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Book Fundamentals of Data Mining in Genomics and Proteomics

Download or read book Fundamentals of Data Mining in Genomics and Proteomics written by Werner Dubitzky and published by Springer Science & Business Media. This book was released on 2007-04-13 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Fundamentals Of Data Mining In Genomics And Proteomics

Download or read book Fundamentals Of Data Mining In Genomics And Proteomics written by Dubitzky Werner Et.Al and published by . This book was released on 2008-12-01 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Rechnergest  tzte Konstruktionsarbeit

Download or read book Rechnergest tzte Konstruktionsarbeit written by Siegfried Schreuder and published by . This book was released on 1989 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Data Mining for Genomics and Proteomics

Download or read book Data Mining for Genomics and Proteomics written by Darius M. Dziuda and published by John Wiley & Sons. This book was released on 2010-07-16 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Outlines and Highlights for Data Mining for Genomics and Proteomics

Download or read book Outlines and Highlights for Data Mining for Genomics and Proteomics written by Cram101 Textbook Reviews and published by Academic Internet Pub Incorporated. This book was released on 2011-04 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: Never HIGHLIGHT a Book Again! Virtually all of the testable terms, concepts, persons, places, and events from the textbook are included. Cram101 Just the FACTS101 studyguides give all of the outlines, highlights, notes, and quizzes for your textbook with optional online comprehensive practice tests. Only Cram101 is Textbook Specific. Accompanys: 9780470163733 .

Book Introduction to Data Mining for the Life Sciences

Download or read book Introduction to Data Mining for the Life Sciences written by Rob Sullivan and published by Springer Science & Business Media. This book was released on 2012-01-07 with total page 644 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining provides a set of new techniques to integrate, synthesize, and analyze tdata, uncovering the hidden patterns that exist within. Traditionally, techniques such as kernel learning methods, pattern recognition, and data mining, have been the domain of researchers in areas such as artificial intelligence, but leveraging these tools, techniques, and concepts against your data asset to identify problems early, understand interactions that exist and highlight previously unrealized relationships through the combination of these different disciplines can provide significant value for the investigator and her organization.

Book Data Mining in Proteomics

Download or read book Data Mining in Proteomics written by Michael Hamacher and published by Humana Press. This book was released on 2010-11-02 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Data Mining in Biomedicine

    Book Details:
  • Author : Panos M. Pardalos
  • Publisher : Springer Science & Business Media
  • Release : 2008-12-10
  • ISBN : 038769319X
  • Pages : 577 pages

Download or read book Data Mining in Biomedicine written by Panos M. Pardalos and published by Springer Science & Business Media. This book was released on 2008-12-10 with total page 577 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Studyguide for Data Mining for Genomics and Proteomics

Download or read book Studyguide for Data Mining for Genomics and Proteomics written by Cram101 Textbook Reviews and published by Cram101. This book was released on 2013-05 with total page 88 pages. Available in PDF, EPUB and Kindle. Book excerpt: Never HIGHLIGHT a Book Again Includes all testable terms, concepts, persons, places, and events. Cram101 Just the FACTS101 studyguides gives all of the outlines, highlights, and quizzes for your textbook with optional online comprehensive practice tests. Only Cram101 is Textbook Specific. Accompanies: 9780872893795. This item is printed on demand.

Book Biological Data Mining And Its Applications In Healthcare

Download or read book Biological Data Mining And Its Applications In Healthcare written by Xiaoli Li and published by World Scientific. This book was released on 2013-11-28 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biologists are stepping up their efforts in understanding the biological processes that underlie disease pathways in the clinical contexts. This has resulted in a flood of biological and clinical data from genomic and protein sequences, DNA microarrays, protein interactions, biomedical images, to disease pathways and electronic health records. To exploit these data for discovering new knowledge that can be translated into clinical applications, there are fundamental data analysis difficulties that have to be overcome. Practical issues such as handling noisy and incomplete data, processing compute-intensive tasks, and integrating various data sources, are new challenges faced by biologists in the post-genome era. This book will cover the fundamentals of state-of-the-art data mining techniques which have been designed to handle such challenging data analysis problems, and demonstrate with real applications how biologists and clinical scientists can employ data mining to enable them to make meaningful observations and discoveries from a wide array of heterogeneous data from molecular biology to pharmaceutical and clinical domains.

Book Biological Data Mining

Download or read book Biological Data Mining written by Jake Y. Chen and published by CRC Press. This book was released on 2009-09-01 with total page 736 pages. Available in PDF, EPUB and Kindle. Book excerpt: Like a data-guzzling turbo engine, advanced data mining has been powering post-genome biological studies for two decades. Reflecting this growth, Biological Data Mining presents comprehensive data mining concepts, theories, and applications in current biological and medical research. Each chapter is written by a distinguished team of interdisciplin

Book Data Analysis and Visualization in Genomics and Proteomics

Download or read book Data Analysis and Visualization in Genomics and Proteomics written by Francisco Azuaje and published by John Wiley & Sons. This book was released on 2005-06-24 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Book Data Mining for Bioinformatics

Download or read book Data Mining for Bioinformatics written by Sumeet Dua and published by CRC Press. This book was released on 2012-11-06 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 help readers from both biology and computer science backgrounds gain an enhanced understanding of this cross-disciplinary field. The book offers authoritative coverage of data mining techniques, technologies, and frameworks used for storing, analyzing, and extracting knowledge from large databases in the bioinformatics domains, including genomics and proteomics. It begins by describing the evolution of bioinformatics and highlighting the challenges that can be addressed using data mining techniques. Introducing the various data mining techniques that can be employed in biological databases, the text is organized into four sections: Supplies a complete overview of the evolution of the field and its intersection with computational learning Describes the role of data mining in analyzing large biological databases—explaining the breath of the various feature selection and feature extraction techniques that data mining has to offer Focuses on concepts of unsupervised learning using clustering techniques and its application to large biological data Covers supervised learning using classification techniques most commonly used in bioinformatics—addressing the need for validation and benchmarking of inferences derived using either clustering or classification The book describes the various biological databases prominently referred to in bioinformatics and includes a detailed list of the applications of advanced clustering algorithms used in bioinformatics. Highlighting the challenges encountered during the application of classification on biological databases, it considers systems of both single and ensemble classifiers and shares effort-saving tips for model selection and performance estimation strategies.

Book Data Mining  Foundations and Intelligent Paradigms

Download or read book Data Mining Foundations and Intelligent Paradigms written by Dawn E. Holmes and published by Springer Science & Business Media. This book was released on 2012-01-12 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: There are many invaluable books available on data mining theory and applications. However, in compiling a volume titled “DATA MINING: Foundations and Intelligent Paradigms: Volume 3: Medical, Health, Social, Biological and other Applications” we wish to introduce some of the latest developments to a broad audience of both specialists and non-specialists in this field.

Book ECML PKDD 2007

    Book Details:
  • Author : A. Fazel Famili
  • Publisher :
  • Release : 2007
  • ISBN :
  • Pages : 110 pages

Download or read book ECML PKDD 2007 written by A. Fazel Famili and published by . This book was released on 2007 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Data Mining in Bioinformatics

Download or read book Data Mining in Bioinformatics written by Jason T. L. Wang and published by Springer Science & Business Media. This book was released on 2005 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written especially for computer scientists, all necessary biology is explained. Presents new techniques on gene expression data mining, gene mapping for disease detection, and phylogenetic knowledge discovery.

Book Data Mining in Computational Proteomics and Genomics

Download or read book Data Mining in Computational Proteomics and Genomics written by Yang Song and published by . This book was released on 2015 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.