Life Science Data Mining
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Life Science Data Mining
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Author : Chung-sheng Li
language : en
Publisher: World Scientific
Release Date : 2006-12-29
Life Science Data Mining written by Chung-sheng Li and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-12-29 with Science categories.
This timely book identifies and highlights the latest data mining paradigms to analyze, combine, integrate, model and simulate vast amounts of heterogeneous multi-modal, multi-scale data for emerging real-world applications in life science.The cutting-edge topics presented include bio-surveillance, disease outbreak detection, high throughput bioimaging, drug screening, predictive toxicology, biosensors, and the integration of macro-scale bio-surveillance and environmental data with micro-scale biological data for personalized medicine. This collection of works from leading researchers in the field offers readers an exceptional start in these areas.
Data Mining Techniques For The Life Sciences
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Author : Oliviero Carugo
language : en
Publisher: Humana
Release Date : 2016-08-23
Data Mining Techniques For The Life Sciences written by Oliviero Carugo and has been published by Humana this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-23 with Science categories.
Most life science researchers will agree that biology is not a truly theoretical branch of science. The hype around computational biology and bioinformatics beginning in the nineties of the 20th century was to be short lived (1, 2). When almost no value of practical importance such as the optimal dose of a drug or the three-dimensional structure of an orphan protein can be computed from fundamental principles, it is still more straightforward to determine them experimentally. Thus, experiments and observationsdogeneratetheoverwhelmingpartofinsightsintobiologyandmedicine. The extrapolation depth and the prediction power of the theoretical argument in life sciences still have a long way to go. Yet, two trends have qualitatively changed the way how biological research is done today. The number of researchers has dramatically grown and they, armed with the same protocols, have produced lots of similarly structured data. Finally, high-throu- put technologies such as DNA sequencing or array-based expression profiling have been around for just a decade. Nevertheless, with their high level of uniform data generation, they reach the threshold of totally describing a living organism at the biomolecular level for the first time in human history. Whereas getting exact data about living systems and the sophistication of experimental procedures have primarily absorbed the minds of researchers previously, the weight increasingly shifts to the problem of interpreting accumulated data in terms of biological function and bio- lecular mechanisms.
Biological Data Mining And Its Applications In Healthcare
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Author : Xiaoli Li
language : en
Publisher: World Scientific
Release Date : 2013-11-28
Biological Data Mining And Its Applications In Healthcare written by Xiaoli Li and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-28 with Science categories.
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.
Advanced Data Mining Technologies In Bioinformatics
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Author : Hui-Huang Hsu
language : en
Publisher: IGI Global
Release Date : 2006-01-01
Advanced Data Mining Technologies In Bioinformatics written by Hui-Huang Hsu and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-01-01 with Computers categories.
"This book covers research topics of data mining on bioinformatics presenting the basics and problems of bioinformatics and applications of data mining technologies pertaining to the field"--Provided by publisher.
Computational Life Sciences
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Author : Jens Dörpinghaus
language : en
Publisher: Springer Nature
Release Date : 2023-03-04
Computational Life Sciences written by Jens Dörpinghaus and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-04 with Computers categories.
This book broadly covers the given spectrum of disciplines in Computational Life Sciences, transforming it into a strong helping hand for teachers, students, practitioners and researchers. In Life Sciences, problem-solving and data analysis often depend on biological expertise combined with technical skills in order to generate, manage and efficiently analyse big data. These technical skills can easily be enhanced by good theoretical foundations, developed from well-chosen practical examples and inspiring new strategies. This is the innovative approach of Computational Life Sciences-Data Engineering and Data Mining for Life Sciences: We present basic concepts, advanced topics and emerging technologies, introduce algorithm design and programming principles, address data mining and knowledge discovery as well as applications arising from real projects. Chapters are largely independent and often flanked by illustrative examples and practical advise.
Fundamentals Of Data Mining In Genomics And Proteomics
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Author : Werner Dubitzky
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-04-13
Fundamentals Of Data Mining In Genomics And Proteomics written by Werner Dubitzky and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-04-13 with Science categories.
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.
Big Data Mining For Climate Change
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Author : Zhihua Zhang
language : en
Publisher: Elsevier
Release Date : 2019-11-20
Big Data Mining For Climate Change written by Zhihua Zhang and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-20 with Science categories.
Climate change mechanisms, impacts, risks, mitigation, adaption, and governance are widely recognized as the biggest, most interconnected problem facing humanity. Big Data Mining for Climate Change addresses one of the fundamental issues facing scientists of climate or the environment: how to manage the vast amount of information available and analyse it. The resulting integrated and interdisciplinary big data mining approaches are emerging, partially with the help of the United Nation's big data climate challenge, some of which are recommended widely as new approaches for climate change research. Big Data Mining for Climate Change delivers a rich understanding of climate-related big data techniques and highlights how to navigate huge amount of climate data and resources available using big data applications. It guides future directions and will boom big-data-driven researches on modeling, diagnosing and predicting climate change and mitigating related impacts. This book mainly focuses on climate network models, deep learning techniques for climate dynamics, automated feature extraction of climate variability, and sparsification of big climate data. It also includes a revelatory exploration of big-data-driven low-carbon economy and management. Its content provides cutting-edge knowledge for scientists and advanced students studying climate change from various disciplines, including atmospheric, oceanic and environmental sciences; geography, ecology, energy, economics, management, engineering, and public policy.
Data Mining And Analysis
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Author : Mohammed J. Zaki
language : en
Publisher: Cambridge University Press
Release Date : 2014-05-12
Data Mining And Analysis written by Mohammed J. Zaki and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-12 with Computers categories.
A comprehensive overview of data mining from an algorithmic perspective, integrating related concepts from machine learning and statistics.
Data Mining Techniques For The Life Sciences
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Author : Oliviero Carugo
language : en
Publisher: Humana
Release Date : 2022-05-05
Data Mining Techniques For The Life Sciences written by Oliviero Carugo and has been published by Humana this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-05 with Science categories.
This third edition details new and updated methods and protocols on important databases and data mining tools. Chapters guides readers through archives of macromolecular sequences and three-dimensional structures, databases of protein-protein interactions, methods for prediction conformational disorder, mutant thermodynamic stability, aggregation, and drug response. Quality of structural data and their release, soft mechanics applications in biology, and protein flexibility are considered, too, together with pan-genome analyses, rational drug combination screening and Omics Deep Mining. Written in the format of the highly successful Methods in Molecular Biology series, each chapter includes an introduction to the topic, lists necessary materials, includes step-by-step, readily reproducible protocols. Authoritative and cutting-edge, Data Mining Techniques for the Life Sciences, Third Edition aims to be a practical guide to researches to help further their study in this field.
Data Integration In The Life Sciences
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Author : Helena Galhardas
language : en
Publisher: Springer
Release Date : 2014-07-05
Data Integration In The Life Sciences written by Helena Galhardas and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-05 with Computers categories.
This book constitutes the refereed proceedings of the 10th International Conference on Data Integration in the Life Sciences, DILS 2014, held in Lisbon, Portugal, in July 2014. The 9 revised full papers and the 5 short papers included in this volume were carefully reviewed and selected from 20 submissions. The papers cover a range of important topics such as data integration platforms and applications; biodiversity data management; ontologies and visualization; linked data and query processing.