This book explores the latest and most relevant topics in the field of computational bioengineering and bioinformatics, with a particular focus on patient-specific, disease-progression modeling. It covers computational methods for cardiovascular disease prediction, with an emphasis on biomechanics, biomedical decision support systems, data mining, personalized diagnostics, bio-signal processing, protein structure prediction, biomedical image processing, analysis and visualization, and high-performance computing. It also discusses state-of-the-art tools for disease characterization, and recent advances in areas such as biomechanics, cardiovascular engineering, patient-specific modeling, population-based modeling, multiscale modeling, image processing, data mining, biomedical decision-support systems, signal processing, biomaterials and dental biomechanics, tissue and cell engineering, computational chemistry and high-performance computing. As such, it is a valuable resource for researchers, medical and bioengineering students, and medical device and software experts
The book's chapters are the result of many international projects in the area of bioengineering and bioinformatics done at the Research and Development Center for Bioengineering BioIRC and by the Faculty of Engineering at the University of ...
The respective chapters provide detailed information on biological databases, sequence alignment, molecular evolution, next-generation sequencing, systems biology, and statistical computing using R. The book also presents a case-based ...
The book introduces basic concepts of multidiscipline-based computational modeling methods, provides detailed step-by-step techniques to build a model with consideration of underlying multiphysics, and discusses many important aspects of a ...
Molinaro, A.M., Simon,R., and Pfeiffer, R.M. (2005). Predictionerror estimation:A comparison ofresampling methods. Bioinformatics, 21: 309– 313. Petricoin, E.F., et al. (2002). Useof proteomic patters in serumto identify ovarian cancer.
This major reference work spans basic and cutting-edge methodologies authored by leaders in the field, providing an invaluable resource for students, scientists, professionals in research institutes, and a broad swath of researchers in ...
This proceedings volume assembles papers from various professionals engaged in the fields of Biomedical Engineering, Bioinformatics and Computational Biology.
It also highlights some unsolved and outstanding theoretical questions, with a potentially high impact on these disciplines. Two communities will be particularly interested in this book.
Statistical methods for computational biology, data mining and visualization 6. Socio Economics and Ethics. This book presents the foundations of key problems in computational molecular biology and bioinformatics.
A.Y. Zomaya, Stability of feature selection algorithms and ensemble feature selection methods in bioinformatics. in Biological Knowledge Discovery Handbook: Preprocessing, Mining and Post Processing of Biological Data (2017) 8.
The editors have built Issues in Bioengineering and Bioinformatics: 2013 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Lifetime Data Analysis in this book to be deeper than what you can ...