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.

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.

Proteomics and peptidomics is the detailed understanding of the role that proteins and peptides play in health and disease and is a necessary compliment to genetic analysis. The functional expression analysis of both proteins and peptides plays a central role in modern drug discovery as well as drug development, and is also a key research area in systems biology. Proteomics and Peptidomics captures the width as well as the depth within the area and exemplifies the variety as well as the traditional basis of analytical chemistry that is needed in order to move forward in expression analysis studies. As a fast emerging field, it gives and overview of parts within the field combined with highly specialized and dedicated topics that are intended to compliment each other.

Proteomics technologies enable the large-scale, high-throughput study of proteoforms inbiological systems. The foremost approach, bottom-up proteomics, can identify and quantify thousands of proteins. However, the analysis of proteoforms is hindered by the required enzymatic digestion. Top-down proteomics does not require enzymatic digestion, enabling proteoform-level analysis. The technical challenge of analyzing proteoforms has thwarted the proliferation of top-down approaches, particularly compared to the ubiquity of bottom-up proteomics. Recent advances in sample preparation have enabled the intact mass measurements of classes of proteoforms traditionally considered challenging for top-down proteomics. Consequently, key barriers to broader applicability remaining in top-down proteomics are data acquisition and data processing. An additional challenge to proteomics in general is data interpretation. Lists of thousands of quantified proteins and/or proteoforms per experiment are not interpretable without software solutions capable of converting the raw output of proteomics experiments into biologically meaningful and actionable insight. This dissertation describes software-based solutions designed to improve the acquisition, processing, and interpretation of proteomics data. Chapter 1 provides an overview of mass spectrometry and the three key challenges addressed by methods in this thesis. Chapter 2 address challenges in data acquisition by introducing automated database searching of a data independent acquisition method for top-down proteomics using a hybrid database search strategy. Chapter 3 describes a new deconvolution method for low-resolution mass spectrometry data processing, taking top-down proteomics beyond high-resolution instruments. Chapter 4 also describes improvements in top-down proteomics data processing, applying astronomical averaging with outlier rejection algorithms to mass spectrometry data. In Chapter 5, a description of the application MetaNetwork, a computer program designed to facilitate systems biology insights for proteomics data is given.

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.

Written by recognized experts in the study of proteins, Proteomics for Biological Discovery begins by discussing the emergence of proteomics from genome sequencing projects and a summary of potential answers to be gained from proteome-level research. The tools of proteomics, from conventional to novel techniques, are then dealt with in terms of underlying concepts, limitations and future directions. An invaluable source of information, this title also provides a thorough overview of the current developments in post-translational modification studies, structural proteomics, biochemical proteomics, microfabrication, applied proteomics, and bioinformatics relevant to proteomics. Presents a comprehensive and coherent review of the major issues faced in terms of technology development, bioinformatics, strategic approaches, and applications Chapters offer a rigorous overview with summary of limitations, emerging approaches, questions, and realistic future industry and basic science applications Discusses higher level integrative aspects, including technical challenges and applications for drug discovery Accessible to the novice while providing experienced investigators essential information Proteomics for Biological Discovery is an essential resource for students, postdoctoral fellows, and researchers across all fields of biomedical research, including biochemistry, protein chemistry, molecular genetics, cell/developmental biology, and bioinformatics.

Proteomics is a multifaceted, interdisciplinary field which studies the complexity and dynamics of proteins in biological systems. It combines powerful separation and analytical technology with advanced informatics to understand the function of proteins in the cell and in the body. This book provides a clear conceptual description of each facet of proteomics, describes recent advances in technology and thinking in each area, and provides details of how these have been applied to a variety of biological problems. It is written by expert practitioners in the field, from industry, research institutions, and the clinic. It provides junior and experienced researchers with an invaluable proteomic reference, and gives fascinating glimpses of the future of this dynamic field.