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Probabilistic Graphical Models for Genetics, Genomics, and Postgenomics
At the crossroads between statistics and machine learning, probabilistic graphical models (PGMs) provide a powerful formal framework to model complex data. An expanding volume of biological data of various types, the so-called 'omics', is in need of accurate and efficient methods for modelling and PGMs are expected to have a prominent role to play.
Biomedical Engineering Systems and Technologies
This book constitutes extended and revised versions of a set of selected papers from the 12th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2019, held in Prague, Czech Republic, in February 2019. The 22 revised and extended full papers presented were carefully reviewed and selected from a total of 271 submissions. The papers are organized in topical sections on biomedical electronics and devices; bioimaging; bioinformatics models, methods and algorithms; bio-inspired systems and signal processing; health informatics.
Algebraic Statistics
Algebraic statistics uses tools from algebraic geometry, commutative algebra, combinatorics, and their computational sides to address problems in statistics and its applications. The starting point for this connection is the observation that many statistical models are semialgebraic sets. The algebra/statistics connection is now over twenty years old, and this book presents the first broad introductory treatment of the subject. Along with background material in probability, algebra, and statistics, this book covers a range of topics in algebraic statistics including algebraic exponential families, likelihood inference, Fisher's exact test, bounds on entries of contingency tables, design of experiments, identifiability of hidden variable models, phylogenetic models, and model selection. With numerous examples, references, and over 150 exercises, this book is suitable for both classroom use and independent study.
Machine Learning, Optimization, and Data Science
This book constitutes the post-conference proceedings of the 4th International Conference on Machine Learning, Optimization, and Data Science, LOD 2018, held in Volterra, Italy, in September 2018.The 46 full papers presented were carefully reviewed and selected from 126 submissions. The papers cover topics in the field of machine learning, artificial intelligence, reinforcement learning, computational optimization and data science presenting a substantial array of ideas, technologies, algorithms, methods and applications.
Biomedical Engineering Systems and Technologies
This book constitutes the thoroughly refereed post-conference proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018, held in Funchal, Madeira, Portugal, in January 2018. The 25 revised full papers presented were carefully reviewed and selected from a total of 299 submissions. The papers are organized in topical sections on biomedical electronics and devices; bioimaging; bioinformatics models, methods and algorithms; health informatics.
Combinatorics, Algorithms, Probabilistic and Experimental Methodologies
The First International Symposium on Combinatorics, Algorithms, Probabilistic and Experimental Methodologies was held in Hangzhou, China, in April 2007. The symposium provided an interdisciplinary forum for researchers to share their discoveries and approaches; search for ideas, methodologies, and tool boxes; find better, faster, and more accurate solutions; and develop a research agenda of common interest. This volume constitutes the refereed post-proceedings of the symposium. Inside you'll find 46 full papers. They represent some of the most important thinking and advancements in the field. The papers address large data processing problems using different methodologies from major disciplines such as computer science, combinatorics, and statistics.
Biomedical Engineering Systems and Technologies
This book constitutes the thoroughly refereed post-conference proceedings of the 5th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2012, held in Vilamoura, Portugal, in February 2012. The 26 revised full papers presented together with one invited lecture were carefully reviewed and selected from a total of 522 submissions. The papers cover a wide range of topics and are organized in four general topical sections on biomedical electronics and devices; bioinformatics models, methods and algorithms; bio-inspired systems and signal processing; health informatics.
Biomedical Engineering Systems and Technologies
This book constitutes the refereed proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2021, held virtually due to the COVID-19 crisis, in February 2021. The conference was held virtually due to the COVID-19 crisis. The 13 full papers included in this book were carefully reviewed and selected from 265 submissions. The papers selected to be included in this book contribute to the understanding of relevant trends of current research on Biomedical Engineering Systems and Technologies, including: Pattern Recognition and Machine Learning, Application of Health Informatics in Clinical Cases, Evaluation and Use of Healthcare IT, Medical Signal Acquisition, Analysis and Processing, Data Mining and Data Analysis, Decision Support Systems, e-Health, e-Health Applications, Mobile Technologies for Healthcare Applications and Medical Devices design.
Physiological Computing Systems
This book constitutes the proceedings of the First International Conference on Physiological Computing Systems, PhyCS 2014, held in Lisbon, Portugal, in January 2014. The 10 papers presented in this volume were carefully reviewed and selected from 52 submissions. They are organized in topical sections named: methodologies and methods; devices; applications; and human factors.
Computational Methods for Understanding Complexity: The Use of Formal Methods in Biology
The complexity of living organisms surpasses our unaided habilities of analysis. Hence, computational and mathematical methods are necessary for increasing our understanding of biological systems. At the same time, there has been a phenomenal recent progress allowing the application of novel formal methods to new domains. This progress has spurred a conspicuous optimism in computational biology. This optimism, in turn, has promoted a rapid increase in collaboration between specialists of biology with specialists of computer science. Through sheer complexity, however, many important biological problems are at present intractable, and it is not clear whether we will ever be able to solve such ...
