Data Mining For Biomarker Discovery

Data Mining for Biomarker Discovery PDF
Author: Panos M. Pardalos
Publisher: Springer Science & Business Media
ISBN: 1461421071
Size: 76.18 MB
Format: PDF, ePub, Docs
Category : Business & Economics
Languages : en
Pages : 246
View: 5774

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Book Description: Biomarker discovery is an important area of biomedical research that may lead to significant breakthroughs in disease analysis and targeted therapy. Biomarkers are biological entities whose alterations are measurable and are characteristic of a particular biological condition. Discovering, managing, and interpreting knowledge of new biomarkers are challenging and attractive problems in the emerging field of biomedical informatics. This volume is a collection of state-of-the-art research into the application of data mining to the discovery and analysis of new biomarkers. Presenting new results, models and algorithms, the included contributions focus on biomarker data integration, information retrieval methods, and statistical machine learning techniques. This volume is intended for students, and researchers in bioinformatics, proteomics, and genomics, as well engineers and applied scientists interested in the interdisciplinary application of data mining techniques.

Data Mining For Genomics And Proteomics

Data Mining for Genomics and Proteomics PDF
Author: Darius M. Dziuda
Publisher: John Wiley & Sons
ISBN: 9780470593400
Size: 48.13 MB
Format: PDF, ePub, Docs
Category : Computers
Languages : en
Pages : 328
View: 2181

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Book Description: 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.

Successes And New Directions In Data Mining

Successes and New Directions in Data Mining PDF
Author: Florent Masseglia
Publisher: IGI Global
ISBN: 1599046458
Size: 57.73 MB
Format: PDF, ePub
Category : Computers
Languages : en
Pages : 369
View: 102

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Book Description: "This book addresses existing solutions for data mining, with particular emphasis on potential real-world applications. It captures defining research on topics such as fuzzy set theory, clustering algorithms, semi-supervised clustering, modeling and managing data mining patterns, and sequence motif mining"--Provided by publisher.

Data Warehousing And Mining Concepts Methodologies Tools And Applications

Data Warehousing and Mining  Concepts  Methodologies  Tools  and Applications PDF
Author: Wang, John
Publisher: IGI Global
ISBN: 159904952X
Size: 50.79 MB
Format: PDF
Category : Technology & Engineering
Languages : en
Pages : 4092
View: 6014

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Book Description: In recent years, the science of managing and analyzing large datasets has emerged as a critical area of research. In the race to answer vital questions and make knowledgeable decisions, impressive amounts of data are now being generated at a rapid pace, increasing the opportunities and challenges associated with the ability to effectively analyze this data.

Bioinformatics And Biomarker Discovery

Bioinformatics and Biomarker Discovery PDF
Author: Francisco Azuaje
Publisher: John Wiley & Sons
ISBN: 111996430X
Size: 48.51 MB
Format: PDF, Kindle
Category : Computers
Languages : en
Pages : 248
View: 4587

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Book Description: This book is designed to introduce biologists, clinicians and computational researchers to fundamental data analysis principles, techniques and tools for supporting the discovery of biomarkers and the implementation of diagnostic/prognostic systems. The focus of the book is on how fundamental statistical and data mining approaches can support biomarker discovery and evaluation, emphasising applications based on different types of "omic" data. The book also discusses design factors, requirements and techniques for disease screening, diagnostic and prognostic applications. Readers are provided with the knowledge needed to assess the requirements, computational approaches and outputs in disease biomarker research. Commentaries from guest experts are also included, containing detailed discussions of methodologies and applications based on specific types of "omic" data, as well as their integration. Covers the main range of data sources currently used for biomarker discovery Covers the main range of data sources currently used for biomarker discovery Puts emphasis on concepts, design principles and methodologies that can be extended or tailored to more specific applications Offers principles and methods for assessing the bioinformatic/biostatistic limitations, strengths and challenges in biomarker discovery studies Discusses systems biology approaches and applications Includes expert chapter commentaries to further discuss relevance of techniques, summarize biological/clinical implications and provide alternative interpretations

Biological Data Mining

Biological Data Mining PDF
Author: Jake Y. Chen
Publisher: CRC Press
ISBN: 9781420086850
Size: 30.97 MB
Format: PDF
Category : Computers
Languages : en
Pages : 733
View: 266

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Book Description: 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 interdisciplinary data mining researchers who cover state-of-the-art biological topics. The first section of the book discusses challenges and opportunities in analyzing and mining biological sequences and structures to gain insight into molecular functions. The second section addresses emerging computational challenges in interpreting high-throughput Omics data. The book then describes the relationships between data mining and related areas of computing, including knowledge representation, information retrieval, and data integration for structured and unstructured biological data. The last part explores emerging data mining opportunities for biomedical applications. This volume examines the concepts, problems, progress, and trends in developing and applying new data mining techniques to the rapidly growing field of genome biology. By studying the concepts and case studies presented, readers will gain significant insight and develop practical solutions for similar biological data mining projects in the future.

Acta Biochimica Polonica

Acta Biochimica Polonica PDF
Author:
Publisher:
ISBN:
Size: 75.78 MB
Format: PDF, Mobi
Category : Biochemistry
Languages : en
Pages :
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Book Description:

Data Mining For Biomedical Applications

Data Mining for Biomedical Applications PDF
Author: Jinyan Li
Publisher: Springer Science & Business Media
ISBN: 3540331042
Size: 17.88 MB
Format: PDF, ePub, Mobi
Category : Computers
Languages : en
Pages : 155
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Book Description: This book constitutes the refereed proceedings of the International Workshop on Data Mining for Biomedical Applications, BioDM 2006, held in Singapore in conjunction with the 10th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2006). The 14 revised full papers presented together with one keynote talk were carefully reviewed and selected from 35 submissions. The papers are organized in topical sections

Mining Gene Expression Data Generated By Next Generation Sequencing Technology

Mining Gene Expression Data Generated by Next Generation Sequencing Technology PDF
Author: Jyota D. Snyder
Publisher:
ISBN:
Size: 72.11 MB
Format: PDF, Kindle
Category : Data mining
Languages : en
Pages : 144
View: 1561

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Book Description: Next generation DNA sequencing (NGS) technology has emerged as a result of genomic research progress made related to the Human Genome Project. A protocol of this technology, called RNA-seq, was designed to sequence RNA transcripts from biological samples. The quantification of gene expression levels using RNA-seq has been predicted to replace microarrays for gene expression profiling. Multivariate data mining methods have been used with microarray gene expression data for determining parsimonious biomarkers that can accurately discriminate between biological classes. At the time of this writing, there was scarce research literature related to multivariate data mining based approaches for biomarker discovery with RNA-seq gene expression data. This study investigated whether current RNA-seq technology (including preprocessing steps that transform raw data into a gene expression matrix) provides data that can be successfully used for multivariate biomarker discovery (that is, to provide multivariate biomarkers with high sensitivity and specificity). The preprocessing performed for this study involved applying upper quartile normalization and log2 transformation to a training set of 452 lung adenocarcinoma samples obtained from The Cancer Genome Atlas and examining the effect of such transformation on the data. Afterwards, an eight gene biomarker was found from the training data using multivariate data mining methods, and the marker was validated with the use of an independent test data set obtained from a study in which 164 biological samples were sequenced using the same NGS technology as utilized for the training data set. The classification of the independent test data set indicated that the biomarker had 97.7% sensitivity and 94.8% specificity. Since these classification metrics were relatively high and the training and test data sets were collected by different labs in different countries, this provided evidence that such data can be adequately prepared for use with the advanced data mining methods for biomarker discovery that are used to analyze microarray gene expression data.

Next Generation Of Data Mining Applications

Next Generation of Data Mining Applications PDF
Author: Mehmed Kantardzic
Publisher: Wiley-IEEE Press
ISBN:
Size: 27.64 MB
Format: PDF, ePub
Category : Computers
Languages : en
Pages : 671
View: 390

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Book Description: Discover the next generation of data-mining tools and technology This book brings together an international team of eighty experts to present readers with the next generation of data-mining applications. Unlike other publications that take a strictly academic and theoretical approach, this book features authors who have successfully developed data-mining solutions for a variety of customer types. Presenting their state-of-the-art methodologies and techniques, the authors show readers how they can analyze enormous quantities of data and make new discoveries by connecting key pieces of data that may be spread across several different databases and file servers. The latest data-mining techniques that will revolutionize research across a wide variety of fields including business, science, healthcare, and industry are all presented. Organized by application, the twenty-five chapters cover applications in: Industry and business Science and engineering Bioinformatics and biotechnology Medicine and pharmaceuticals Web and text-mining Security New trends in data-mining technology And much more . . . Readers from a variety of disciplines will learn how the next generation of data-mining applications can radically enhance their ability to analyze data and open the doors to new opportunities. Readers will discover: New data-mining tools to automate the evaluation and qualification of sales opportunities The latest tools needed for gene mapping and proteomic data analysis Sophisticated techniques that can be engaged in crime fighting and prevention With its coverage of the most advanced applications, Next Generation of Data-Mining Applications is essential reading for all researchers working in data mining or who are tasked with making sense of an ever-growing quantity of data. The publication also serves as an excellent textbook for upper-level undergraduate and graduate courses in computer science, information management, and statistics.