
Database Technology For Life Sciences And Medicine
World Scientific Publishing Co Pte Ltd
Published on 1. September 2010
Book
Hardback
388 pages
978-981-4307-70-3 (ISBN)
Description
This book presents innovative approaches from database researchers supporting the challenging process of knowledge discovery in biomedicine. Ranging from how to effectively store and organize biomedical data via data quality and case studies to sophisticated data mining methods, this book provides the state-of-the-art of database technology for life sciences and medicine.A valuable source of information for experts in life sciences who want to be updated about the possibilities of database technology in their field, this volume will also be inspiring for students and researchers in informatics who are keen to contribute to this emerging field of interdisciplinary research.
More details
Series
Language
English
Place of publication
Singapore
Singapore
Target group
College/higher education
Dimensions
Height: 235 mm
Width: 157 mm
Thickness: 25 mm
Weight
714 gr
ISBN-13
978-981-4307-70-3 (9789814307703)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
Editor
Ludwig-maximilians Univ Munich, Germany
Technische Univ Munchen, Germany
Content
Core Database Technology: Data Quality in Medical Databases; Database Architecture to Support Biological and Medical Research: Federated Databases, Data Management Platforms, Data Warehouses, Multi-Agent Systems; Anonymity-Preserving Dissemination of Patient Records; Ontology-Based Data Integration in Medicine; Efficient Similarity Search in Biological and Medical Databases; Data Mining: Data Mining For Hospital Productivity Improvement; Multi-Step Patient Health Classification; Motive Discovery in Brain Networks; Feature Selection to Identify Liver Diseases from Breath-Gas Data; Mining Association Rules Between Breast Cancer Prognostic Factors and Gene Expression Data.