Biological Data Mining -

Biological Data Mining

Jake Y. Chen, Stefano Lonardi (Herausgeber)

Buch | Softcover
736 Seiten
2017
CRC Press (Verlag)
978-1-138-11658-0 (ISBN)
93,50 inkl. MwSt
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.

Jake Y. Chen is an assistant professor of informatics at Indiana University, an assistant professor of computer science at Purdue University, and director of the Indiana Center for Systems Biology and Personalized Medicine. Stefano Lonardi is an associate professor of computer science and engineering at the University of California, Riverside.

Sequence, Structure, and Function. Genomics, Transcriptomics, and Proteomics. Functional and Molecular Interaction Networks. Literature, Ontology, and Knowledge Integration. Genome Medicine Applications.

Erscheinungsdatum
Reihe/Serie Chapman & Hall/CRC Data Mining and Knowledge Discovery Series
Zusatzinfo 69 Tables, black and white; 169 Illustrations, black and white
Verlagsort London
Sprache englisch
Maße 156 x 234 mm
Gewicht 1088 g
Themenwelt Informatik Datenbanken Data Warehouse / Data Mining
Mathematik / Informatik Informatik Theorie / Studium
Naturwissenschaften Biologie
ISBN-10 1-138-11658-0 / 1138116580
ISBN-13 978-1-138-11658-0 / 9781138116580
Zustand Neuware
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