Data Mining In Computational Proteomics And Genomics PDF Download
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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 | : 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 | : 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 | : Jason T. L. Wang |
Publisher | : World Scientific |
Total Pages | : 266 |
Release | : 2003 |
Genre | : Science |
ISBN | : 9812382577 |
Download Computational Biology and Genome Informatics Book in PDF, ePub and Kindle
This book contains articles written by experts on a wide range of topics that are associated with the analysis and management of biological information at the molecular level. It contains chapters on RNA and protein structure analysis, DNA computing, sequence mapping, genome comparison, gene expression data mining, metabolic network modeling, and phyloinformatics. The important work of some representative researchers in bioinformatics is brought together for the first time in one volume. The topic is treated in depth and is related to, where applicable, other emerging technologies such as data mining and visualization. The goal of the book is to introduce readers to the principle techniques of bioinformatics in the hope that they will build on them to make new discoveries of their own. Contents: Exploring RNA Intermediate Conformations with the Massively Parallel Genetic Algorithm; Introduction to Self-Assembling DNA Nanostructures for Computation and Nanofabrication; Mapping Sequence to Rice FPC; Graph Theoretic Sequence Clustering Algorithms and their Applications to Genome Comparison; The Protein Information Resource for Functional Genomics and Proteomics; High-Grade Ore for Data Mining in 3D Structures; Protein Classification: A Geometric Hashing Approach; Interrelated Clustering: An Approach for Gene Expression Data Analysis; Creating Metabolic Network Models Using Text Mining and Expert Knowledge; Phyloinformatics and Tree Networks. Readership: Molecular biologists who rely on computers and mathematical scientists with interests in biology.
Author | : Sumeet Dua |
Publisher | : CRC Press |
Total Pages | : 351 |
Release | : 2012-11-06 |
Genre | : Computers |
ISBN | : 1466588667 |
Download Data Mining for Bioinformatics Book in PDF, ePub and Kindle
Covering theory, algorithms, and methodologies, as well as data mining technologies, Data Mining for Bioinformatics provides a comprehensive discussion of data-intensive computations used in data mining with applications in bioinformatics. It supplies a broad, yet in-depth, overview of the application domains of data mining for bioinformatics to he
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 | : Soumya Raychaudhuri |
Publisher | : OUP Oxford |
Total Pages | : 312 |
Release | : 2006-01-26 |
Genre | : Science |
ISBN | : 0191513776 |
Download Computational Text Analysis Book in PDF, ePub and Kindle
This book brings together the two disparate worlds of computational text analysis and biology and presents some of the latest methods and applications to proteomics, sequence analysis and gene expression data. Modern genomics generates large and comprehensive data sets but their interpretation requires an understanding of a vast number of genes, their complex functions, and interactions. Keeping up with the literature on a single gene is a challenge itself-for thousands of genes it is simply. impossible. Here, Soumya Raychaudhuri presents the techniques and algorithms needed to access and utilize the vast scientific text, i.e. methods that automatically read the literature on all the genes. Including background chapters on the necessary biology, statistics and genomics, in addition to practical examples of interpreting many different types of modern experiments, this book is ideal for students and researchers in computational biology, bioinformatics, genomics, statistics and computer science
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 | : J. Perry Gustafson |
Publisher | : Springer Science & Business Media |
Total Pages | : 257 |
Release | : 2007-05-11 |
Genre | : Science |
ISBN | : 0387241876 |
Download Genome Exploitation Book in PDF, ePub and Kindle
Genome Exploitation: Data Mining the Genome is developed from the 23rd Stadler Genetic Symposium. This volume discusses and illustrates how scientists are going to characterize and make use of the massive amount of information being accumulated about the plant and animal genomes. Genome Exploitation: Data Mining the Genome is a state-of-the-art picture on mining the Genome databases. This is one of the few times that researchers in both plants and animals will be working together to create a seminal data resource.
Author | : Francisco Azuaje |
Publisher | : John Wiley & Sons |
Total Pages | : 284 |
Release | : 2005-06-24 |
Genre | : Science |
ISBN | : 0470094400 |
Download Data Analysis and Visualization in Genomics and Proteomics Book in PDF, ePub and Kindle
Data Analysis and Visualization in Genomics and Proteomics is the first book addressing integrative data analysis and visualization in this field. It addresses important techniques for the interpretation of data originating from multiple sources, encoded in different formats or protocols, and processed by multiple systems. One of the first systematic overviews of the problem of biological data integration using computational approaches This book provides scientists and students with the basis for the development and application of integrative computational methods to analyse biological data on a systemic scale Places emphasis on the processing of multiple data and knowledge resources, and the combination of different models and systems