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.
"Sinopsis" puede pertenecer a otra edición de este libro.
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.
"Sobre este título" puede pertenecer a otra edición de este libro.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
Condición: As New. Unread book in perfect condition. Nº de ref. del artículo: 6383520
Cantidad disponible: Más de 20 disponibles
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
Condición: New. Nº de ref. del artículo: 6383520-n
Cantidad disponible: Más de 20 disponibles
Librería: California Books, Miami, FL, Estados Unidos de America
Condición: New. Nº de ref. del artículo: I-9781420086843
Cantidad disponible: Más de 20 disponibles
Librería: moluna, Greven, Alemania
Gebunden. Condición: New. 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. Nº de ref. del artículo: 595755045
Cantidad disponible: Más de 20 disponibles
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
Condición: As New. Unread book in perfect condition. Nº de ref. del artículo: 6383520
Cantidad disponible: Más de 20 disponibles
Librería: Ria Christie Collections, Uxbridge, Reino Unido
Condición: New. In English. Nº de ref. del artículo: ria9781420086843_new
Cantidad disponible: Más de 20 disponibles
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
Condición: New. Nº de ref. del artículo: 6383520-n
Cantidad disponible: Más de 20 disponibles
Librería: Revaluation Books, Exeter, Reino Unido
Hardcover. Condición: Brand New. 1st edition. 733 pages. 9.53x6.50x1.65 inches. In Stock. Nº de ref. del artículo: x-1420086847
Cantidad disponible: 2 disponibles
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Buch. Condición: Neu. Neuware - 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. Nº de ref. del artículo: 9781420086843
Cantidad disponible: 2 disponibles