Development of Algorithms for Mass Spectrometry Based Proteomics PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Development of Algorithms for Mass Spectrometry Based Proteomics PDF full book. Access full book title Development of Algorithms for Mass Spectrometry Based Proteomics by Lukas Reiter. Download full books in PDF and EPUB format.
Author: Lukas Reiter
Publisher:
ISBN:
Category :
Languages : en
Pages :
Get Book Here
Book Description
Author: Lukas Reiter
Publisher:
ISBN:
Category :
Languages : en
Pages :
Get Book Here
Book Description
Author: Fahad Saeed
Publisher: Springer Nature
ISBN: 3031019601
Category : Science
Languages : en
Pages : 146
Get Book Here
Book Description
To date, processing of high-throughput Mass Spectrometry (MS) data is accomplished using serial algorithms. Developing new methods to process MS data is an active area of research but there is no single strategy that focuses on scalability of MS based methods. Mass spectrometry is a diverse and versatile technology for high-throughput functional characterization of proteins, small molecules and metabolites in complex biological mixtures. In the recent years the technology has rapidly evolved and is now capable of generating increasingly large (multiple tera-bytes per experiment) and complex (multiple species/microbiome/high-dimensional) data sets. This rapid advance in MS instrumentation must be matched by equally fast and rapid evolution of scalable methods developed for analysis of these complex data sets. Ideally, the new methods should leverage the rich heterogeneous computational resources available in a ubiquitous fashion in the form of multicore, manycore, CPU-GPU, CPU-FPGA, and IntelPhi architectures. The absence of these high-performance computing algorithms now hinders scientific advancements for mass spectrometry research. In this book we illustrate the need for high-performance computing algorithms for MS based proteomics, and proteogenomics and showcase our progress in developing these high-performance algorithms.
Author: Conrad Bessant
Publisher: Royal Society of Chemistry
ISBN: 1782626735
Category : Science
Languages : en
Pages : 429
Get Book Here
Book Description
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.
Author: Ari Michael Frank
Publisher:
ISBN:
Category :
Languages : en
Pages : 205
Get Book Here
Book Description
Tandem mass spectrometry (MS/MS) has emerged as the leading technology for high-throughput proteomics analysis, making it possible to rapidly identify and characterize thousands of different proteins in complex biological samples. In recent years we have witnessed a dramatic increase in the capability to acquire proteomics MS/MS data. To avoid computational bottlenecks, this growth in acquisition power must be accompanied by a comparable improvement in analysis capabilities. In this dissertation we present several algorithms we developed to meet some of the major computational challenges that have arisen in MS/MS analysis. Throughout our work we continually address two (sometimes overlapping) problems: how to make MS/MS-based sequence identifications more accurate, and how to make the identification process work much faster. Much of the work we present revolves around algorithms for de novo sequencing of peptides, which aims to discover the amino acid sequence of protein digests (peptides), solely from their experimental mass spectrum. We start off by describing a new scoring model which is used in our de novo sequencing algorithm called PepNovo. Our scoring scheme is based on a graphical model decomposition that describes many of the conditions that determine the intensities of fragment ions observed in mass spectra, such as dependencies between related fragment ions and the influence of the amino acids adjacent to the cleavage site. Besides predicting whole peptide sequences, one of the most useful applications of de novo algorithms is to generate short sequence tags for the purpose of database filtration. We demonstrate how using these tags speeds up database searches by two orders of magnitude compared to conventional methods. We extend the use of tag filtration and show that with high-resolution data, our de novo sequencing is accurate enough to enable extremely rapid identification via direct hash lookup of peptide sequences. The vast amount of MS/MS data that has become available has made it possible to use advanced data-driven machine learning methods to devise more acute algorithms. We describe a new scoring function for peptide-spectrum matches that uses the RankBoost ranking algorithm to learn and model the influences of the many intricate processes that occur during peptide fragmentation. Our method's superior discriminatory power boosts PepNovo's performance beyond the current state-of-the-art de novo sequencing algorithms. Our score also greatly improves the performance of database search programs, significantly increasing both their speed and sensitivity. When we applied our method to the challenging task of a proteogenomic search against a six-frame translation of the human genome, we were able to significantly increase the number of peptide identifications compared to current techniques by 60\%. To help speed up MS/MS analysis, we developed a clustering algorithm that exploits the redundancy that is inherent in large mass spectrometry datasets (these often contain hundreds and even thousands of spectra of the same peptide). When applied to large MS/MS datasets on the order of ten million spectra, our clustering algorithm reduces the number of spectra by an order of magnitude, without losing peptide identifications. Finally, we touch upon sequencing of intact proteins (``top-down'' analysis), which from a computational perspective, is only in its infancy -- very few algorithms have been developed for analysis of this type of data. We developed MS-TopDown, which uses the Spectral Alignment algorithm to characterize protein forms (i.e., determine the modification/mutation sites). Our algorithm can handle heavily modified proteins and can also distinguish between several isobaric protein forms present in the same spectrum.
Author: Lukas Reiter
Publisher:
ISBN:
Category :
Languages : en
Pages : 188
Get Book Here
Book Description
Author: Jörg von Hagen
Publisher: John Wiley & Sons
ISBN: 3527644695
Category : Science
Languages : en
Pages : 498
Get Book Here
Book Description
This long-awaited first guide to sample preparation for proteomics studies overcomes a major bottleneck in this fast growing technique within the molecular life sciences. By addressing the topic from three different angles -- sample, method and aim of the study -- this practical reference has something for every proteomics researcher. Following an introduction to the field, the book looks at sample preparation for specific techniques and applications and finishes with a section on the preparation of sample types. For each method described, a summary of the pros and cons is given, as well as step-by-step protocols adaptable to any specific proteome analysis task.
Author: Daniela Cecconi
Publisher:
ISBN: 9781071616413
Category : Proteomics
Languages : en
Pages : 326
Get Book Here
Book Description
This thorough book collects methods and strategies to analyze proteomics data. It is intended to describe how data obtained by gel-based or gel-free proteomics approaches can be inspected, organized, and interpreted to extrapolate biological information. Organized into four sections, the volume explores strategies to analyze proteomics data obtained by gel-based approaches, different data analysis approaches for gel-free proteomics experiments, bioinformatic tools for the interpretation of proteomics data to obtain biological significant information, as well as methods to integrate proteomics data with other omics datasets including genomics, transcriptomics, metabolomics, and other types of data. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detailed implementation advice that will ensure high quality results in the lab. Authoritative and practical, Proteomics Data Analysis serves as an ideal guide to introduce researchers, both experienced and novice, to new tools and approaches for data analysis to encourage the further study of proteomics.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 406
Get Book Here
Book Description
The work described in this dissertation highlights the versatility of mass spectrometry-based proteomics, detailing the development and/or application of several diverse methods that enable, and improve upon, the large-scale identification and/or quantification of whole proteomes. A broad overview of mass spectrometry-based proteomics and the technological innovations that have driven the field forward are presented in Chapter 1. Chapter 2 outlines a method that utilizes NeuCode SILAC labeling and machine learning algorithms to enable product ion annotation within tandem mass spectra, facilitating the implementation of both automated database searching and de novo sequencing. Chapter 3 presents a strategy for performing multiplexed quantification in the context of data-independent acquisition. Chapter 4 describes the extension of QuantMode, a strategy that utilizes gas-phase purification to improve the quantitative accuracy of isobaric tag-based methods, to an ETD-enabled ion trap system. Chapter 5 outlines a method that improves the sampling depth of label-free experiments without the use of offline fractionation or the significant increase in analysis time. In Chapter 6, both label-free and isobaric tag-based strategies are employed to evaluate the localization and functionality of proteins, protein phosphorylation, and protein acetylation within the various tissues of the model legume Medicago truncatula.
Author: Katrin Marcus
Publisher: Humana Press
ISBN: 9781617798849
Category : Science
Languages : en
Pages : 539
Get Book Here
Book Description
Protein modifications and changes made to them, as well as the quantities of expressed proteins, can define the various functional stages of the cell. Accordingly, perturbations can lead to various diseases and disorders. As a result, it has become paramount to be able to detect and monitor post-translational modifications and to measure the abundance of proteins within the cell with extreme sensitivity. While protein identification is an almost routine requirement nowadays, reliable techniques for quantifying unmodified proteins (including those that escape detection under standard conditions, such as protein isoforms and membrane proteins) is not routine. Quantitative Methods in Proteomics gives a detailed survey of topics and methods on the principles underlying modern protein analysis, from statistical issues when planning proteomics experiments, to gel-based and mass spectrometry-based applications. The quantification of post-translational modifications is also addressed, followed by the “hot” topics of software and data analysis, as well as various overview chapters which provide a comprehensive overview of existing methods in quantitative proteomics. Written in the successful Methods in Molecular BiologyTM series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible protocols, and notes on troubleshooting and avoiding known pitfalls. Authoritative and easily accessible, Quantitative Methods in Proteomics serves as a comprehensive and competent overview of the important and still growing field of quantitative proteomics.
Author: W. Andy Tao
Publisher: John Wiley & Sons
ISBN: 1118970217
Category : Science
Languages : en
Pages : 448
Get Book Here
Book Description
PROVIDES STRATEGIES AND CONCEPTS FOR UNDERSTANDING CHEMICAL PROTEOMICS, AND ANALYZING PROTEIN FUNCTIONS, MODIFICATIONS, AND INTERACTIONS—EMPHASIZING MASS SPECTROMETRY THROUGHOUT Covering mass spectrometry for chemical proteomics, this book helps readers understand analytical strategies behind protein functions, their modifications and interactions, and applications in drug discovery. It provides a basic overview and presents concepts in chemical proteomics through three angles: Strategies, Technical Advances, and Applications. Chapters cover those many technical advances and applications in drug discovery, from target identification to validation and potential treatments. The first section of Mass Spectrometry-Based Chemical Proteomics starts by reviewing basic methods and recent advances in mass spectrometry for proteomics, including shotgun proteomics, quantitative proteomics, and data analyses. The next section covers a variety of techniques and strategies coupling chemical probes to MS-based proteomics to provide functional insights into the proteome. In the last section, it focuses on using chemical strategies to study protein post-translational modifications and high-order structures. Summarizes chemical proteomics, up-to-date concepts, analysis, and target validation Covers fundamentals and strategies, including the profiling of enzyme activities and protein-drug interactions Explains technical advances in the field and describes on shotgun proteomics, quantitative proteomics, and corresponding methods of software and database usage for proteomics Includes a wide variety of applications in drug discovery, from kinase inhibitors and intracellular drug targets to the chemoproteomics analysis of natural products Addresses an important tool in small molecule drug discovery, appealing to both academia and the pharmaceutical industry Mass Spectrometry-Based Chemical Proteomics is an excellent source of information for readers in both academia and industry in a variety of fields, including pharmaceutical sciences, drug discovery, molecular biology, bioinformatics, and analytical sciences.
