Search results for ""Author Ingvar Eidhammer""

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.

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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.

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Genomics and bioinformatics play an increasingly important and transformative role in medicine, society and agriculture. The mapping of the human genome has revealed 35,000 or so genes which might code for more than one protein, resulting in 100,000 proteins for the humans alone. Since proteins are attractive targets for developing drugs, efforts are now underway to map sequences and assign functions to many novel proteins. This book takes the novel approach to cover both the sequence and structure analysis of proteins in one volume and from an algorithmic perspective. Key features of the book include: Provides a comprehensive introduction to the analysis of protein sequence and structure analysis. Takes an algorithmic approach, relying on computational methods rather than theoretical. Provides an integrated presentation of theory, examples, exercises and applications. Includes coverage of both protein structure, and sequence, analysis. Accessible enough for biologists, yet rigorous enough for computer scientists and mathematicians. Supported by a Web site featuring exercises, solutions, images, and computer programs. Visit this website for exercises with solutions, computer programs, errata and additional material: http://www.ii.uib.no/proteinbioinformatics/

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