Overview

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.

Full Product Details

Author:   Conrad Bessant (Queen Mary University of London, UK) ,  Simon J. Gaskell ,  Conrad Bessant ,  Bin Ma
Publisher:   Royal Society of Chemistry
Imprint:   Royal Society of Chemistry
Volume:   Volume 5
Dimensions:   Width: 15.60cm , Height: 2.80cm , Length: 23.40cm
Weight:   0.795kg
ISBN:  

9781782624288

ISBN 10:   1782624287
Pages:   428
Publication Date:   23 November 2016
Audience:   College/higher education ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

Introduction to Proteome Informatics; De Novo Sequencing; Peptide-Spectrum Matching; PSM Scoring and Validation; Protein Grouping; Identification and Localisation of Post Translational Modifications; Algorithms for MS1-Based Quantitation; Algorithms for MS2-Based Quantitation; Informatics Solutions for Selected Reaction Monitoring; Data Analysis for Data Independent Acquisition; Mining Proteomics Repositories; Data Formats of the Proteomics Standards Initiative; OpenMS; Using Galaxy for Proteomics; R for Proteomics; Proteogenomics: Proteomics for Genome Annotation; Proteomics Informed by Transcriptomics; Subject Index

Reviews

This is a timely book for the proteomics researcher in guiding decision trees involved in the informatics pipelines of this rapidly developing field. The book does an excellent job in focusing on that part of the informatics discipline, both at the user interface and behind the scenes algorithms, that is of great importance to developing innovative and effective methods for protein interrogation. -- Taufika Islam Williams * Analytical and Bioanalytical Chemistry * Book's topic: Proteomics, the comprehensive interrogation of proteins expressed by a living system, has enjoyed expeditious growth and development in recent years, as it brings together a range of informatics themes that fortify and support the everincreasing power of LC-MS/MS platforms to tackle important biological questions. Proteins are the vehicles of change in living cells and understanding them is elemental to understanding molecular biology. The complexity of the proteomics workflow, from sample preparation to LC-MS/MS to bioinformatics analyses, is such thatmore often than not, the intricacies and indeed shortcomings of the bioinformatics software are not carefully considered during data interpretation. This is an unwelcome prospect, given that comprehending the inner workings of living systems can be intimately tied to fluctuating patterns of protein expression,which can only be as thoroughly understood as the cumulative proteomics experiment allows. State-of-the-art sample preparation and LC-MS/MS will only be as biologically informative as the informatics methods with which data are interrogated. Proteome informatics is described as the ever increasing collection of bioinformatics methodologies that can be exercised in the analysis of protein expression. The book Proteome informatics, edited byConradBessant and the 5th volume of the Royal Society of Chemistry on New Developments in Mass Spectrometry, describes the bioinformatics of proteome analyses in the very context of proteomics workflows. It is an opportune discussion by leading experts on the current state of this evolving discipline, highlighting the essential fund of knowledge that will enable the proteomics expert, who may or may not be well-versed in computer science or statistics, to exploit and construct algorithms that can effectively interrogate gigabytes of data, while keeping a sharp focus on the limitations of what such software can reasonably underscore about the system being studied. Contents: This book is divided into four main sections, which follow an introductory chapter on proteome informatics. The first section describes protein identification and begins with manual de novo sequencing to more sophisticated de novo algorithms. The book steers into details of peptide spectrum matching by database search and the alternative spectral library search in use today. Despite the established advantages of the latter, the approach is only as good as the population of the library itself, which invariably limits the identification of experimental peptides and their post-translational modifications (PTMs). Discussion proceeds into peptide-spectrum match (PSM) scoring and validation, a lynchpin of proteome informatics which unequivocally dictates the goodness of fit in a given peptide (and subsequently protein) identification. Merits and demerits of common methods are briefly explored. This is proceeded by a chapter on protein grouping, which links identified peptides to identifying proteins. The section concludes with commentary on identification and positioning of the all-important PTMs. Indeed, the hundreds of in vivo PTMs (not to mention the many more possibilities of chemical modifications that may be artificially introduced into the system under investigation) are subject to change with changing cellular milieu, and hence are critical in a comprehensive proteomics study. The second section is dedicated to the quantification of proteins. Algorithms detailing MS1-based quantification are examined in its five components. The central point for such algorithms is the detection and quantification of peptidespecific signal patterns, called features. Peptide- and protein level identification are effected using precursor ion exact mass, charge state, and tandem MS. Chromatographic alignment fine-tunes all runs to a common retention time (RT) coordinate system such that corresponding features will display analogous RTs. -- Taufika Islam Williams * Analytical and Bioanalytical Chemistry - Review part 1 * by Charles Malkoff (2016), Modern proteomics-sample preparation, analysis and practical applications edited by Hamid Mirzaei and Martin Carrasco (2016), Protein bioinformatics edited by Cathy Wu, Cecilia Arighi and Karen Ross (2017). Some provide a bird's eye view of informatics as applied to proteomics. Some delve deeper into PTMs, while others focus on database searching aspects, cancer research, human proteins, or the interplay between gene expression and protein expression. Yet others center on proteomics while discussing informatics as a part of the whole experiment or explore specific MS-based methods and data analysis strategies. This book presents the advantage of elaborating important bioinformatics details, both at the user interface and behind the scenes (i.e., software algorithms), that should be carefully considered by the proteomics scientist in experimental design to better understand and interpret the data. Critical assessment: The book performs a thorough assessment of informatics processes and considerations in proteomics. Representative examples of informatics workflows are provided and discussed, but given the breadth of the subject, not all important bioinformatics software that is currently used in proteomics (i.e., Byonic (TM) by Protein Metrics) was able to receive attention. This is relevant because a detailed comparison of the inner workings of proteomics software in use today would better equip the proteomics researcher to build effective workflows, which is the major purpose of this book. Nevertheless, the discussions of examples that are provided do highlight the considerations of importance when selecting software and of course when using the software in the proteomics experiment. It must be mentioned that Bessant has put together a very useful body of work, harnessing the expertise of over 35 contributing authors to cover a number of very relevant topics in the informatics arena of proteomics science. Some topics are more in-depth than others perhaps not as thorough as they ought to be. There is unavoidable overlap with limited inter-chapter connections. The book would have benefited from additional chapters describing the integration of proteomics data with other metadata experiments (i.e., metabolomics, lipidomics) and the unique bioinformatics challenges they present. Mass spectrometry imaging (MSI), a rapidly emerging and developing field, is not covered in much detail in the context of this book. The particulars of open source software in proteomics, along with protein identification and quantification, are overall, quite helpful. Readership recommendation: The target audience for this book includes scientists and doctoral students using proteomics science to understand biological systems. Given the interdisciplinary nature of proteomics, this book will be of benefit to and of interest to the bioanalytical chemist, biophysicist, biomedical engineer, biologist, and indeed the biostatistician. The book is constructed in such a manner that it includes enough introductory material for those new to proteome analysis, as well as enough depth and details for experts and specialists. No doubt, it offers a very useful fund of knowledge to the proteomics researcher. -- Taufika Islam Williams * Analytical and Bioanalytical Chemistry - Review part 3 * Internal standard features are then used to derive normalization factors that correct for sample loading disparities and ionization variabilities. Protein-level differential analysis encompasses processes to quantify proteins via constituent peptide analyses, as well as approaches to determine protein regulation disparities across study samples. MS2-based quantification, which exploits abundance data of fragment ions in tandem MS spectra, is then discussed by drawing comparisons between spectral counting and reporter ion-based quantification. Discussion then veers into the bioinformatics support for selected reaction monitoring (SRM), the gold standard for accurate, unambiguous MS-based quantification. The section concludes with a chapter on dataindependent acquisition (DIA), which primarily differs from data-dependent acquisition (DDA) in that the window selection of the first mass analyzer is dynamic during DDA, whereas it is used to scan the entire spectrum during DIA. Data analysis can be tricky in DIA and the chapter does justice in surveying DIA theory, notable DIA methods employed today, and major considerations in data interrogation. The third section details the open source software landscape for bioinformatics in proteomics investigations. A key consideration is data formatting, given the breadth of academic and commercial software that is commonly exercised for proteomics data management. The section proceeds to discuss three major software platforms for proteomics data analysis pipelines: OpenMS (modular solution for proteomics and metabolomics), Galaxy (originally designed for the genomics research community), and R (programming language for statistical computing and graphics). Section 4 takes the reader into the broader territory of integrating proteomics data with that from other studies, particularly genomics and transcriptomics. Proteogenomics, the application of proteomics data to augment genome annotation, does not quite offer the sensitivities featured by RNA-Seq and does exhibit particular bioinformatics challenges. Nevertheless, a major advantage of this field is the successful interrogation of proteins whose exact sequences are missing from generic databases to which they are matched and whose function may have critical bearings on biological phenotype. The authors detail underlying theory, software platforms, data formats, current challenges, and future direction. The section, and indeed the book, concludes with a discussion of the union between proteomics and transcriptomics data or proteome informed by transcriptomics (PIT). While PIT data can be used for genome annotations, the power behind this approach lies in facilitating proteomic analyses in the absence of a reference genome, not to mention the pinpointing of sequence variation and examining such dynamic events as isoform switching. In PIT, the protein database is created from RNA-Seq data. The authors elaborate PIT applications and data management options. Comparison with the existing literature: This book is distinctive in how it frames bioinformatics strictly in its relevance to designing a proteomics experiment. The authors draw upon only that portion of knowledge from key disciplines that intersect with proteomics to better construct sophisticated and robust informatics pipelines. In the last decade, a number of books have addressed bioinformatics as it relates to the rapidly developing field of proteomics, notably Bioinformatics for comparative proteomics edited by Cathy Wu and Chuming Chen (2010), Proteome bioinformatics edited by Simon Hubbard and Andrew Jones (2010), Bioinformatics of human proteomics edited by XiagdongWang (2013), Mass spectrometry data analysis in proteomics edited by Rune Matthiesen (2013), Bioinformatics: genomics and proteomics by Ruchi Singh (2015), Proteome bioinformatics edited by Shivakumar Keerthikumar and Suresh Mathivanan (2016), Exploring genomics, proteomics and bioinformatics by Charles Malkoff (2016), Modern proteomics-sample preparation, analysis and practical applications edited by Hamid Mirzaei and Martin Carrasco (2016), Protein bioinformatics edited by Cathy Wu, Cecilia Arighi and Karen Ross (2017). Some provide a bird's eye view of informatics as applied to proteomics. Some delve deeper into PTMs, while others focus on database searching aspects, cancer research, human proteins, or the interplay between gene expression and protein expression. Yet others center on proteomics while discussing informatics as a part of the whole experiment or explore specific MS-based methods and data analysis strategies. This book presents the advantage of elaborating important bioinformatics details, both at the user interface and behind the scenes (i.e., software algorithms), that should be carefully considered by the proteomics scientist in experimental design to better understand and interpret the data. Critical assessment: The book performs a thorough assessment of informatics processes and considerations in proteomics. Representative examples of informatics workflows are provided and discussed, but given the breadth of the subject, not all important bioinformatics software that is currently used in proteomics (i.e., Byonic (TM) by Protein Metrics) was able to receive attention. This is relevant because a detailed comparison of the inner workings of proteomics software in use today would better equip the proteomics researcher to build effective workflows, which is the major purpose of this book. Nevertheless, the discussions of examples that are provided do highlight the considerations of importance when selecting software and of course when using the software in the proteomics experiment. It must be mentioned that Bessant has put together a very useful body of work, harnessing the expertise of over 35 contributing authors to cover a number of very relevant topics in the informatics arena of proteomics science. Some topics are more in-depth than others perhaps not as thorough as they ought to be. There is unavoidable overlap with limited inter-chapter connections. The book would have benefited from additional chapters describing the integration of proteomics data with other metadata experiments (i.e., metabolomics, lipidomics) and the unique bioinformatics challenges they present. Mass spectrometry imaging (MSI), a rapidly emerging and developing field, is not covered in much detail in the context of this book. The particulars of open source software in proteomics, along with protein identification and quantification, are overall, quite helpful. Readership recommendation: The target audience for this book includes scientists and doctoral students using proteomics science to understand biological systems. Given the interdisciplinary nature of proteomics, this book will be of benefit to and of interest to the bioanalytical chemist, biophysicist, biomedical engineer, biologist, and indeed the biostatistician. The book is constructed in such a manner that it includes enough introductory material for those new to proteome analysis, as well as enough depth and details for experts and specialists. No doubt, it offers a very useful fund of knowledge to the proteomics researcher. Summary: Proteomics research is inherently multidisciplinary in its workflows, as it brings together concepts from chemistry, engineering, computer science, biochemistry, statistics, mathematics, and biology to understand protein expression. This is a timely book for the proteomics researcher in guiding decision trees involved in the informatics pipelines of this rapidly developing field. The book does an excellent job in focusing on that part of the informatics discipline, both at the user interface and behind the scenes algorithms, that is of great importance to developing innovative and effective methods for protein interrogation. Informatics is placed squarely within the framework of proteomics and this will be most beneficial indeed for the target audience. -- Taufika Islam Williams * Analytical and Bioanalytical Chemistry - Review part 2 *

This is a timely book for the proteomics researcher in guiding decision trees involved in the informatics pipelines of this rapidly developing field. The book does an excellent job in focusing on that part of the informatics discipline, both at the user interface and behind the scenes algorithms, that is of great importance to developing innovative and effective methods for protein interrogation. -- Taufika Islam Williams * Analytical and Bioanalytical Chemistry * Book’s topic: Proteomics, the comprehensive interrogation of proteins expressed by a living system, has enjoyed expeditious growth and development in recent years, as it brings together a range of informatics themes that fortify and support the everincreasing power of LC-MS/MS platforms to tackle important biological questions. Proteins are the vehicles of change in living cells and understanding them is elemental to understanding molecular biology. The complexity of the proteomics workflow, from sample preparation to LC-MS/MS to bioinformatics analyses, is such thatmore often than not, the intricacies and indeed shortcomings of the bioinformatics software are not carefully considered during data interpretation. This is an unwelcome prospect, given that comprehending the inner workings of living systems can be intimately tied to fluctuating patterns of protein expression,which can only be as thoroughly understood as the cumulative proteomics experiment allows. State-of-the-art sample preparation and LC-MS/MS will only be as biologically informative as the informatics methods with which data are interrogated. Proteome informatics is described as the ever increasing collection of bioinformatics methodologies that can be exercised in the analysis of protein expression. The book Proteome informatics, edited byConradBessant and the 5th volume of the Royal Society of Chemistry on New Developments in Mass Spectrometry, describes the bioinformatics of proteome analyses in the very context of proteomics workflows. It is an opportune discussion by leading experts on the current state of this evolving discipline, highlighting the essential fund of knowledge that will enable the proteomics expert, who may or may not be well-versed in computer science or statistics, to exploit and construct algorithms that can effectively interrogate gigabytes of data, while keeping a sharp focus on the limitations of what such software can reasonably underscore about the system being studied. Contents: This book is divided into four main sections, which follow an introductory chapter on proteome informatics. The first section describes protein identification and begins with manual de novo sequencing to more sophisticated de novo algorithms. The book steers into details of peptide spectrum matching by database search and the alternative spectral library search in use today. Despite the established advantages of the latter, the approach is only as good as the population of the library itself, which invariably limits the identification of experimental peptides and their post-translational modifications (PTMs). Discussion proceeds into peptide-spectrum match (PSM) scoring and validation, a lynchpin of proteome informatics which unequivocally dictates the “goodness of fit” in a given peptide (and subsequently protein) identification. Merits and demerits of common methods are briefly explored. This is proceeded by a chapter on protein grouping, which links identified peptides to identifying proteins. The section concludes with commentary on identification and positioning of the all-important PTMs. Indeed, the hundreds of in vivo PTMs (not to mention the many more possibilities of chemical modifications that may be artificially introduced into the system under investigation) are subject to change with changing cellular milieu, and hence are critical in a comprehensive proteomics study. The second section is dedicated to the quantification of proteins. Algorithms detailing MS1-based quantification are examined in its five components. The central point for such algorithms is the detection and quantification of peptidespecific signal patterns, called features. Peptide- and protein level identification are effected using precursor ion exact mass, charge state, and tandem MS. Chromatographic alignment fine-tunes all runs to a common retention time (RT) coordinate system such that corresponding features will display analogous RTs. -- Taufika Islam Williams * Analytical and Bioanalytical Chemistry - Review part 1 * Internal standard features are then used to derive normalization factors that correct for sample loading disparities and ionization variabilities. Protein-level differential analysis encompasses processes to quantify proteins via constituent peptide analyses, as well as approaches to determine protein regulation disparities across study samples. MS2-based quantification, which exploits abundance data of fragment ions in tandem MS spectra, is then discussed by drawing comparisons between spectral counting and reporter ion-based quantification. Discussion then veers into the bioinformatics support for selected reaction monitoring (SRM), the gold standard for accurate, unambiguous MS-based quantification. The section concludes with a chapter on dataindependent acquisition (DIA), which primarily differs from data-dependent acquisition (DDA) in that the window selection of the first mass analyzer is dynamic during DDA, whereas it is used to scan the entire spectrum during DIA. Data analysis can be tricky in DIA and the chapter does justice in surveying DIA theory, notable DIA methods employed today, and major considerations in data interrogation. The third section details the open source software landscape for bioinformatics in proteomics investigations. A key consideration is data formatting, given the breadth of academic and commercial software that is commonly exercised for proteomics data management. The section proceeds to discuss three major software platforms for proteomics data analysis pipelines: OpenMS (modular solution for proteomics and metabolomics), Galaxy (originally designed for the genomics research community), and R (programming language for statistical computing and graphics). Section 4 takes the reader into the broader territory of integrating proteomics data with that from other studies, particularly genomics and transcriptomics. Proteogenomics, the application of proteomics data to augment genome annotation, does not quite offer the sensitivities featured by RNA-Seq and does exhibit particular bioinformatics challenges. Nevertheless, a major advantage of this field is the successful interrogation of proteins whose exact sequences are missing from generic databases to which they are matched and whose function may have critical bearings on biological phenotype. The authors detail underlying theory, software platforms, data formats, current challenges, and future direction. The section, and indeed the book, concludes with a discussion of the union between proteomics and transcriptomics data or proteome informed by transcriptomics (PIT). While PIT data can be used for genome annotations, the power behind this approach lies in facilitating proteomic analyses in the absence of a reference genome, not to mention the pinpointing of sequence variation and examining such dynamic events as isoform switching. In PIT, the protein database is created from RNA-Seq data. The authors elaborate PIT applications and data management options. Comparison with the existing literature: This book is distinctive in how it frames bioinformatics strictly in its relevance to designing a proteomics experiment. The authors draw upon only that portion of knowledge from key disciplines that intersect with proteomics to better construct sophisticated and robust informatics pipelines. In the last decade, a number of books have addressed bioinformatics as it relates to the rapidly developing field of proteomics, notably Bioinformatics for comparative proteomics edited by Cathy Wu and Chuming Chen (2010), Proteome bioinformatics edited by Simon Hubbard and Andrew Jones (2010), Bioinformatics of human proteomics edited by XiagdongWang (2013), Mass spectrometry data analysis in proteomics edited by Rune Matthiesen (2013), Bioinformatics: genomics and proteomics by Ruchi Singh (2015), Proteome bioinformatics edited by Shivakumar Keerthikumar and Suresh Mathivanan (2016), Exploring genomics, proteomics and bioinformatics by Charles Malkoff (2016), Modern proteomics—sample preparation, analysis and practical applications edited by Hamid Mirzaei and Martin Carrasco (2016), Protein bioinformatics edited by Cathy Wu, Cecilia Arighi and Karen Ross (2017). Some provide a bird’s eye view of informatics as applied to proteomics. Some delve deeper into PTMs, while others focus on database searching aspects, cancer research, human proteins, or the interplay between gene expression and protein expression. Yet others center on proteomics while discussing informatics as a part of the whole experiment or explore specific MS-based methods and data analysis strategies. This book presents the advantage of elaborating important bioinformatics details, both at the user interface and behind the scenes (i.e., software algorithms), that should be carefully considered by the proteomics scientist in experimental design to better understand and interpret the data. Critical assessment: The book performs a thorough assessment of informatics processes and considerations in proteomics. Representative examples of informatics workflows are provided and discussed, but given the breadth of the subject, not all important bioinformatics software that is currently used in proteomics (i.e., Byonic™ by Protein Metrics) was able to receive attention. This is relevant because a detailed comparison of the inner workings of proteomics software in use today would better equip the proteomics researcher to build effective workflows, which is the major purpose of this book. Nevertheless, the discussions of examples that are provided do highlight the considerations of importance when selecting software and of course when using the software in the proteomics experiment. It must be mentioned that Bessant has put together a very useful body of work, harnessing the expertise of over 35 contributing authors to cover a number of very relevant topics in the informatics arena of proteomics science. Some topics are more in-depth than others perhaps not as thorough as they ought to be. There is unavoidable overlap with limited inter-chapter connections. The book would have benefited from additional chapters describing the integration of proteomics data with other metadata experiments (i.e., metabolomics, lipidomics) and the unique bioinformatics challenges they present. Mass spectrometry imaging (MSI), a rapidly emerging and developing field, is not covered in much detail in the context of this book. The particulars of open source software in proteomics, along with protein identification and quantification, are overall, quite helpful. Readership recommendation: The target audience for this book includes scientists and doctoral students using proteomics science to understand biological systems. Given the interdisciplinary nature of proteomics, this book will be of benefit to and of interest to the bioanalytical chemist, biophysicist, biomedical engineer, biologist, and indeed the biostatistician. The book is constructed in such a manner that it includes enough introductory material for those new to proteome analysis, as well as enough depth and details for experts and specialists. No doubt, it offers a very useful fund of knowledge to the proteomics researcher. Summary: Proteomics research is inherently multidisciplinary in its workflows, as it brings together concepts from chemistry, engineering, computer science, biochemistry, statistics, mathematics, and biology to understand protein expression. This is a timely book for the proteomics researcher in guiding decision trees involved in the informatics pipelines of this rapidly developing field. The book does an excellent job in focusing on that part of the informatics discipline, both at the user interface and behind the scenes algorithms, that is of great importance to developing innovative and effective methods for protein interrogation. Informatics is placed squarely within the framework of proteomics and this will be most beneficial indeed for the target audience. -- Taufika Islam Williams * Analytical and Bioanalytical Chemistry - Review part 2 * by Charles Malkoff (2016), Modern proteomics—sample preparation, analysis and practical applications edited by Hamid Mirzaei and Martin Carrasco (2016), Protein bioinformatics edited by Cathy Wu, Cecilia Arighi and Karen Ross (2017). Some provide a bird’s eye view of informatics as applied to proteomics. Some delve deeper into PTMs, while others focus on database searching aspects, cancer research, human proteins, or the interplay between gene expression and protein expression. Yet others center on proteomics while discussing informatics as a part of the whole experiment or explore specific MS-based methods and data analysis strategies. This book presents the advantage of elaborating important bioinformatics details, both at the user interface and behind the scenes (i.e., software algorithms), that should be carefully considered by the proteomics scientist in experimental design to better understand and interpret the data. Critical assessment: The book performs a thorough assessment of informatics processes and considerations in proteomics. Representative examples of informatics workflows are provided and discussed, but given the breadth of the subject, not all important bioinformatics software that is currently used in proteomics (i.e., Byonic™ by Protein Metrics) was able to receive attention. This is relevant because a detailed comparison of the inner workings of proteomics software in use today would better equip the proteomics researcher to build effective workflows, which is the major purpose of this book. Nevertheless, the discussions of examples that are provided do highlight the considerations of importance when selecting software and of course when using the software in the proteomics experiment. It must be mentioned that Bessant has put together a very useful body of work, harnessing the expertise of over 35 contributing authors to cover a number of very relevant topics in the informatics arena of proteomics science. Some topics are more in-depth than others perhaps not as thorough as they ought to be. There is unavoidable overlap with limited inter-chapter connections. The book would have benefited from additional chapters describing the integration of proteomics data with other metadata experiments (i.e., metabolomics, lipidomics) and the unique bioinformatics challenges they present. Mass spectrometry imaging (MSI), a rapidly emerging and developing field, is not covered in much detail in the context of this book. The particulars of open source software in proteomics, along with protein identification and quantification, are overall, quite helpful. Readership recommendation: The target audience for this book includes scientists and doctoral students using proteomics science to understand biological systems. Given the interdisciplinary nature of proteomics, this book will be of benefit to and of interest to the bioanalytical chemist, biophysicist, biomedical engineer, biologist, and indeed the biostatistician. The book is constructed in such a manner that it includes enough introductory material for those new to proteome analysis, as well as enough depth and details for experts and specialists. No doubt, it offers a very useful fund of knowledge to the proteomics researcher. -- Taufika Islam Williams * Analytical and Bioanalytical Chemistry - Review part 3 *

This is a timely book for the proteomics researcher in guiding decision trees involved in the informatics pipelines of this rapidly developing field. The book does an excellent job in focusing on that part of the informatics discipline, both at the user interface and behind the scenes algorithms, that is of great importance to developing innovative and effective methods for protein interrogation. * Analytical and Bioanalytical Chemistry *

Book's topic: Proteomics, the comprehensive interrogation of proteins expressed by a living system, has enjoyed expeditious growth and development in recent years, as it brings together a range of informatics themes that fortify and support the everincreasing power of LC-MS/MS platforms to tackle important biological questions. Proteins are the vehicles of change in living cells and understanding them is elemental to understanding molecular biology. The complexity of the proteomics workflow, from sample preparation to LC-MS/MS to bioinformatics analyses, is such thatmore often than not, the intricacies and indeed shortcomings of the bioinformatics software are not carefully considered during data interpretation. This is an unwelcome prospect, given that comprehending the inner workings of living systems can be intimately tied to fluctuating patterns of protein expression,which can only be as thoroughly understood as the cumulative proteomics experiment allows. State-of-the-art sample preparation and LC-MS/MS will only be as biologically informative as the informatics methods with which data are interrogated. Proteome informatics is described as the ever increasing collection of bioinformatics methodologies that can be exercised in the analysis of protein expression. The book Proteome informatics, edited byConradBessant and the 5th volume of the Royal Society of Chemistry on New Developments in Mass Spectrometry, describes the bioinformatics of proteome analyses in the very context of proteomics workflows. It is an opportune discussion by leading experts on the current state of this evolving discipline, highlighting the essential fund of knowledge that will enable the proteomics expert, who may or may not be well-versed in computer science or statistics, to exploit and construct algorithms that can effectively interrogate gigabytes of data, while keeping a sharp focus on the limitations of what such software can reasonably underscore about the system being studied. Contents: This book is divided into four main sections, which follow an introductory chapter on proteome informatics. The first section describes protein identification and begins with manual de novo sequencing to more sophisticated de novo algorithms. The book steers into details of peptide spectrum matching by database search and the alternative spectral library search in use today. Despite the established advantages of the latter, the approach is only as good as the population of the library itself, which invariably limits the identification of experimental peptides and their post-translational modifications (PTMs). Discussion proceeds into peptide-spectrum match (PSM) scoring and validation, a lynchpin of proteome informatics which unequivocally dictates the goodness of fit in a given peptide (and subsequently protein) identification. Merits and demerits of common methods are briefly explored. This is proceeded by a chapter on protein grouping, which links identified peptides to identifying proteins. The section concludes with commentary on identification and positioning of the all-important PTMs. Indeed, the hundreds of in vivo PTMs (not to mention the many more possibilities of chemical modifications that may be artificially introduced into the system under investigation) are subject to change with changing cellular milieu, and hence are critical in a comprehensive proteomics study. The second section is dedicated to the quantification of proteins. Algorithms detailing MS1-based quantification are examined in its five components. The central point for such algorithms is the detection and quantification of peptidespecific signal patterns, called features. Peptide- and protein level identification are effected using precursor ion exact mass, charge state, and tandem MS. Chromatographic alignment fine-tunes all runs to a common retention time (RT) coordinate system such that corresponding features will display analogous RTs. -- Taufika Islam Williams * Analytical and Bioanalytical Chemistry - Review part 1 * This is a timely book for the proteomics researcher in guiding decision trees involved in the informatics pipelines of this rapidly developing field. The book does an excellent job in focusing on that part of the informatics discipline, both at the user interface and behind the scenes algorithms, that is of great importance to developing innovative and effective methods for protein interrogation. -- Taufika Islam Williams * Analytical and Bioanalytical Chemistry * Internal standard features are then used to derive normalization factors that correct for sample loading disparities and ionization variabilities. Protein-level differential analysis encompasses processes to quantify proteins via constituent peptide analyses, as well as approaches to determine protein regulation disparities across study samples. MS2-based quantification, which exploits abundance data of fragment ions in tandem MS spectra, is then discussed by drawing comparisons between spectral counting and reporter ion-based quantification. Discussion then veers into the bioinformatics support for selected reaction monitoring (SRM), the gold standard for accurate, unambiguous MS-based quantification. The section concludes with a chapter on dataindependent acquisition (DIA), which primarily differs from data-dependent acquisition (DDA) in that the window selection of the first mass analyzer is dynamic during DDA, whereas it is used to scan the entire spectrum during DIA. Data analysis can be tricky in DIA and the chapter does justice in surveying DIA theory, notable DIA methods employed today, and major considerations in data interrogation. The third section details the open source software landscape for bioinformatics in proteomics investigations. A key consideration is data formatting, given the breadth of academic and commercial software that is commonly exercised for proteomics data management. The section proceeds to discuss three major software platforms for proteomics data analysis pipelines: OpenMS (modular solution for proteomics and metabolomics), Galaxy (originally designed for the genomics research community), and R (programming language for statistical computing and graphics). Section 4 takes the reader into the broader territory of integrating proteomics data with that from other studies, particularly genomics and transcriptomics. Proteogenomics, the application of proteomics data to augment genome annotation, does not quite offer the sensitivities featured by RNA-Seq and does exhibit particular bioinformatics challenges. Nevertheless, a major advantage of this field is the successful interrogation of proteins whose exact sequences are missing from generic databases to which they are matched and whose function may have critical bearings on biological phenotype. The authors detail underlying theory, software platforms, data formats, current challenges, and future direction. The section, and indeed the book, concludes with a discussion of the union between proteomics and transcriptomics data or proteome informed by transcriptomics (PIT). While PIT data can be used for genome annotations, the power behind this approach lies in facilitating proteomic analyses in the absence of a reference genome, not to mention the pinpointing of sequence variation and examining such dynamic events as isoform switching. In PIT, the protein database is created from RNA-Seq data. The authors elaborate PIT applications and data management options. Comparison with the existing literature: This book is distinctive in how it frames bioinformatics strictly in its relevance to designing a proteomics experiment. The authors draw upon only that portion of knowledge from key disciplines that intersect with proteomics to better construct sophisticated and robust informatics pipelines. In the last decade, a number of books have addressed bioinformatics as it relates to the rapidly developing field of proteomics, notably Bioinformatics for comparative proteomics edited by Cathy Wu and Chuming Chen (2010), Proteome bioinformatics edited by Simon Hubbard and Andrew Jones (2010), Bioinformatics of human proteomics edited by XiagdongWang (2013), Mass spectrometry data analysis in proteomics edited by Rune Matthiesen (2013), Bioinformatics: genomics and proteomics by Ruchi Singh (2015), Proteome bioinformatics edited by Shivakumar Keerthikumar and Suresh Mathivanan (2016), Exploring genomics, proteomics and bioinformatics by Charles Malkoff (2016), Modern proteomics-sample preparation, analysis and practical applications edited by Hamid Mirzaei and Martin Carrasco (2016), Protein bioinformatics edited by Cathy Wu, Cecilia Arighi and Karen Ross (2017). Some provide a bird's eye view of informatics as applied to proteomics. Some delve deeper into PTMs, while others focus on database searching aspects, cancer research, human proteins, or the interplay between gene expression and protein expression. Yet others center on proteomics while discussing informatics as a part of the whole experiment or explore specific MS-based methods and data analysis strategies. This book presents the advantage of elaborating important bioinformatics details, both at the user interface and behind the scenes (i.e., software algorithms), that should be carefully considered by the proteomics scientist in experimental design to better understand and interpret the data. Critical assessment: The book performs a thorough assessment of informatics processes and considerations in proteomics. Representative examples of informatics workflows are provided and discussed, but given the breadth of the subject, not all important bioinformatics software that is currently used in proteomics (i.e., Byonic (TM) by Protein Metrics) was able to receive attention. This is relevant because a detailed comparison of the inner workings of proteomics software in use today would better equip the proteomics researcher to build effective workflows, which is the major purpose of this book. Nevertheless, the discussions of examples that are provided do highlight the considerations of importance when selecting software and of course when using the software in the proteomics experiment. It must be mentioned that Bessant has put together a very useful body of work, harnessing the expertise of over 35 contributing authors to cover a number of very relevant topics in the informatics arena of proteomics science. Some topics are more in-depth than others perhaps not as thorough as they ought to be. There is unavoidable overlap with limited inter-chapter connections. The book would have benefited from additional chapters describing the integration of proteomics data with other metadata experiments (i.e., metabolomics, lipidomics) and the unique bioinformatics challenges they present. Mass spectrometry imaging (MSI), a rapidly emerging and developing field, is not covered in much detail in the context of this book. The particulars of open source software in proteomics, along with protein identification and quantification, are overall, quite helpful. Readership recommendation: The target audience for this book includes scientists and doctoral students using proteomics science to understand biological systems. Given the interdisciplinary nature of proteomics, this book will be of benefit to and of interest to the bioanalytical chemist, biophysicist, biomedical engineer, biologist, and indeed the biostatistician. The book is constructed in such a manner that it includes enough introductory material for those new to proteome analysis, as well as enough depth and details for experts and specialists. No doubt, it offers a very useful fund of knowledge to the proteomics researcher. Summary: Proteomics research is inherently multidisciplinary in its workflows, as it brings together concepts from chemistry, engineering, computer science, biochemistry, statistics, mathematics, and biology to understand protein expression. This is a timely book for the proteomics researcher in guiding decision trees involved in the informatics pipelines of this rapidly developing field. The book does an excellent job in focusing on that part of the informatics discipline, both at the user interface and behind the scenes algorithms, that is of great importance to developing innovative and effective methods for protein interrogation. Informatics is placed squarely within the framework of proteomics and this will be most beneficial indeed for the target audience. -- Taufika Islam Williams * Analytical and Bioanalytical Chemistry - Review part 2 * by Charles Malkoff (2016), Modern proteomics-sample preparation, analysis and practical applications edited by Hamid Mirzaei and Martin Carrasco (2016), Protein bioinformatics edited by Cathy Wu, Cecilia Arighi and Karen Ross (2017). Some provide a bird's eye view of informatics as applied to proteomics. Some delve deeper into PTMs, while others focus on database searching aspects, cancer research, human proteins, or the interplay between gene expression and protein expression. Yet others center on proteomics while discussing informatics as a part of the whole experiment or explore specific MS-based methods and data analysis strategies. This book presents the advantage of elaborating important bioinformatics details, both at the user interface and behind the scenes (i.e., software algorithms), that should be carefully considered by the proteomics scientist in experimental design to better understand and interpret the data. Critical assessment: The book performs a thorough assessment of informatics processes and considerations in proteomics. Representative examples of informatics workflows are provided and discussed, but given the breadth of the subject, not all important bioinformatics software that is currently used in proteomics (i.e., Byonic (TM) by Protein Metrics) was able to receive attention. This is relevant because a detailed comparison of the inner workings of proteomics software in use today would better equip the proteomics researcher to build effective workflows, which is the major purpose of this book. Nevertheless, the discussions of examples that are provided do highlight the considerations of importance when selecting software and of course when using the software in the proteomics experiment. It must be mentioned that Bessant has put together a very useful body of work, harnessing the expertise of over 35 contributing authors to cover a number of very relevant topics in the informatics arena of proteomics science. Some topics are more in-depth than others perhaps not as thorough as they ought to be. There is unavoidable overlap with limited inter-chapter connections. The book would have benefited from additional chapters describing the integration of proteomics data with other metadata experiments (i.e., metabolomics, lipidomics) and the unique bioinformatics challenges they present. Mass spectrometry imaging (MSI), a rapidly emerging and developing field, is not covered in much detail in the context of this book. The particulars of open source software in proteomics, along with protein identification and quantification, are overall, quite helpful. Readership recommendation: The target audience for this book includes scientists and doctoral students using proteomics science to understand biological systems. Given the interdisciplinary nature of proteomics, this book will be of benefit to and of interest to the bioanalytical chemist, biophysicist, biomedical engineer, biologist, and indeed the biostatistician. The book is constructed in such a manner that it includes enough introductory material for those new to proteome analysis, as well as enough depth and details for experts and specialists. No doubt, it offers a very useful fund of knowledge to the proteomics researcher. -- Taufika Islam Williams * Analytical and Bioanalytical Chemistry - Review part 3 *

Book’s topic: Proteomics, the comprehensive interrogation of proteins expressed by a living system, has enjoyed expeditious growth and development in recent years, as it brings together a range of informatics themes that fortify and support the everincreasing power of LC-MS/MS platforms to tackle important biological questions. Proteins are the vehicles of change in living cells and understanding them is elemental to understanding molecular biology. The complexity of the proteomics workflow, from sample preparation to LC-MS/MS to bioinformatics analyses, is such thatmore often than not, the intricacies and indeed shortcomings of the bioinformatics software are not carefully considered during data interpretation. This is an unwelcome prospect, given that comprehending the inner workings of living systems can be intimately tied to fluctuating patterns of protein expression,which can only be as thoroughly understood as the cumulative proteomics experiment allows. State-of-the-art sample preparation and LC-MS/MS will only be as biologically informative as the informatics methods with which data are interrogated. Proteome informatics is described as the ever increasing collection of bioinformatics methodologies that can be exercised in the analysis of protein expression. The book Proteome informatics, edited byConradBessant and the 5th volume of the Royal Society of Chemistry on New Developments in Mass Spectrometry, describes the bioinformatics of proteome analyses in the very context of proteomics workflows. It is an opportune discussion by leading experts on the current state of this evolving discipline, highlighting the essential fund of knowledge that will enable the proteomics expert, who may or may not be well-versed in computer science or statistics, to exploit and construct algorithms that can effectively interrogate gigabytes of data, while keeping a sharp focus on the limitations of what such software can reasonably underscore about the system being studied. Contents: This book is divided into four main sections, which follow an introductory chapter on proteome informatics. The first section describes protein identification and begins with manual de novo sequencing to more sophisticated de novo algorithms. The book steers into details of peptide spectrum matching by database search and the alternative spectral library search in use today. Despite the established advantages of the latter, the approach is only as good as the population of the library itself, which invariably limits the identification of experimental peptides and their post-translational modifications (PTMs). Discussion proceeds into peptide-spectrum match (PSM) scoring and validation, a lynchpin of proteome informatics which unequivocally dictates the “goodness of fit” in a given peptide (and subsequently protein) identification. Merits and demerits of common methods are briefly explored. This is proceeded by a chapter on protein grouping, which links identified peptides to identifying proteins. The section concludes with commentary on identification and positioning of the all-important PTMs. Indeed, the hundreds of in vivo PTMs (not to mention the many more possibilities of chemical modifications that may be artificially introduced into the system under investigation) are subject to change with changing cellular milieu, and hence are critical in a comprehensive proteomics study. The second section is dedicated to the quantification of proteins. Algorithms detailing MS1-based quantification are examined in its five components. The central point for such algorithms is the detection and quantification of peptidespecific signal patterns, called features. Peptide- and protein level identification are effected using precursor ion exact mass, charge state, and tandem MS. Chromatographic alignment fine-tunes all runs to a common retention time (RT) coordinate system such that corresponding features will display analogous RTs. * Analytical and Bioanalytical Chemistry - Review part 1 * Internal standard features are then used to derive normalization factors that correct for sample loading disparities and ionization variabilities. Protein-level differential analysis encompasses processes to quantify proteins via constituent peptide analyses, as well as approaches to determine protein regulation disparities across study samples. MS2-based quantification, which exploits abundance data of fragment ions in tandem MS spectra, is then discussed by drawing comparisons between spectral counting and reporter ion-based quantification. Discussion then veers into the bioinformatics support for selected reaction monitoring (SRM), the gold standard for accurate, unambiguous MS-based quantification. The section concludes with a chapter on dataindependent acquisition (DIA), which primarily differs from data-dependent acquisition (DDA) in that the window selection of the first mass analyzer is dynamic during DDA, whereas it is used to scan the entire spectrum during DIA. Data analysis can be tricky in DIA and the chapter does justice in surveying DIA theory, notable DIA methods employed today, and major considerations in data interrogation. The third section details the open source software landscape for bioinformatics in proteomics investigations. A key consideration is data formatting, given the breadth of academic and commercial software that is commonly exercised for proteomics data management. The section proceeds to discuss three major software platforms for proteomics data analysis pipelines: OpenMS (modular solution for proteomics and metabolomics), Galaxy (originally designed for the genomics research community), and R (programming language for statistical computing and graphics). Section 4 takes the reader into the broader territory of integrating proteomics data with that from other studies, particularly genomics and transcriptomics. Proteogenomics, the application of proteomics data to augment genome annotation, does not quite offer the sensitivities featured by RNA-Seq and does exhibit particular bioinformatics challenges. Nevertheless, a major advantage of this field is the successful interrogation of proteins whose exact sequences are missing from generic databases to which they are matched and whose function may have critical bearings on biological phenotype. The authors detail underlying theory, software platforms, data formats, current challenges, and future direction. The section, and indeed the book, concludes with a discussion of the union between proteomics and transcriptomics data or proteome informed by transcriptomics (PIT). While PIT data can be used for genome annotations, the power behind this approach lies in facilitating proteomic analyses in the absence of a reference genome, not to mention the pinpointing of sequence variation and examining such dynamic events as isoform switching. In PIT, the protein database is created from RNA-Seq data. The authors elaborate PIT applications and data management options. Comparison with the existing literature: This book is distinctive in how it frames bioinformatics strictly in its relevance to designing a proteomics experiment. The authors draw upon only that portion of knowledge from key disciplines that intersect with proteomics to better construct sophisticated and robust informatics pipelines. In the last decade, a number of books have addressed bioinformatics as it relates to the rapidly developing field of proteomics, notably Bioinformatics for comparative proteomics edited by Cathy Wu and Chuming Chen (2010), Proteome bioinformatics edited by Simon Hubbard and Andrew Jones (2010), Bioinformatics of human proteomics edited by XiagdongWang (2013), Mass spectrometry data analysis in proteomics edited by Rune Matthiesen (2013), Bioinformatics: genomics and proteomics by Ruchi Singh (2015), Proteome bioinformatics edited by Shivakumar Keerthikumar and Suresh Mathivanan (2016), Exploring genomics, proteomics and bioinformatics by Charles Malkoff (2016), Modern proteomics—sample preparation, analysis and practical applications edited by Hamid Mirzaei and Martin Carrasco (2016), Protein bioinformatics edited by Cathy Wu, Cecilia Arighi and Karen Ross (2017). Some provide a bird’s eye view of informatics as applied to proteomics. Some delve deeper into PTMs, while others focus on database searching aspects, cancer research, human proteins, or the interplay between gene expression and protein expression. Yet others center on proteomics while discussing informatics as a part of the whole experiment or explore specific MS-based methods and data analysis strategies. This book presents the advantage of elaborating important bioinformatics details, both at the user interface and behind the scenes (i.e., software algorithms), that should be carefully considered by the proteomics scientist in experimental design to better understand and interpret the data. Critical assessment: The book performs a thorough assessment of informatics processes and considerations in proteomics. Representative examples of informatics workflows are provided and discussed, but given the breadth of the subject, not all important bioinformatics software that is currently used in proteomics (i.e., Byonic™ by Protein Metrics) was able to receive attention. This is relevant because a detailed comparison of the inner workings of proteomics software in use today would better equip the proteomics researcher to build effective workflows, which is the major purpose of this book. Nevertheless, the discussions of examples that are provided do highlight the considerations of importance when selecting software and of course when using the software in the proteomics experiment. It must be mentioned that Bessant has put together a very useful body of work, harnessing the expertise of over 35 contributing authors to cover a number of very relevant topics in the informatics arena of proteomics science. Some topics are more in-depth than others perhaps not as thorough as they ought to be. There is unavoidable overlap with limited inter-chapter connections. The book would have benefited from additional chapters describing the integration of proteomics data with other metadata experiments (i.e., metabolomics, lipidomics) and the unique bioinformatics challenges they present. Mass spectrometry imaging (MSI), a rapidly emerging and developing field, is not covered in much detail in the context of this book. The particulars of open source software in proteomics, along with protein identification and quantification, are overall, quite helpful. Readership recommendation: The target audience for this book includes scientists and doctoral students using proteomics science to understand biological systems. Given the interdisciplinary nature of proteomics, this book will be of benefit to and of interest to the bioanalytical chemist, biophysicist, biomedical engineer, biologist, and indeed the biostatistician. The book is constructed in such a manner that it includes enough introductory material for those new to proteome analysis, as well as enough depth and details for experts and specialists. No doubt, it offers a very useful fund of knowledge to the proteomics researcher. Summary: Proteomics research is inherently multidisciplinary in its workflows, as it brings together concepts from chemistry, engineering, computer science, biochemistry, statistics, mathematics, and biology to understand protein expression. This is a timely book for the proteomics researcher in guiding decision trees involved in the informatics pipelines of this rapidly developing field. The book does an excellent job in focusing on that part of the informatics discipline, both at the user interface and behind the scenes algorithms, that is of great importance to developing innovative and effective methods for protein interrogation. Informatics is placed squarely within the framework of proteomics and this will be most beneficial indeed for the target audience. * Analytical and Bioanalytical Chemistry - Review part 2 * by Charles Malkoff (2016), Modern proteomics—sample preparation, analysis and practical applications edited by Hamid Mirzaei and Martin Carrasco (2016), Protein bioinformatics edited by Cathy Wu, Cecilia Arighi and Karen Ross (2017). Some provide a bird’s eye view of informatics as applied to proteomics. Some delve deeper into PTMs, while others focus on database searching aspects, cancer research, human proteins, or the interplay between gene expression and protein expression. Yet others center on proteomics while discussing informatics as a part of the whole experiment or explore specific MS-based methods and data analysis strategies. This book presents the advantage of elaborating important bioinformatics details, both at the user interface and behind the scenes (i.e., software algorithms), that should be carefully considered by the proteomics scientist in experimental design to better understand and interpret the data. Critical assessment: The book performs a thorough assessment of informatics processes and considerations in proteomics. Representative examples of informatics workflows are provided and discussed, but given the breadth of the subject, not all important bioinformatics software that is currently used in proteomics (i.e., Byonic™ by Protein Metrics) was able to receive attention. This is relevant because a detailed comparison of the inner workings of proteomics software in use today would better equip the proteomics researcher to build effective workflows, which is the major purpose of this book. Nevertheless, the discussions of examples that are provided do highlight the considerations of importance when selecting software and of course when using the software in the proteomics experiment. It must be mentioned that Bessant has put together a very useful body of work, harnessing the expertise of over 35 contributing authors to cover a number of very relevant topics in the informatics arena of proteomics science. Some topics are more in-depth than others perhaps not as thorough as they ought to be. There is unavoidable overlap with limited inter-chapter connections. The book would have benefited from additional chapters describing the integration of proteomics data with other metadata experiments (i.e., metabolomics, lipidomics) and the unique bioinformatics challenges they present. Mass spectrometry imaging (MSI), a rapidly emerging and developing field, is not covered in much detail in the context of this book. The particulars of open source software in proteomics, along with protein identification and quantification, are overall, quite helpful. Readership recommendation: The target audience for this book includes scientists and doctoral students using proteomics science to understand biological systems. Given the interdisciplinary nature of proteomics, this book will be of benefit to and of interest to the bioanalytical chemist, biophysicist, biomedical engineer, biologist, and indeed the biostatistician. The book is constructed in such a manner that it includes enough introductory material for those new to proteome analysis, as well as enough depth and details for experts and specialists. No doubt, it offers a very useful fund of knowledge to the proteomics researcher. * Analytical and Bioanalytical Chemistry - Review part 3 * This is a timely book for the proteomics researcher in guiding decision trees involved in the informatics pipelines of this rapidly developing field. The book does an excellent job in focusing on that part of the informatics discipline, both at the user interface and behind the scenes algorithms, that is of great importance to developing innovative and effective methods for protein interrogation. * Analytical and Bioanalytical Chemistry *

Author Information

Conrad Bessant is Professor of Bioinformatics at Queen Mary University of London. He has particular interests in proteomics, software development and machine learning and is striving to ensure that everyone using proteomics data can access the latest analysis methods and knows how to use them in the most effective way.

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