Zaki has published over 70 papers on data mining, he has coedited 5 books, and served as guesteditor for information systems special issue on bioinformatics and biological data mining, sigkdd. Data mining for bioinformatics applications sciencedirect. Download the ebook data mining for bioinformatics sumeet dua in pdf or epub format and read it directly on your mobile phone, computer or any device. With a growing volume of biomedical databases and repositories, the need to develop a set of tools to address their analysis and support knowledge discovery is becoming acute. The data mining community has developed a substantial set of techniques for computational treatment of these data. As discussed bioinformatics is an increasingly data rich industry and thus using data mining techniques helps to propose proactive research within specific fields of the biomedical industry. Zalerts allow you to be notified by email about the availability of new books according to your search query. Development of novel data mining methods will play a fundamental role in understanding these rapidly expanding sources of biological data. Bioinformatics is the science of storing, analyzing, and utilizing information from biological data such as sequences, molecules, gene expressions, and pathways. It contains an extensive collection of machine learning algorithms and data preprocessing methods.
The weka machine learning workbench provides a generalpurpose environment for automatic classification, regression, clustering and feature selectioncommon data mining problems in bioinformatics research. Data mining is the process of automatic discovery of novel and understandable models and patterns from large amounts of data. Download data mining for bioinformatics sumeet dua pdf. Covering theory, algorithms, and methodologies, as well as data mining technologies, data mining for bioinformatics provides a comprehensive discussion of dataintensive computations used in data mining with applications in bioinformatics. In addition, appropriate protocols, languages, and network services are required for mining distributed data to handle the meta data and mappings required for mining distributed data. Data mining and gene expression analysis in bioinformatics. Additionally this allows for researchers to develop a better understanding of biological mechanisms in order to discover new treatments within healthcare and knowledge of life.
Data mining for bioinformatics sumeet dua, pradeep. Pdf application of data mining in bioinformatics researchgate. A search query can be a title of the book, a name of the author, isbn or anything else. Bioinformatics can be defined as the application of computer technology to the management of biological. An introduction into data mining in bioinformatics. This book is targeted to readers who are interested in the embodiments of data mining techniques, technologies, and frameworks employed for effective storing. Bioinformatics or computational biology is the interdisciplinary science of. Data mining is the use of automated data analysis techniques to uncover. Application of data mining in the field of bioinformatics. 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.1022 1345 82 931 798 147 545 1524 303 258 1265 980 1116 1068 93 1162 467 486 1204 1368 1256 1513 590 961 23 1477 862 520 1317 1426 580 282