data-mining-techniques-for-the-life-sciences

Download Book Data Mining Techniques For The Life Sciences in PDF format. You can Read Online Data Mining Techniques For The Life Sciences here in PDF, EPUB, Mobi or Docx formats.

Data Mining Techniques For The Life Sciences

Author : Oliviero Carugo
ISBN : 1071620940
Genre : Science
File Size : 34. 33 MB
Format : PDF, Mobi
Download : 234
Read : 1077

Get This Book


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.

Introduction To Data Mining For The Life Sciences

Author : Rob Sullivan
ISBN : 9781597452908
Genre : Science
File Size : 21. 81 MB
Format : PDF, ePub, Mobi
Download : 778
Read : 474

Get This Book


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.

Life Science Data Mining

Author :
ISBN : 9789814476829
Genre :
File Size : 86. 26 MB
Format : PDF, ePub, Docs
Download : 295
Read : 1247

Get This Book



Handbook Of Research On Computational Grid Technologies For Life Sciences Biomedicine And Healthcare

Author : Cannataro, Mario
ISBN : 9781605663753
Genre : Medical
File Size : 50. 38 MB
Format : PDF, Mobi
Download : 336
Read : 576

Get This Book


"This book provides methodologies and developments of grid technologies applied in different fields of life sciences"--Provided by publisher.

Data Integration In The Life Sciences

Author : Patrick Lambrix
ISBN : 9783642151194
Genre : Science
File Size : 35. 28 MB
Format : PDF
Download : 801
Read : 701

Get This Book


The development and increasingly widespread deployment of high-throughput experimental methods in the life sciences is giving rise to numerous large, c- plex and valuable data resources. This foundation of experimental data und- pins the systematic study of organismsand diseases, which increasinglydepends on the development of models of biological systems. The development of these models often requires integration of diverse experimental data resources; once constructed, the models themselves become data and present new integration challenges for tasks such as interpretation, validation and comparison. The Data Integration in the Life Sciences (DILS) Conference series brings together data and knowledge management researchers from the computer s- ence research community with bioinformaticians and computational biologists, to improve the understanding of how emerging data integration techniques can address requirements identi?ed in the life sciences. DILS 2010 was the seventh event in the series and was held in Goth- burg, Sweden during August 25–27, 2010. The associated proceedings contain 14 peer-reviewed papers and 2 invited papers. The sessions addressed ontology engineering, and in particular, evolution, matching and debugging of ontologies, akeycomponentforsemanticintegration;Web servicesasanimportanttechn- ogy for data integration in the life sciences; data and text mining techniques for discovering and recognizing biomedical entities and relationships between these entities; and information management, introducing data integration solutions for di?erent types of applications related to cancer, systems biology and - croarray experimental data, and an approach for integrating ranked data in the life sciences.

Database Technology For Life Sciences And Medicine

Author :
ISBN : 9789814464819
Genre :
File Size : 85. 67 MB
Format : PDF, ePub, Mobi
Download : 749
Read : 1295

Get This Book



Biological Data Mining And Its Applications In Healthcare

Author : Xiaoli Li
ISBN : 9789814551021
Genre : Computers
File Size : 83. 6 MB
Format : PDF
Download : 712
Read : 308

Get This Book


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. Contents:Sequence Analysis:Mining the Sequence Databases for Homology Detection: Application to Recognition of Functions of Trypanosoma brucei brucei Proteins and Drug Targets (G Ramakrishnan, V S Gowri, R Mudgal, N R Chandra and N Srinivasan)Identification of Genes and Their Regulatory Regions Based on Multiple Physical and Structural Properties of a DNA Sequence (Xi Yang, Nancy Yu Song and Hong Yan)Mining Genomic Sequence Data for Related Sequences Using Pairwise Statistical Significance (Yuhong Zhang and Yunbo Rao)Biological Network Mining:Indexing for Similarity Queries on Biological Networks (Günhan Gülsoy, Md Mahmudul Hasan, Yusuf Kavurucu and Tamer Kahveci)Theory and Method of Completion for a Boolean Regulatory Network Using Observed Data (Takeyuki Tamura and Tatsuya Akutsu)Mining Frequent Subgraph Patterns for Classifying Biological Data (Saeed Salem)On the Integration of Prior Knowledge in the Inference of Regulatory Networks (Catharina Olsen, Benjamin Haibe-Kains, John Quackenbush and Gianluca Bontempi)Classification, Trend Analysis and 3D Medical Images:Classification and Its Application to Drug-Target Prediction (Jian-Ping Mei, Chee-Keong Kwoh, Peng Yang and Xiao-Li Li)Characterization and Prediction of Human Protein-Protein Interactions (Yi Xiong, Dan Syzmanski and Daisuke Kihara)Trend Analysis (Wen-Chuan Xie, Miao He and Jake Yue Chen)Data Acquisition and Preprocessing on Three Dimensional Medical Images (Yuhua Jiao, Liang Chen and Jin Chen)Text Mining and Its Biomedical Applications:Text Mining in Biomedicine and Healthcare (Hong-Jie Dai, Chi-Yang Wu, Richard Tzong-Han Tsai and Wen-Lian Hsu)Learning to Rank Biomedical Documents with Only Positive and Unlabeled Examples: A Case Study (Mingzhu Zhu, Yi-Fang Brook Wu, Meghana Samir Vasavada and Jason T L Wang)Automated Mining of Disease-Specific Protein Interaction Networks Based on Biomedical Literature (Rajesh Chowdhary, Boris R Jankovic, Rachel V Stankowski, John A C Archer, Xiangliang Zhang, Xin Gao, Vladimir B Bajic) Readership: Students, professionals, those who perform biological, medical and bioinformatics research. Keywords:Healthcare;Data Mining;Biological Data Mining;Protein Interactions;Gene Regulation;Text Mining;Biological Literature Mining;Drug Discovery;Disease Network;Biological Network;Graph Mining;Sequence Analysis;Structure Analysis;Trend Analysis;Medical ImagesKey Features:Each chapter of this book will include a section to introduce a specific class of data mining techniques, which will be written in a tutorial style so that even non-computational readers such as biologists and healthcare researchers can appreciate themThe book will disseminate the impact research results and best practices of data mining approaches to the cross-disciplinary researchers and practitioners from both the data mining disciplines and the life sciences domains. The authors of the book will be well-known data mining experts, bioinformaticians and cliniciansEach chapter will also provide a detailed description on how to apply the data mining techniques in real-world biological and clinical applications. Thus, readers of this book can easily appreciate the computational techniques and how they can be used to address their own research issues

Data Integration In The Life Sciences

Author : Bertram Ludäscher
ISBN : 9783540279679
Genre : Computers
File Size : 59. 32 MB
Format : PDF, ePub
Download : 225
Read : 155

Get This Book


This book constitutes the refereed proceedings of the Second International Workshop on Data Integration in the Life Sciences, DILS 2005, held in San Diego, CA, USA in July 2005. The 20 revised full papers presented together with 8 revised posters and demonstration papers, 2 keynote articles and 5 invited position statements were carefully reviewed and selected from 50 initial submissions. The papers are organized in topical sections on user applications, ontologies, data integration, and others and address all current issues in data integration from the life science point of view.

Data Mining Techniques In Grid Computing Environments

Author : Werner Dubitzky
ISBN : 9780470699898
Genre : Medical
File Size : 86. 4 MB
Format : PDF, ePub, Docs
Download : 818
Read : 866

Get This Book


Based around eleven international real life case studies and including contributions from leading experts in the field this groundbreaking book explores the need for the grid-enabling of data mining applications and provides a comprehensive study of the technology, techniques and management skills necessary to create them. This book provides a simultaneous design blueprint, user guide, and research agenda for current and future developments and will appeal to a broad audience; from developers and users of data mining and grid technology, to advanced undergraduate and postgraduate students interested in this field.

Data Mining For Systems Biology

Author : Hiroshi Mamitsuka
ISBN : 1493985612
Genre : Data mining
File Size : 44. 27 MB
Format : PDF, ePub, Mobi
Download : 854
Read : 734

Get This Book



Java Data Mining Strategy Standard And Practice

Author : Mark F. Hornick
ISBN : 0080495915
Genre : Computers
File Size : 62. 82 MB
Format : PDF, ePub, Mobi
Download : 219
Read : 1256

Get This Book


Whether you are a software developer, systems architect, data analyst, or business analyst, if you want to take advantage of data mining in the development of advanced analytic applications, Java Data Mining, JDM, the new standard now implemented in core DBMS and data mining/analysis software, is a key solution component. This book is the essential guide to the usage of the JDM standard interface, written by contributors to the JDM standard. Data mining introduction - an overview of data mining and the problems it can address across industries; JDM's place in strategic solutions to data mining-related problems JDM essentials - concepts, design approach and design issues, with detailed code examples in Java; a Web Services interface to enable JDM functionality in an SOA environment; and illustration of JDM XML Schema for JDM objects JDM in practice - the use of JDM from vendor implementations and approaches to customer applications, integration, and usage; impact of data mining on IT infrastructure; a how-to guide for building applications that use the JDM API Free, downloadable KJDM source code referenced in the book available here

Identifying Product And Process State Drivers In Manufacturing Systems Using Supervised Machine Learning

Author : Thorsten Wuest
ISBN : 9783319176116
Genre : Technology & Engineering
File Size : 81. 46 MB
Format : PDF, Kindle
Download : 390
Read : 1171

Get This Book


The book reports on a novel approach for holistically identifying the relevant state drivers of complex, multi-stage manufacturing systems. This approach is able to utilize complex, diverse and high-dimensional data sets, which often occur in manufacturing applications, and to integrate the important process intra- and interrelations. The approach has been evaluated using three scenarios from different manufacturing domains (aviation, chemical and semiconductor). The results, which are reported in detail in this book, confirmed that it is possible to incorporate implicit process intra- and interrelations on both a process and programme level by applying SVM-based feature ranking. In practice, this method can be used to identify the most important process parameters and state characteristics, the so-called state drivers, of a manufacturing system. Given the increasing availability of data and information, this selection support can be directly utilized in, e.g., quality monitoring and advanced process control. Importantly, the method is neither limited to specific products, manufacturing processes or systems, nor by specific quality concepts.

Data Mining For Bioinformatics Applications

Author : He Zengyou
ISBN : 9780081001073
Genre : Computers
File Size : 81. 32 MB
Format : PDF
Download : 975
Read : 415

Get This Book


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

Data Mining And Data Warehousing

Author : Barbara Mento
ISBN : UOM:39015052882167
Genre : Data mining
File Size : 43. 56 MB
Format : PDF, Docs
Download : 868
Read : 1243

Get This Book


"The goal of this survey was to determine the extent to which data mining technology is being used by ARL member institutions, researchers, libraries and and administrations. The survey also hoped to elicit ideas and opinions concerning the potential role of libraries in supporting data mining and data warehousing in research institutions. The first seven survey questions focus on data mining and data warehousing activities at the institutional level. The remaining questions explore the current library use of data mining technology and opportunities for future use. Since data warehouses are the foundation of data mining, several questions focused on current support and future plans for data warehousing. The survey was sent to 124 ARL member libraries. Sixty-five (52%) responded to the survey"--P. 9.

Data Mining

Author :
ISBN : 9781839692666
Genre : Computers
File Size : 46. 37 MB
Format : PDF
Download : 488
Read : 397

Get This Book


The availability of big data due to computerization and automation has generated an urgent need for new techniques to analyze and convert big data into useful information and knowledge. Data mining is a promising and leading-edge technology for mining large volumes of data, looking for hidden information, and aiding knowledge discovery. It can be used for characterization, classification, discrimination, anomaly detection, association, clustering, trend or evolution prediction, and much more in fields such as science, medicine, economics, engineering, computers, and even business analytics. This book presents basic concepts, ideas, and research in data mining.

New Contributions In Information Systems And Technologies

Author : Alvaro Rocha
ISBN : 9783319165288
Genre : Technology & Engineering
File Size : 53. 70 MB
Format : PDF, Mobi
Download : 783
Read : 439

Get This Book


This book contains a selection of articles from The 2015 World Conference on Information Systems and Technologies (WorldCIST'15), held between the 1st and 3rd of April in Funchal, Madeira, Portugal, a global forum for researchers and practitioners to present and discuss recent results and innovations, current trends, professional experiences and challenges of modern Information Systems and Technologies research, technological development and applications. The main topics covered are: Information and Knowledge Management; Organizational Models and Information Systems; Intelligent and Decision Support Systems; Big Data Analytics and Applications; Software Systems, Architectures, Applications and Tools; Multimedia Systems and Applications; Computer Networks, Mobility and Pervasive Systems; Human-Computer Interaction; Health Informatics; Information Technologies in Education; Information Technologies in Radio communications.

Introduction To Data Mining And Its Applications

Author : S. Sumathi
ISBN : 9783540343509
Genre : Computers
File Size : 41. 43 MB
Format : PDF, ePub, Docs
Download : 346
Read : 891

Get This Book


This book explores the concepts of data mining and data warehousing, a promising and flourishing frontier in data base systems and new data base applications and is also designed to give a broad, yet in-depth overview of the field of data mining. Data mining is a multidisciplinary field, drawing work from areas including database technology, AI, machine learning, NN, statistics, pattern recognition, knowledge based systems, knowledge acquisition, information retrieval, high performance computing and data visualization. This book is intended for a wide audience of readers who are not necessarily experts in data warehousing and data mining, but are interested in receiving a general introduction to these areas and their many practical applications. Since data mining technology has become a hot topic not only among academic students but also for decision makers, it provides valuable hidden business and scientific intelligence from a large amount of historical data. It is also written for technical managers and executives as well as for technologists interested in learning about data mining.

Knowledge Exploration In Life Science Informatics

Author : Jesús A. López
ISBN : 9783540304784
Genre : Computers
File Size : 44. 13 MB
Format : PDF, Docs
Download : 674
Read : 387

Get This Book


This volume of the Springer Lecture Notes in Computer Science series contains the contributions presented at the International Symposium on Knowledge Exploration in Life Science Informatics (KELSI 2004) held in Milan, Italy, 25-26 November 2004. The two main objectives of the symposium were: • To explore the symbiosis between information and knowledge technologies and v- ious life science disciplines, such as biochemistry, biology, neuroscience, medical research, social sciences, and so on. • To investigate the synergy among different life science informatics areas, including cheminformatics,bioinformatics,neuroinformatics,medical informatics,systems - ology, socionics, and others. Modern life sciences investigate phenomena and systems at the level of molecules, cells, tissues, organisms, and populations. Typical areas of interest include natural e- lution, development,disease, behavior,cognition,and consciousness.This quest is g- eratinganoverwhelmingandfast-growingamountofdata,information,andknowledge, re?ecting living systems at different levels of organization. Future progress of the life sciences will depend on effective and ef?cient management, sharing, and exploitation of these resources by computational means.

Advances In Data Mining Applications And Theoretical Aspects

Author : Petra Perner
ISBN : 9783319209104
Genre : Computers
File Size : 37. 35 MB
Format : PDF, Docs
Download : 877
Read : 1064

Get This Book


This book constitutes the refereed proceedings of the 15th Industrial Conference on Advances in Data Mining, ICDM 2015, held in Hamburg, Germany, in July 2015. The 16 revised full papers presented were carefully reviewed and selected from numerous submissions. The topics range from theoretical aspects of data mining to applications of data mining, such as in multimedia data, in marketing, in medicine and agriculture, and in process control, industry and society.

Computational Life Sciences

Author : Michael R. Berthold
ISBN : 9783540291046
Genre : Computers
File Size : 73. 97 MB
Format : PDF
Download : 492
Read : 1079

Get This Book


This book constitutes the refereed proceedings of the First International Symposium on Computational Life Sciences, CompLife 2005, held in Konstanz, Germany in September 2005. The 21 revised full papers presented together with 3 papers of a workshop on Distributed Data Mining in the Life Sciences (LifeDDM) were carefully reviewed and selected from 49 initial submissions. The papers cover areas ranging from high-level system biology to data analysis related to mass spec traces and are organized in topical sections on systems biology, data analysis and integration, structural biology, genomics, computational proteomics, molecular informatics, molecular structure determination and simulation, and distributed data mining.

Top Download:

Best Books