology, machine learning, and statistical perspectives. Readers will be able to acquire both theoretical and practical knowledge of methods for identifying novel patterns of high biological significance. To measure the effectiveness of such algorithms, we discuss statistical and biological performance metrics that can be used in real life or in a simulated environment. This book discusses a large number of benchmark algorithms, tools, systems, and repositories that are commonly used in analyzing gene expression data and validating results. This book will benefit students, researchers, and practitioners in biology, medicine, and computer science by enabling them to acquire in-depth knowledge in statistical and machine-learning-based methods for analyzing gene expression data. Key Features: An introduction to the Central Dogma of molecular biology and information flow in biological systems A systematic overview of the methods for generating gene expression data Background knowledge on statistical modeling and machine learning techniques Detailed methodology of analyzing gene expression data with an example case study Clustering methods for finding co-expression patterns from microarray, bulkRNA, and scRNA data A large number of practical tools, systems, and repositories that are useful for computational biologists to create, analyze, and validate biologically relevant gene expression patterns Suitable for multidisciplinary researchers and practitioners in computer science and biological sciences


Book Synopsis Gene Expression Data Analysis by : Pankaj Barah

Download or read book Gene Expression Data Analysis written by Pankaj Barah and published by CRC Press. This book was released on 2021-11-21 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: Development of high-throughput technologies in molecular biology during the last two decades has contributed to the production of tremendous amounts of data. Microarray and RNA sequencing are two such widely used high-throughput technologies for simultaneously monitoring the expression patterns of thousands of genes. Data produced from such experiments are voluminous (both in dimensionality and numbers of instances) and evolving in nature. Analysis of huge amounts of data toward the identification of interesting patterns that are relevant for a given biological question requires high-performance computational infrastructure as well as efficient machine learning algorithms. Cross-communication of ideas between biologists and computer scientists remains a big challenge. Gene Expression Data Analysis: A Statistical and Machine Learning Perspective has been written with a multidisciplinary audience in mind. The book discusses gene expression data analysis from molecular biology, machine learning, and statistical perspectives. Readers will be able to acquire both theoretical and practical knowledge of methods for identifying novel patterns of high biological significance. To measure the effectiveness of such algorithms, we discuss statistical and biological performance metrics that can be used in real life or in a simulated environment. This book discusses a large number of benchmark algorithms, tools, systems, and repositories that are commonly used in analyzing gene expression data and validating results. This book will benefit students, researchers, and practitioners in biology, medicine, and computer science by enabling them to acquire in-depth knowledge in statistical and machine-learning-based methods for analyzing gene expression data. Key Features: An introduction to the Central Dogma of molecular biology and information flow in biological systems A systematic overview of the methods for generating gene expression data Background knowledge on statistical modeling and machine learning techniques Detailed methodology of analyzing gene expression data with an example case study Clustering methods for finding co-expression patterns from microarray, bulkRNA, and scRNA data A large number of practical tools, systems, and repositories that are useful for computational biologists to create, analyze, and validate biologically relevant gene expression patterns Suitable for multidisciplinary researchers and practitioners in computer science and biological sciences


Cap-Analysis Gene Expression (CAGE)

Cap-Analysis Gene Expression (CAGE)

Author: Piero Carninci

Publisher: Pan Stanford Publishing

Published: 2010

Total Pages: 281

ISBN-13: 9814241342

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This book is a guide for users of new technologies, as it includes accurately proven protocols, allowing readers to prepare their samples for experiments. Although examples mainly concern mammalians, the discussion expands to other groups of eukaryotes, where these approaches are complementing genome sequencing.


Book Synopsis Cap-Analysis Gene Expression (CAGE) by : Piero Carninci

Download or read book Cap-Analysis Gene Expression (CAGE) written by Piero Carninci and published by Pan Stanford Publishing. This book was released on 2010 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a guide for users of new technologies, as it includes accurately proven protocols, allowing readers to prepare their samples for experiments. Although examples mainly concern mammalians, the discussion expands to other groups of eukaryotes, where these approaches are complementing genome sequencing.


Primer of Genetic Analysis

Primer of Genetic Analysis

Author: James N. Thompson, Jr

Publisher: Cambridge University Press

Published: 2007-10-01

Total Pages: 488

ISBN-13: 1139465643

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An invaluable student-tested study aid, this primer, first published in 2007, provides guided instruction for the analysis and interpretation of genetic principles and practice in problem solving. Each section is introduced with a summary of useful hints for problem solving and an overview of the topic with key terms. A series of problems, generally progressing from simple to more complex, then allows students to test their understanding of the material. Each question and answer is accompanied by detailed explanation. This third edition includes additional problems in basic areas that often challenge students, extended coverage in molecular biology and development, an expanded glossary of terms, and updated historical landmarks. Students at all levels, from beginning biologists and premedical students to graduates seeking a review of basic genetics, will find this book a valuable aid. It will complement the formal presentation in any genetics textbook or stand alone as a self-paced review manual.


Book Synopsis Primer of Genetic Analysis by : James N. Thompson, Jr

Download or read book Primer of Genetic Analysis written by James N. Thompson, Jr and published by Cambridge University Press. This book was released on 2007-10-01 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: An invaluable student-tested study aid, this primer, first published in 2007, provides guided instruction for the analysis and interpretation of genetic principles and practice in problem solving. Each section is introduced with a summary of useful hints for problem solving and an overview of the topic with key terms. A series of problems, generally progressing from simple to more complex, then allows students to test their understanding of the material. Each question and answer is accompanied by detailed explanation. This third edition includes additional problems in basic areas that often challenge students, extended coverage in molecular biology and development, an expanded glossary of terms, and updated historical landmarks. Students at all levels, from beginning biologists and premedical students to graduates seeking a review of basic genetics, will find this book a valuable aid. It will complement the formal presentation in any genetics textbook or stand alone as a self-paced review manual.


Computational Methods for the Analysis of Genomic Data and Biological Processes

Computational Methods for the Analysis of Genomic Data and Biological Processes

Author: Francisco A. Gómez Vela

Publisher: MDPI

Published: 2021-02-05

Total Pages: 222

ISBN-13: 3039437712

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In recent decades, new technologies have made remarkable progress in helping to understand biological systems. Rapid advances in genomic profiling techniques such as microarrays or high-performance sequencing have brought new opportunities and challenges in the fields of computational biology and bioinformatics. Such genetic sequencing techniques allow large amounts of data to be produced, whose analysis and cross-integration could provide a complete view of organisms. As a result, it is necessary to develop new techniques and algorithms that carry out an analysis of these data with reliability and efficiency. This Special Issue collected the latest advances in the field of computational methods for the analysis of gene expression data, and, in particular, the modeling of biological processes. Here we present eleven works selected to be published in this Special Issue due to their interest, quality, and originality.


Book Synopsis Computational Methods for the Analysis of Genomic Data and Biological Processes by : Francisco A. Gómez Vela

Download or read book Computational Methods for the Analysis of Genomic Data and Biological Processes written by Francisco A. Gómez Vela and published by MDPI. This book was released on 2021-02-05 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent decades, new technologies have made remarkable progress in helping to understand biological systems. Rapid advances in genomic profiling techniques such as microarrays or high-performance sequencing have brought new opportunities and challenges in the fields of computational biology and bioinformatics. Such genetic sequencing techniques allow large amounts of data to be produced, whose analysis and cross-integration could provide a complete view of organisms. As a result, it is necessary to develop new techniques and algorithms that carry out an analysis of these data with reliability and efficiency. This Special Issue collected the latest advances in the field of computational methods for the analysis of gene expression data, and, in particular, the modeling of biological processes. Here we present eleven works selected to be published in this Special Issue due to their interest, quality, and originality.