Bioinformatics And Medical Applications
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Bioinformatics and Medical Applications
BIOINFORMATICS AND MEDICAL APPLICATIONS The main topics addressed in this book are big data analytics problems in bioinformatics research such as microarray data analysis, sequence analysis, genomics-based analytics, disease network analysis, techniques for big data analytics, and health information technology. Bioinformatics and Medical Applications: Big Data Using Deep Learning Algorithms analyses massive biological datasets using computational approaches and the latest cutting-edge technologies to capture and interpret biological data. The book delivers various bioinformatics computational methods used to identify diseases at an early stage by assembling cutting-edge resources into a single collection designed to enlighten the reader on topics focusing on computer science, mathematics, and biology. In modern biology and medicine, bioinformatics is critical for data management. This book explains the bioinformatician’s important tools and examines how they are used to evaluate biological data and advance disease knowledge. The editors have curated a distinguished group of perceptive and concise chapters that presents the current state of medical treatments and systems and offers emerging solutions for a more personalized approach to healthcare. Applying deep learning techniques for data-driven solutions in health information allows automated analysis whose method can be more advantageous in supporting the problems arising from medical and health-related information. Audience The primary audience for the book includes specialists, researchers, postgraduates, designers, experts, and engineers, who are occupied with biometric research and security-related issues.
Translational Bioinformatics in Healthcare and Medicine
Translational Bioinformatics in Healthcare and Medicine offers an overview of main principles of bioinformatics, biological databases, clinical informatics, health informatics, viroinformatics and real-case applications of translational bioinformatics in healthcare. Written by experts from both technology and clinical sides, the content brings together essential knowledge to make the best of recent advancements of the field. The book discusses topics such as next generation sequence analysis, genomics in clinical care, IoT applications, blockchain technology, patient centered interoperability of EHR, health data mining, and translational bioinformatics methods for drug discovery and drug repurposing. In addition, it discusses the role of bioinformatics in cancer research and viroinformatics approaches to counter viral diseases through informatics. This is a valuable resource for bioinformaticians, clinicians, healthcare professionals, graduate students and several members of biomedical field who are interested in learning more about how bioinformatics can impact in their research and practice. - Covers recent advancements in translational bioinformatics and its healthcare applications - Discusses integrative and multidisciplinary approaches to U-healthcare systems development and management - Bridges the gap among various knowledge domains in the field, integrating both technological and clinical knowledge into practical content
Java for Bioinformatics and Biomedical Applications
Author: Harshawardhan Bal
language: en
Publisher: Springer Science & Business Media
Release Date: 2007-01-16
April 2006 Introduction Bioinformatics is at a crossroads. We work in a field that is changing every day, increasingly moving from specific solutions created by single researchers working alone or in small groups to larger, often geographically dispersed programs enabled by collaborative computing and open software. This book represents an important development, giving the reader an opportunity to discover how the use of open and reusable Java code can solve large bioinformatics problems in a software engineered and robust way. I work with one of the authors of this book every day, on the National Cancer Institute's cancer Biomedical Informatics Grid (caBIGTM) project, and I can attest that they are well suited to share with their readers both their experience in the development and use of bioinformatics software, as well as their interest in solid software engineering and interoperability. Background and history In its short history, bioinformatics has become an increasingly important part of how scientists involved in biological research go about their work. This has lead to an explosion of interest in the subject, and a similar explosion in tools and data resources for researchers to learn and use in their work. Historically, tools for bioinformatics have been idiosyncratic and are custom-developed by the end-users (or those close to them) in an iterative fashion until the specific immediate problem is solved. This has led to a balkanization of informatics systems, sometimes yielding multiple, incompatible systems at a single institution for a single application.