Data Mining In Proteomics PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Data Mining In Proteomics PDF full book. Access full book title Data Mining In Proteomics.
Author | : Werner Dubitzky |
Publisher | : Springer Science & Business Media |
Total Pages | : 300 |
Release | : 2007-04-13 |
Genre | : Science |
ISBN | : 0387475095 |
Download Fundamentals of Data Mining in Genomics and Proteomics Book in PDF, ePub and Kindle
This book presents state-of-the-art analytical methods from statistics and data mining for the analysis of high-throughput data from genomics and proteomics. It adopts an approach focusing on concepts and applications and presents key analytical techniques for the analysis of genomics and proteomics data by detailing their underlying principles, merits and limitations.
Author | : Michael Hamacher |
Publisher | : Humana Press |
Total Pages | : 0 |
Release | : 2010-11-02 |
Genre | : Science |
ISBN | : 9781607619864 |
Download Data Mining in Proteomics Book in PDF, ePub and Kindle
Through the rapid development of proteomics methods and technologies, an enormous amount of data was created, leading to a wide-spread rethinking of strategy design and data interpretation. In Data Mining in Proteomics: From Standards to Applications, experts in the field present these new insights within the proteomics community, taking the historical evolution as well as the most important international standardization projects into account. Along with basic and sophisticated overviews of proteomics technologies, standard data formats, and databases, the volume features chapters on data interpretation strategies including statistics, spectra interpretation, and analysis environments as well as specialized tasks such as data annotation, peak picking, phosphoproteomics, spectrum libraries, LC/MS imaging, and splice isoforms. As a part of the highly successful Methods in Molecular BiologyTM series, this work provides the kind of detailed description and implementation advice that is crucial for getting optimal results. Authoritative and cutting-edge, Data Mining in Proteomics: From Standards to Applications is a well-balanced compendium for beginners and experts, offering a broad scope of data mining topics but always focusing on the current state-of-the-art and beyond.
Author | : Darius M. Dziuda |
Publisher | : John Wiley & Sons |
Total Pages | : 348 |
Release | : 2010-07-16 |
Genre | : Computers |
ISBN | : 0470593407 |
Download Data Mining for Genomics and Proteomics Book in PDF, ePub and Kindle
Data Mining for Genomics and Proteomics uses pragmatic examples and a complete case study to demonstrate step-by-step how biomedical studies can be used to maximize the chance of extracting new and useful biomedical knowledge from data. It is an excellent resource for students and professionals involved with gene or protein expression data in a variety of settings.
Author | : Li, Xiao-Li |
Publisher | : IGI Global |
Total Pages | : 450 |
Release | : 2009-05-31 |
Genre | : Technology & Engineering |
ISBN | : 1605663999 |
Download Biological Data Mining in Protein Interaction Networks Book in PDF, ePub and Kindle
"The goal of this book is to disseminate research results and best practices from cross-disciplinary researchers and practitioners interested in, and working on bioinformatics, data mining, and proteomics"--Provided by publisher.
Author | : Siegfried Schreuder |
Publisher | : |
Total Pages | : 187 |
Release | : 1989 |
Genre | : Computer-aided design |
ISBN | : 9780387516608 |
Download Rechnergestützte Konstruktionsarbeit Book in PDF, ePub and Kindle
Author | : Chia-Yu Yen |
Publisher | : |
Total Pages | : 156 |
Release | : 2003 |
Genre | : Data mining |
ISBN | : |
Download Data Mining and Quantitative Analysis of Proteomics Book in PDF, ePub and Kindle
Author | : Yang Song |
Publisher | : |
Total Pages | : 92 |
Release | : 2015 |
Genre | : |
ISBN | : |
Download Data Mining in Computational Proteomics and Genomics Book in PDF, ePub and Kindle
This dissertation addresses data mining in bioinformatics by investigating two important problems, namely peak detection and structure matching. Peak detection is useful for biological pattern discovery while structure matching finds many applications in clustering and classification. The first part of this dissertation focuses on elastic peak detection in 2D liquid chromatographic mass spectrometry (LC-MS) data used in proteomics research. These data can be modeled as a time series, in which the X-axis represents time points and the Y-axis represents intensity values. A peak occurs in a set of 2D LC-MS data when the sum of the intensity values in a sliding time window exceeds a user-determined threshold. The elastic peak detection problem is to locate all peaks across multiple window sizes of interest in the dataset. A new method, called PeakID, is proposed in this dissertation, which solves the elastic peak detection problem in 2D LC-MS data without yielding any false negative. PeakID employs a novel data structure, called a Shifted Aggregation Tree or AggTree for short, to find the different peaks in the dataset. This method works by first constructing an AggTree in a bottom-up manner from the dataset, and then searching the AggTree for the peaks in a top-down manner. PeakID uses a state-space algorithm to find the topology and structure of an efficient AggTree. Experimental results demonstrate the superiority of the proposed method over other methods on both synthetic and real-world data. The second part of this dissertation focuses on RNA pseudoknot structure matching and alignment. RNA pseudoknot structures play important roles in many genomic processes. Previous methods for comparative pseudoknot analysis mainly focus on simultaneous folding and alignment of RNA sequences. Little work has been done to align two known RNA secondary structures with pseudoknots taking into account both sequence and structure information of the two RNAs. A new method, called RKalign, is proposed in this dissertation for aligning two known RNA secondary structures with pseudoknots. RKalign adopts the partition function methodology to calculate the posterior log-odds scores of the alignments between bases or base pairs of the two RNAs with a dynamic programming algorithm. The posterior log-odds scores are then used to calculate the expected accuracy of an alignment between the RNAs. The goal is to find an optimal alignment with the maximum expected accuracy. RKalign employs a greedy algorithm to achieve this goal. The performance of RKalign is investigated and compared with existing tools for RNA structure alignment. An extension of the proposed method to multiple alignment of pseudoknot structures is also discussed. RKalign is implemented in Java and freely accessible on the Internet. As more and more pseudoknots are revealed, collected and stored in public databases, it is anticipated that a tool like RKalign will play a significant role in data comparison, annotation, analysis, and retrieval in these databases.
Author | : He Zengyou |
Publisher | : Woodhead Publishing |
Total Pages | : 100 |
Release | : 2015-06-09 |
Genre | : Computers |
ISBN | : 008100107X |
Download Data Mining for Bioinformatics Applications Book in PDF, ePub and Kindle
Data Mining for Bioinformatics Applications provides valuable information on the data mining methods have been widely used for solving real bioinformatics problems, including problem definition, data collection, data preprocessing, modeling, and validation. The text uses an example-based method to illustrate how to apply data mining techniques to solve real bioinformatics problems, containing 45 bioinformatics problems that have been investigated in recent research. For each example, the entire data mining process is described, ranging from data preprocessing to modeling and result validation. Provides valuable information on the data mining methods have been widely used for solving real bioinformatics problems Uses an example-based method to illustrate how to apply data mining techniques to solve real bioinformatics problems Contains 45 bioinformatics problems that have been investigated in recent research
Author | : Panos M. Pardalos |
Publisher | : Springer Science & Business Media |
Total Pages | : 577 |
Release | : 2008-12-10 |
Genre | : Medical |
ISBN | : 038769319X |
Download Data Mining in Biomedicine Book in PDF, ePub and Kindle
This volume presents an extensive collection of contributions covering aspects of the exciting and important research field of data mining techniques in biomedicine. Coverage includes new approaches for the analysis of biomedical data; applications of data mining techniques to real-life problems in medical practice; comprehensive reviews of recent trends in the field. The book addresses incorporation of data mining in fundamental areas of biomedical research: genomics, proteomics, protein characterization, and neuroscience.
Author | : Robert Winkler |
Publisher | : Royal Society of Chemistry |
Total Pages | : 460 |
Release | : 2020-03-19 |
Genre | : Science |
ISBN | : 1788017218 |
Download Processing Metabolomics and Proteomics Data with Open Software Book in PDF, ePub and Kindle
Metabolomics and proteomics allow deep insights into the chemistry and physiology of biological systems. This book expounds open-source programs, platforms and programming tools for analysing metabolomics and proteomics mass spectrometry data. In contrast to commercial software, open-source software is created by the academic community, which facilitates the direct interaction between users and developers and accelerates the implementation of new concepts and ideas. The first section of the book covers the basics of mass spectrometry, experimental strategies, data operations, the open-source philosophy, metabolomics, proteomics and statistics/ data mining. In the second section, active programmers and users describe available software packages. Included tutorials, datasets and code examples can be used for training and for building custom workflows. Finally, every reader is invited to participate in the open science movement.