Identification of Proteins by Tandem Mass Spectrometry Using Improved Peptide Fragmentation Models PDF Download
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Author: Frédéric Schütz
Publisher:
ISBN:
Category : Mass spectrometry
Languages : en
Pages : 180
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Book Description
Author: Frédéric Schütz
Publisher:
ISBN:
Category : Mass spectrometry
Languages : en
Pages : 180
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Book Description
Author: Michael Kinter
Publisher: John Wiley & Sons
ISBN: 0471231886
Category : Science
Languages : en
Pages : 321
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Book Description
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
Author: Hua Xu
Publisher:
ISBN:
Category : Bioinformatics
Languages : en
Pages :
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Book Description
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.
Author: John R. Chapman
Publisher: Springer Science & Business Media
ISBN: 1592590454
Category : Science
Languages : en
Pages : 539
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Book Description
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.
Author: Jian Wang
Publisher:
ISBN: 9781303217050
Category :
Languages : en
Pages : 124
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Book Description
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.
Author: Oscar Alzate
Publisher: CRC Press
ISBN: 1420076264
Category : Medical
Languages : en
Pages : 356
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Book Description
In this, the post-genomic age, our knowledge of biological systems continues to expand and progress. As the research becomes more focused, so too does the data. Genomic research progresses to proteomics and brings us to a deeper understanding of the behavior and function of protein clusters. And now proteomics gives way to neuroproteomics as we beg
Author: Sacha Baginsky
Publisher: Springer Science & Business Media
ISBN: 376437439X
Category : Science
Languages : en
Pages : 362
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Book Description
This volume aims to provide a timely view of the state-of-the-art in systems biology. The editors take the opportunity to define systems biology as they and the contributing authors see it, and this will lay the groundwork for future studies. The volume is well-suited to both students and researchers interested in the methods of systems biology. Although the focus is on plant systems biology, the proposed material could be suitably applied to any organism.
Author: Willy Vincent Bienvenut
Publisher: Springer Science & Business Media
ISBN: 9781402033186
Category : Medical
Languages : en
Pages : 324
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Book Description
At present where protein identification and characterisation using mass spectrometry is a method of choice, this book is presenting a review of basic proteomic techniques. The second part of the book is related to the novel high throughput protein identification technique called the 'molecular scanner'. Several protein identification techniques are described, especially the peptide mass fingerprint with MALDI-MS based method. E.g. ionisation process, matrix available, signal reproducibility and suppression effect, as well as date treatment for protein identification using bioinformatics tools.
Author: Daniela Cecconi
Publisher:
ISBN: 9781071616413
Category : Proteomics
Languages : en
Pages : 326
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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: Kuang-Ying Hsi
Publisher:
ISBN:
Category :
Languages : en
Pages : 46
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Book Description
Tandem mass spectrometry (MS2) is widely used for peptide and protein identification. One of the most fundamental problems for peptide identification in MS2 is to score peptide annotations against the spectrum which is produced by the peptide. In this thesis, a Bayesian network model is proposed for scoring peptides from Q-TOF mass spectrometers. The research is based on the Bayesian network probabilistic methodology used by InsPecT software, which exploits a hybrid strategy of both database search and de novo algorithms for peptide identification. Initially we focused on the connections of InsPecT scoring model without any changes of nodes. We attempted to determine the connections between nodes for Q-TOF by their dependencies. In order to prove that we need the complete set of nodes as the original InsPecT scoring model, we reduced the number of nodes and surprisingly caused significant improvement in peptide identification performance. The 18-node model was reduced to 10-node models for both charge 2 and charge 3 ions, and we obtained the percentage gain in spectra identification 37.51% for charge 2 and 57.68% for charge 3 ions compared to the InsPecT software 2006.10.20 version. The simplified model also leads to computation time reduction. Currently InsPecT does not perform as well as Mascot on Q-TOF data. Reason for that may be that InsPecT was originally trained for LTQ data and in this thesis we only focused our improvement on the InsPecT scoring stage. Deficiencies may occur in the initial tagging and final calculation of the score. Further research may do an exhaustive combination of fragment ions to derive a set of most discriminative and informative ions.
