Download or read book Novel Data Analysis Methods and Algorithms for Identification of Peptides and Proteins by Use of Tandem Mass Spectrometry written by Hua Xu and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: Tandem mass spectrometry is one of the most important tools for protein analysis. This thesis is focused on the development of new methods and algorithms for tandem mass spectrometry data analysis. A database search engine, MassMatrix, has also been developed that incorporates these methods and algorithms. The program is publicly available both on the web server at www.massmatrix.net and as a deliverable software package for personal computers. Three different scoring algorithms have been developed to identify and characterize proteins and peptides by use of tandem mass spectrometry data. The first one is targeted at the next generation of tandem mass spectrometers that are capable of high mass accuracy and resolution. Two scores calculated by the algorithm are sensitive to high mass accuracy due to the fact that this new algorithm explicitly incorporates mass accuracy into scoring potential peptide and protein matches for tandem mass spectra. The algorithm is further improved by employing Monte Carlo Simulations to calculate ion abundance based scores without any assumptions or simplifications. For high mass accuracy data, MassMatrix provides improvements in sensitivity over other database search programs. The second scoring algorithm based on peptide sequence tags inferred from tandem mass spectra further improves the performance of MassMatrix for low mass accuracy tandem mass spectrometry data. The third algorithm is the first automated data analysis method that uses peptide retention times in liquid chromatography to evaluate potential peptide matches for tandem mass spectrometry data. The algorithm predicts reverse phase liquid chromatography retention times of peptides by their hydrophobicities and compares the predicted retention times with the observed ones to evaluate the peptide matches. In order to handle low quality data, a new method has also been developed to reduce noise in tandem mass spectra and screen poor quality spectra. In addition, a data analysis method for identification of disulfide bonds in proteins and peptides by tandem mass spectrometry data has been developed and incorporated in MassMatrix. By this new approach, proteins and peptides with disulfide bonds can be directly identified in tandem mass spectrometry with high confidence without any chemical reduction and/or other derivatization.

Download or read book Mass Spectrometry Data Analysis in Proteomics written by Rune Matthiesen and published by Springer Science & Business Media. This book was released on 2008-02-02 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is an in-depth guide to the theory and practice of analyzing raw mass spectrometry (MS) data in proteomics. The volume outlines available bioinformatics programs, algorithms, and databases available for MS data analysis. General guidelines for data analysis using search engines such as Mascot, Xtandem, and VEMS are provided, with specific attention to identifying poor quality data and optimizing search parameters.

Download or read book Protein Sequencing and Identification Using Tandem Mass Spectrometry written by Michael Kinter and published by John Wiley & Sons. This book was released on 2005-04-12 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: How to design, execute, and interpret experiments for protein sequencing using mass spectrometry The rapid expansion of searchable protein and DNA databases in recent years has triggered an explosive growth in the application of mass spectrometry to protein sequencing. This timely and authoritative book provides professionals and scientists in biotechnology research with complete coverage of procedures for analyzing protein sequences by mass spectrometry, including step-by-step guidelines for sample preparation, analysis, and data interpretation. Michael Kinter and Nicholas Sherman present their own high-quality, laboratory-tested protocols for the analysis of a wide variety of samples, demonstrating how to carry out specific experiments and obtain fast, reliable results with a 99% success rate. Readers will get sufficient experimental detail to apply in their own laboratories, learn about the proper selection and operation of instruments, and gain essential insight into the fundamental principles of mass spectrometry and protein sequencing. Coverage includes: * Peptide fragmentation and interpretation of product ion spectra * Basic polyacrylamide gel electrophoresis * Preparation of protein digests for sequencing experiments * Mass spectrometric analysis using capillary liquid chromatography * Techniques for protein identification by database searches * Characterization of modified peptides using tandem mass spectrometry And much more

Download or read book Mass Spectrometry of Proteins and Peptides written by John R. Chapman and published by Springer Science & Business Media. This book was released on 2008-02-05 with total page 539 pages. Available in PDF, EPUB and Kindle. Book excerpt: Little more than three years down the line and I am already writing the Preface to a second volume to follow Protein and Peptide Analysis by Mass . What has happened in between these times to make this second venture worthwhile? New types of mass spectrometric instrumentation have appeared so that new techniques have become possible and existing techniques have become much more feasible. More particularly, however, the newer ionization te- niques, introduced for the analysis of high molecular weight materials, have now been thoroughly used and studied. As a result, there has been an en- mous improvement in the associated sample handling technology so that these methods are now routinely applied to much smaller sample amounts as well as to more intractable samples. Again, this particular community of mass spectrometry users has both increased in number and diversified. And, riding this wave of acceptance, leaders in the field have set their sights on more complex problems: molecular interaction, ion structures, quantitation, and kinetics are just a few of the newer areas reported in Mass Spectrometry of Proteins and Peptides. As with the first volume, one purpose of this collection, Mass Spectr- etry of Proteins and Peptides, is to show the reader what can be done by the application of mass spectrometry, and perhaps even to encourage the reader to venture down new paths.

Download or read book Novel Methods for Improved Identification Throughput and High resolution Scoring for Proteomics written by Brendan Keeley Faherty and published by . This book was released on 2012 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of proteomics aims to identify and quantify the protein contents of a biological sample. The mass spectrometer is the instrument of choice to characterize these proteins. In the typical proteomics experiment, mass spectra are collected from peptides as the peptides are eluted off of a liquid chromatography column and electrosprayed into the instrument as ions. Certain peptides are further selected as ions and isolated and fragmented. The fragments are recorded as tandem mass spectra, which are lists of fragment masses and intensities, and are subsequently used for identification. After the sample has been analyzed by the mass spectrometer, a number of methods, including database searching, can be used to match each tandem mass spectrum to a peptide that existed in the biological sample. Historically, the time to successfully identify the collected tandem mass spectra has been substantially longer than the time spent collecting them on the instrument. One of the standard database searching algorithms used for identification, SEQUEST, was published in 1994 when the time spent in data analysis was almost an afterthought since the number of collected spectra could be measured in the dozens. Today, modern mass spectrometers are capable of collecting thousands of tandem mass spectra each hour with orders and magnitude greater peak resolution. This thesis work builds on the SEQUEST algorithm and focuses on the use of high-resolution tandem mass spectra for the purposes of identification in order to allow more accurate and comprehensive identifications as well as novel methods to increase the throughput of the analysis of tandem mass spectra by database searching.

Download or read book Computational and Statistical Methods for Protein Quantification by Mass Spectrometry written by Ingvar Eidhammer and published by John Wiley & Sons. This book was released on 2012-12-10 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Expanding the Toolbox of Tandem Mass Spectrometry with Algorithms to Identify Mass Spectra from More Than One Peptide written by Jian Wang and published by . This book was released on 2013 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: In high-throughput proteomics the development of computational methods and novel experimental strategies often rely on each other. In several areas, mass spectrometry methods for data acquisition are ahead of computational methods to interpret the resulting tandem mass (MS/MS) spectra. While there are numerous situations where two or more peptides are co-fragmented in the same MS/MS spectrum, nearly all mainstream computational approaches still make the ubiquitous assumption that each MS/MS spectrum comes from only one peptide. In this thesis we addressed problems in three emerging areas where computational tools that relax the above assumption are crucial for the success application of these approaches on a large-scale. In the first chapter we describe algorithms for the identification of mixture spectra that are from more than one co-eluting peptide precursors. The ability to interpret mixture spectra not only improves peptide identification in traditional data-dependent-acquisition (DDA) workflows but is also crucial for the success application of emerging data-independent-acquisition (DIA) techniques that have the potential to greatly improve the throughput of peptide identification. In chapter two, we address the problem of identification of peptides with complex post-translational modification (PTM). Detection of PTMs is important to understand the functional dynamics of proteins. Complex PTMs resulted from the conjugation of another macromolecule onto the substrate protein. The resultant modified peptides not only generate spectrum that contains a mixture of fragment ions from both the PTM and the substrate peptide but they also display substantially different fragmentation patterns as compared to conventional, unmodified peptides. We describe a hybrid experimental and computational approach to build search tools that capture the specific fragmentation patterns of modified peptides. Finally in chapter three we address the problem of identification of linked peptides. Linked peptides are two peptides that are covalently linked together. The generation and identification of linked peptides has recently been demonstrated to be a versatile tool to study protein-protein interactions and protein structures, however the identification of linked peptides face many challenges. We integrate lessons learned in the previous chapters to build an efficient and sensitive tool to identify linked peptides from MS/MS spectra.

Download or read book Proteome Informatics written by Conrad Bessant and published by Royal Society of Chemistry. This book was released on 2016-11-23 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bringing together world experts to provide clear explanations of the key algorithms, workflows and analysis frameworks, Proteome Informatics will provide a detailed introduction to the main informatics topics that underpin the various LC-MS/MS protocols used for protein identification and quantitation.

Download or read book Protein and Peptide Mass Spectrometry in Drug Discovery written by Michael L. Gross and published by John Wiley & Sons. This book was released on 2011-09-26 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book that highlights mass spectrometry and its application in characterizing proteins and peptides in drug discovery An instrumental analytical method for quantifying the mass and characterization of various samples from small molecules to large proteins, mass spectrometry (MS) has become one of the most widely used techniques for studying proteins and peptides over the last decade. Bringing together the work of experts in academia and industry, Protein and Peptide Mass Spectrometry in Drug Discovery highlights current analytical approaches, industry practices, and modern strategies for the characterization of both peptides and proteins in drug discovery. Illustrating the critical role MS technology plays in characterizing target proteins and protein products, the methods used, ion mobility, and the use of microwave radiation to speed proteolysis, the book also covers important emerging applications for neuroproteomics and antigenic peptides. Placing an emphasis on the pharmaceutical industry, the book stresses practice and applications, presenting real-world examples covering the most recent advances in mass spectrometry, and providing an invaluable resource for pharmaceutical scientists in industry and academia, analytical and bioanalytical chemists, and researchers in protein science and proteomics.

Download or read book Novel Data Analysis Approaches for Cross linking Mass Spectrometry Proteomics and Glycoproteomics written by Lei Lu and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Bottom-up proteomics has emerged as a powerful technology for biological studies. The technique is used for a myriad of purposes, including among others protein identification, post-translational modification identification, protein-protein interaction analysis, protein quantification analysis, and protein structure analysis. The data analysis approaches of bottom-up proteomics have evolved over the past two decades, and many different algorithms and software programs have been developed for these varied purposes. In this thesis, I have focused on improving the database search strategies for the important special applications of bottom-up proteomics, including cross-linking mass spectrometry proteomics and O-glycoproteomics. In cross-linking mass spectrometry proteomics, a sample of proteins is treated with a chemical cross-linking reagent. This causes peptides within the proteins to be cross-linked to one another, forming peptide doublets that are released by treatment of the sample with a protease such as trypsin. The data analysis tools are designed to identify the cross-linked peptides. In O-glycoproteomics, the peptides that are released by protease digestion of the protein sample can be modified with any of or even multiple distinct O-glycans, and the data analysis tools should be able to identify all of the glycans and the modification sites at which they are located. In both cases, traditional database searching strategies which try to match the experimental spectra to all potential theoretical spectra is not practical due to the large increases in search space. Researchers suffered from a lack of efficient data analysis tools for these two applications. Here we successfully devised new search algorithms to address these problems, and impemented them in two new software modules in our laboratories' bottom-up software engine MetaMorpheus (Crosslinking data analysis via MetaMorpheusXL and O-glycoproteomics data analysis via O-Pair Search). The new search strategies used in the software program are both based on ion-indexed open search, which was first developed for large scale proteomic studies in the programs MSFragger and Open-pFind. The ion-indexed open search was optimized for cross-linking mass spectrometry proteomics and O-glycoproteomics in this study, and combined with other algorithms. In O-glycoproteomics, a graph-based algorithm is used to speed up the identification and localization of O-glycans. Other useful features have been added in the software program, such as enabling analysis of both cleavable cross-links and non-cleavable cross-links in the cross-link search module, and calculating localization probabilities in the O-glyco search module. Further optimizations including machine learning methods for false discovery rate (FDR) analysis, retention time prediction and spectral prediction could further improve the current best search approaches for cross-link proteomics and O-glycoproteomics data analysis. Chapter 1 provides an overview of bottom-up proteomics data analysis methods and outlines how ion-indexed open search could be useful for special bottom-up proteomics studies. Chapter 2 describes the development of a cross-linking mass spectrometry proteomics search module, resulting in efficiency improvements for both cleavable and non-cleavable cross-link proteomics data analysis. Chapter 3 describes the development of an O-glycoproteomics search module; by combining the ion-indexed open search algorithm with the graph-based localization algorithm, the O-pair Search is more than 2000 times faster than the currently widely used software program Byonic. In Chapter 4, a novel top-down data acquisition method is described. Chapter 5 provides conclusions and future directions.

Download or read book Introduction to Protein Mass Spectrometry written by Pradip K. Ghosh and published by Elsevier. This book was released on 2024-04-26 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Protein Mass Spectrometry, Second Edition provides a comprehensive overview of this increasingly important, yet complex, analytical technique. This book enables readers to understand how determinations about protein identity from mass spectrometric data are made. Coverage begins with the technical basics, including preparations, instruments, and spectrometric analysis of peptides and proteins, before exploring applied use in biological applications, bioinformatics, database, and software resources. This new edition is fully updated to include the latest developments in the field and will feature new content covering recent progress in the areas where there have been the most exciting advances. These include PNNL’s multilevel-PCB-based SLIM realization, SLIM-Agilent QQQ field trials; employment of SLIM-IMS-cryo-IR combination in molecular structure determination; proximity-labelling mass spectrometry, and applications in neuroscience. Offers up-to-date, introductory information for scientists and researchers new to the field, as well as advanced insights into the critical assessment of computer-analyzed mass spectrometric results and their current limitations Provides examples of commonly used MS instruments from a range of key manufacturers/developers, including Bruker, Applied Biosystems, JEOL, Thermo Scientific/Thermo Fisher Scientific, IU, Waters and PNNL Includes biological applications and exploration of analytical tools and databases for bioinformatics Features definitions, case studies, and recent developments in protein mass spectrometry Includes sections new to this edition on SLIM (Structures for Lossless Ion Manipulation) and mass spectrometry applications in neuroscience, including synaptic biology and Alzheimer’s disease

Download or read book Novel Data Analysis Approaches for Cross linking Mass Spectrometry Proteomics and Glycoproteomics written by Lei Lu and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bottom-up proteomics has emerged as a powerful technology for biological studies. The technique is used for a myriad of purposes, including among others protein identification, post-translational modification identification, protein-protein interaction analysis, protein quantification analysis, and protein structure analysis. The data analysis approaches of bottom-up proteomics have evolved over the past two decades, and many different algorithms and software programs have been developed for these varied purposes. In this thesis, I have focused on improving the database search strategies for the important special applications of bottom-up proteomics, including cross-linking mass spectrometry proteomics and O-glycoproteomics. In cross-linking mass spectrometry proteomics, a sample of proteins is treated with a chemical cross-linking reagent. This causes peptides within the proteins to be cross-linked to one another, forming peptide doublets that are released by treatment of the sample with a protease such as trypsin. The data analysis tools are designed to identify the cross-linked peptides. In O-glycoproteomics, the peptides that are released by protease digestion of the protein sample can be modified with any of or even multiple distinct O-glycans, and the data analysis tools should be able to identify all of the glycans and the modification sites at which they are located. In both cases, traditional database searching strategies which try to match the experimental spectra to all potential theoretical spectra is not practical due to the large increases in search space. Researchers suffered from a lack of efficient data analysis tools for these two applications. Here we successfully devised new search algorithms to address these problems, and impemented them in two new software modules in our laboratories' bottom-up software engine MetaMorpheus (Crosslinking data analysis via MetaMorpheusXL and O-glycoproteomics data analysis via O-Pair Search). The new search strategies used in the software program are both based on ion-indexed open search, which was first developed for large scale proteomic studies in the programs MSFragger and Open-pFind. The ion-indexed open search was optimized for cross-linking mass spectrometry proteomics and O-glycoproteomics in this study, and combined with other algorithms. In O-glycoproteomics, a graph-based algorithm is used to speed up the identification and localization of O-glycans. Other useful features have been added in the software program, such as enabling analysis of both cleavable cross-links and non-cleavable cross-links in the cross-link search module, and calculating localization probabilities in the O-glyco search module. Further optimizations including machine learning methods for false discovery rate (FDR) analysis, retention time prediction and spectral prediction could further improve the current best search approaches for cross-link proteomics and O-glycoproteomics data analysis. Chapter 1 provides an overview of bottom-up proteomics data analysis methods and outlines how ion-indexed open search could be useful for special bottom-up proteomics studies. Chapter 2 describes the development of a cross-linking mass spectrometry proteomics search module, resulting in efficiency improvements for both cleavable and non-cleavable cross-link proteomics data analysis. Chapter 3 describes the development of an O-glycoproteomics search module; by combining the ion-indexed open search algorithm with the graph-based localization algorithm, the O-pair Search is more than 2000 times faster than the currently widely used software program Byonic. In Chapter 4, a novel top-down data acquisition method is described. Chapter 5 provides conclusions and future directions.

Download or read book Development of Data Independent Acquisition Techniques for the Analysis of Protein Mixtures by Tandem Mass Spectrometry written by Jarrett D. Egertson and published by . This book was released on 2013 with total page 149 pages. Available in PDF, EPUB and Kindle. Book excerpt: Novel algorithms and data acquisition methods designed to improve the ability to identify and quantify proteins in complex biological mixtures using tandem mass spectrometry are presented. An algorithm for de novo correction of mass-to-charge measurements in MS/MS spectra acquired in a shotgun proteomics workflow is described. The correction of m/z measurements makes the interpretation of MS/MS spectra easier and can increase the number of peptides identified in a bottom-up shotgun proteomics experiment. The technique is described as de novo because it can detect systematic mass measurement error in a collection of tandem mass spectra without any input besides the spectra themselves. To improve quantitation of peptides, a multiplexed data independent acquisition (DIA) technique is presented. Data acquired using DIA can be queried for data on virtually any protein. These data can be used to compare the abundances of proteins in multiple samples with high sensitivity (often higher than using MS data). However, DIA techniques have typically had low precursor selectivity compared to popular data dependent acquisition (DDA) techniques resulting in mixed MS/MS spectra that are difficult to interpret and prone to chemical interference. A method for overcoming this limitation of DIA by multiplexing (and computational demultiplexing) is described. DIA and DDA techniques are used to study the response of the budding yeast S. cerevisiae to treatment with rapamycin. The response to rapamycin is of interest because it extends lifespan in a wide range of organisms. Spectral counting for peptide quantitation using DDA data is compared to quantitation using MS/MS fragment ion chromatograms integrated over time with DIA data.

Download or read book Algorithms for Characterizing Peptides and Glycopeptides with Mass Spectrometry written by Lin He and published by . This book was released on 2013 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: The emergence of tandem mass spectrometry (MS/MS) technology has significantly accelerated protein identification and quantification in proteomics. It enables high-throughput analysis of proteins and their quantities in a complex protein mixture. A mass spectrometer can easily and rapidly generate large volumes of mass spectral data for a biological sample. This bulk of data makes manual interpretation impossible and has also brought numerous challenges in automated data analysis. Algorithmic solutions have been proposed and provide indispensable analytical support in current proteomic experiments. However, new algorithms are still needed to either improve result accuracy or provide additional data analysis capabilities for both protein identification and quantification. Accurate identification of proteins in a sample is the preliminary requirement of a proteomic study. In many cases, a mass spectrum cannot provide complete information to identify the peptide without ambiguity because of the inefficiency of the peptide fragmentation technique and the prevalent existence of noise. We propose ADEPTS to this problem using the complementary information provided in different types of mass spectra. Meanwhile, the occurrence of posttranslational modifications (PTMs) on proteins is another major issue that prevents the interpretation of a large portion of spectra. Using current software tools, users have to specify possible PTMs in advance. However, the number of possible PTMs has to be limited since specifying more PTMs to the software leads to a longer running time and lower result accuracy. Thus, we develop DeNovoPTM and PeaksPTM to provide efficient and accurate solutions. Glycosylation is one of the most frequently observed PTMs in proteomics. It plays important roles in many disease processes and thus has attracted growing research interest. However, lack of algorithms that can identify intact glycopeptides has become the major obstacle that hinders glycoprotein studies. We propose a novel algorithm, GlycoMaster DB, to fulfil this urgent requirement. Additional research is presented on protein quantification, which studies the changes of protein quantity by comparing two or more mass spectral datasets. A crucial problem in the quantification is to correct the retention time distortions between different datasets. Heuristic solutions from previous research have been used in practice but none of them has yet claimed a clear optimization goal. To address this issue, we propose a combinatorial model and practical algorithms for this problem.

Download or read book New Methods in Peptide Mapping for the Characterization of Proteins written by William S. Hancock and published by CRC Press. This book was released on 1995-10-23 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text is devoted to the characterization of recombinant DNA-derived proteins by peptide mapping. It describes new technological procedures including capillary electrophoresis, analysis of glycopeptides and the use of electrospray and matrix-assisted laser desorption mass spectrometry. The book presents practical procedures for preparing a protein sample, the enzyme digestion, choice of separation method and procedures for the structural analysis of the separated species. Many figures of peptide maps illustrate typical results. Tables of summary information about digestion, separation conditions, and analyses of important protein samples are also presented.

Download or read book Introduction to Proteomics written by Daniel Liebler and published by Springer Science & Business Media. This book was released on 2001-12-04 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: Daniel C. Liebler masterfully introduces the science of proteomics by spelling out the basics of how one analyzes proteins and proteomes, and just how these approaches are then employed to investigate their roles in living systems. He explains the key concepts of proteomics, how the analytical instrumentation works, what data mining and other software tools do, and how these tools can be integrated to study proteomes. Also discussed are how protein and peptide separation techniques are applied in proteomics, how mass spectrometry is used to identify proteins, and how data analysis software enables protein identification and the mapping of modifications. In addition, there are proteomic approaches for analyzing differential protein expression, characterizing proteomic diversity, and dissecting protein-protein interactions and networks.

Download or read book Statistical Analysis of Proteomics Metabolomics and Lipidomics Data Using Mass Spectrometry written by Susmita Datta and published by Springer. This book was released on 2016-12-15 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents an overview of computational and statistical design and analysis of mass spectrometry-based proteomics, metabolomics, and lipidomics data. This contributed volume provides an introduction to the special aspects of statistical design and analysis with mass spectrometry data for the new omic sciences. The text discusses common aspects of design and analysis between and across all (or most) forms of mass spectrometry, while also providing special examples of application with the most common forms of mass spectrometry. Also covered are applications of computational mass spectrometry not only in clinical study but also in the interpretation of omics data in plant biology studies. Omics research fields are expected to revolutionize biomolecular research by the ability to simultaneously profile many compounds within either patient blood, urine, tissue, or other biological samples. Mass spectrometry is one of the key analytical techniques used in these new omic sciences. Liquid chromatography mass spectrometry, time-of-flight data, and Fourier transform mass spectrometry are but a selection of the measurement platforms available to the modern analyst. Thus in practical proteomics or metabolomics, researchers will not only be confronted with new high dimensional data types—as opposed to the familiar data structures in more classical genomics—but also with great variation between distinct types of mass spectral measurements derived from different platforms, which may complicate analyses, comparison, and interpretation of results.