Computational Methods For Mass Spectrometry Proteomics PDF Download
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Author | : Ingvar Eidhammer |
Publisher | : John Wiley & Sons |
Total Pages | : 296 |
Release | : 2008-02-28 |
Genre | : Medical |
ISBN | : 9780470724293 |
Download Computational Methods for Mass Spectrometry Proteomics Book in PDF, ePub and Kindle
Proteomics is the study of the subsets of proteins present in different parts of an organism and how they change with time and varying conditions. Mass spectrometry is the leading technology used in proteomics, and the field relies heavily on bioinformatics to process and analyze the acquired data. Since recent years have seen tremendous developments in instrumentation and proteomics-related bioinformatics, there is clearly a need for a solid introduction to the crossroads where proteomics and bioinformatics meet. Computational Methods for Mass Spectrometry Proteomics describes the different instruments and methodologies used in proteomics in a unified manner. The authors put an emphasis on the computational methods for the different phases of a proteomics analysis, but the underlying principles in protein chemistry and instrument technology are also described. The book is illustrated by a number of figures and examples, and contains exercises for the reader. Written in an accessible yet rigorous style, it is a valuable reference for both informaticians and biologists. Computational Methods for Mass Spectrometry Proteomics is suited for advanced undergraduate and graduate students of bioinformatics and molecular biology with an interest in proteomics. It also provides a good introduction and reference source for researchers new to proteomics, and for people who come into more peripheral contact with the field.
Author | : Ingvar Eidhammer |
Publisher | : John Wiley & Sons |
Total Pages | : 290 |
Release | : 2012-12-10 |
Genre | : Mathematics |
ISBN | : 111849377X |
Download Computational and Statistical Methods for Protein Quantification by Mass Spectrometry Book in PDF, ePub and Kindle
The definitive introduction to data analysis in quantitative proteomics This book provides all the necessary knowledge about mass spectrometry based proteomics methods and computational and statistical approaches to pursue the planning, design and analysis of quantitative proteomics experiments. The author’s carefully constructed approach allows readers to easily make the transition into the field of quantitative proteomics. Through detailed descriptions of wet-lab methods, computational approaches and statistical tools, this book covers the full scope of a quantitative experiment, allowing readers to acquire new knowledge as well as acting as a useful reference work for more advanced readers. Computational and Statistical Methods for Protein Quantification by Mass Spectrometry: Introduces the use of mass spectrometry in protein quantification and how the bioinformatics challenges in this field can be solved using statistical methods and various software programs. Is illustrated by a large number of figures and examples as well as numerous exercises. Provides both clear and rigorous descriptions of methods and approaches. Is thoroughly indexed and cross-referenced, combining the strengths of a text book with the utility of a reference work. Features detailed discussions of both wet-lab approaches and statistical and computational methods. With clear and thorough descriptions of the various methods and approaches, this book is accessible to biologists, informaticians, and statisticians alike and is aimed at readers across the academic spectrum, from advanced undergraduate students to post doctorates entering the field.
Author | : Pavel Sinitcyn |
Publisher | : |
Total Pages | : 0 |
Release | : 2019 |
Genre | : |
ISBN | : |
Download Computational Methods for Understanding Mass Spectrometry-Based Shotgun Proteomics Data Book in PDF, ePub and Kindle
Computational proteomics is the data science concerned with the identification and quantification of proteins from high-throughput data and the biological interpretation of their concentration changes, posttranslational modifications, interactions, and subcellular localizations. Today, these data most often originate from mass spectrometry-based shotgun proteomics experiments. In this review, we survey computational methods for the analysis of such proteomics data, focusing on the explanation of the key concepts. Starting with mass spectrometric feature detection, we then cover methods for the identification of peptides. Subsequently, protein inference and the control of false discovery rates are highly important topics covered. We then discuss methods for the quantification of peptides and proteins. A section on downstream data analysis covers exploratory statistics, network analysis, machine learning, and multiomics data integration. Finally, we discuss current developments and provide an outlook on what the near future of computational proteomics might bear.
Author | : Hamid Hamzeiy |
Publisher | : |
Total Pages | : |
Release | : 2021 |
Genre | : Mass spectrometry |
ISBN | : |
Download Advancing Computational Methods for Mass Spectrometry-based Proteomics, Metabolomics, and Analysis of Multi-omics Datasets Book in PDF, ePub and Kindle
Author | : Rune Matthiesen |
Publisher | : Humana |
Total Pages | : 470 |
Release | : 2019-10-01 |
Genre | : Science |
ISBN | : 9781493997435 |
Download Mass Spectrometry Data Analysis in Proteomics Book in PDF, ePub and Kindle
The aim of this new edition is to provide detailed information on each topic and present novel ideas and views that can influence future developments in mass spectrometry-based proteomics. In contrast to the previous editions, this third edition aims to provide the most relevant computational methods, focusing on computational concepts. 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, Mass Spectrometry Data Analysis in Proteomics, Third Edition to ensure successful results in the further study of this vital field.
Author | : Lukas Mueller |
Publisher | : |
Total Pages | : 144 |
Release | : 2011-07 |
Genre | : Mass spectrometry |
ISBN | : 9783838332307 |
Download Novel Computational Techniques in Mass Spectrometry Based Proteomics Book in PDF, ePub and Kindle
Author | : Rune Matthiesen |
Publisher | : |
Total Pages | : 405 |
Release | : 2013 |
Genre | : Mass spectrometry |
ISBN | : 9781627033923 |
Download Mass Spectrometry Data Analysis in Proteomics Book in PDF, ePub and Kindle
Since the publishing of the first edition, the methodologies and instrumentation involved in the field of mass spectrometry-based proteomics has improved considerably. Fully revised and expanded, Mass Spectrometry Data Analysis in Proteomics, Second Edition presents expert chapters on specific MS-based methods or data analysis strategies in proteomics. The volume covers data analysis topics relevant for quantitative proteomics, post translational modification, HX-MS, glycomics, and data exchange standards, among other topics. Written in the highly successful Methods in Molecular Biology series format, chapters include brief introductions to their respective subjects, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Updated and authoritative, Mass Spectrometry Data Analysis in Proteomics, Second Edition serves as a detailed guide for all researchers seeking to further our knowledge in the field of proteomics.
Author | : Lei Wang (Computer scientist) |
Publisher | : |
Total Pages | : 0 |
Release | : 2022 |
Genre | : Machine learning |
ISBN | : |
Download Computational Methods to Improve and Validate Peptide Identifications in Proteomics Book in PDF, ePub and Kindle
With the rapid development of mass spectrometry technology in the past decade and the recent large-scale proteomics projects, massive and highly redundant tandem mass spectra (MS/MS) are being generated at an unprecedented speed. Hundreds of publications have been made for proteomics studies, yet computational methods which can efficiently identify and analyze the sheer amount of proteomic MS/MS data are still outstanding. The thesis aims to provide systematic approaches to studying MS/MS data from three aspects: spectral clustering, spectral library searching and validation of peptide-spectrum matchings (PSMs).I first introduce a rapid algorithm accelerated by Locality Sensitive Hashing (LSH) techniques to reduce the redundancy in proteomics datasets via clustering similar spectra. The proposed method demonstrates 7-11X performance improvement in running time while retaining superior sensitivity and accuracy when compared to the state of the art spectral clustering algorithms. In addition to the reduction of repetition of similar spectra, the time to search protein database, i.e. a commonly used technique for peptide identification, can be greatly shortened when using the consensus spectra that usually exhibit higher quality than the raw spectra. As a result, It can be demonstrated that more peptide identifications were obtained at the same low false discovery rate (FDR).The second chapter delves into spectral library searching, a complementary approach to database searching for peptide identifications on MS/MS spectra. LSH techniques ensure that similar spectra are placed into the same buckets, whereas spectra with low pairwise similarity are scattered into different buckets. Each input experimental spectrum can then be compared against a subset of highly similar spectra, thus diminishing the unnecessary spectral similarity computation between the input spectrum and all possible combinations of candidate peptides. The identified peptides overlap with those reported by other existing algorithms to a great extent. More importantly, the acceleration rate in the running time of proposed algorithm compared to existing ones increases with the growing size of spectral libraries.Redundancy in large scale proteomic datasets are exploited to further improve the searching results by eliminating the false PSMs examined through a post-processing step. Despite the success of data searching algorithms in proteomics, the peptide identification results usually contain a small fraction of incorrect peptide assignments. Target decoy approach was introduced in previous work to assess the quality of identifications, by searching spectrum against both target and decoy sequences. I formalize the method to improve peptide identifications by removing false PSMs in a probabilistic post-processing approach. As a result, as low as 0.8\\% FDR can be obtained on the remaining PSMs previously reported at 1\\% FDR level and up to 38\\% more unique peptides can be reported at the expected FDR level.I anticipate the computational methods developed in the dissertation can advance the proteomics research field by improving the protein identification through database searching, spectral library searching and validating the searching outputs in a subsequent step. Although the algorithms were evaluated for proteomics studies, they can be extended to small molecules such as natural products, lipids and glycoconjugates. These algorithms can also be generalized to the identification of experimental MS/MS spectra from a molecule of specific interest in massive omic datasets.
Author | : Rosa M. Vitale |
Publisher | : |
Total Pages | : |
Release | : 2011 |
Genre | : Computers |
ISBN | : |
Download Computational Methods in Mass Spectrometry-Based Protein 3D Studies Book in PDF, ePub and Kindle
Computational Methods in Mass Spectrometry-Based Protein 3D Studies.
Author | : Robin Schmid |
Publisher | : |
Total Pages | : |
Release | : 2020 |
Genre | : |
ISBN | : |
Download Computational Methods for Mass Spectrometry Data Analysis and Imaging Book in PDF, ePub and Kindle