› › Probabilistic Modeling In Bioinformatics And Medical Informatics

Probabilistic Modeling in Bioinformatics and Medical Informatics

Author : Dirk Husmeier

Publisher : Springer Science & Business Media

Page : 511 pages

File Size : 28,4 MB

Release : 2006-05-06

Category : Computers

ISBN : 1846281199

Get eBook

Book Description

Probabilistic Modelling in Bioinformatics and Medical Informatics has been written for researchers and students in statistics, machine learning, and the biological sciences. The first part of this book provides a self-contained introduction to the methodology of Bayesian networks. The following parts demonstrate how these methods are applied in bioinformatics and medical informatics. All three fields - the methodology of probabilistic modeling, bioinformatics, and medical informatics - are evolving very quickly. The text should therefore be seen as an introduction, offering both elementary tutorials as well as more advanced applications and case studies.



Handbook of Statistical Bioinformatics

Author : Henry Horng-Shing Lu

Publisher : Springer Nature

Page : 406 pages

File Size : 20,58 MB

Release : 2022-12-08

Category : Science

ISBN : 3662659026

Get eBook

Book Description

Now in its second edition, this handbook collects authoritative contributions on modern methods and tools in statistical bioinformatics with a focus on the interface between computational statistics and cutting-edge developments in computational biology. The three parts of the book cover statistical methods for single-cell analysis, network analysis, and systems biology, with contributions by leading experts addressing key topics in probabilistic and statistical modeling and the analysis of massive data sets generated by modern biotechnology. This handbook will serve as a useful reference source for students, researchers and practitioners in statistics, computer science and biological and biomedical research, who are interested in the latest developments in computational statistics as applied to computational biology.



Biological Sequence Analysis

Author : Richard Durbin

Publisher : Cambridge University Press

Page : 372 pages

File Size : 19,92 MB

Release : 1998-04-23

Category : Science

ISBN : 113945739X

Get eBook

Book Description

Probabilistic models are becoming increasingly important in analysing the huge amount of data being produced by large-scale DNA-sequencing efforts such as the Human Genome Project. For example, hidden Markov models are used for analysing biological sequences, linguistic-grammar-based probabilistic models for identifying RNA secondary structure, and probabilistic evolutionary models for inferring phylogenies of sequences from different organisms. This book gives a unified, up-to-date and self-contained account, with a Bayesian slant, of such methods, and more generally to probabilistic methods of sequence analysis. Written by an interdisciplinary team of authors, it aims to be accessible to molecular biologists, computer scientists, and mathematicians with no formal knowledge of the other fields, and at the same time present the state-of-the-art in this new and highly important field.



Machine Learning, Big Data, and IoT for Medical Informatics

Author : Pardeep Kumar

Publisher : Academic Press

Page : 458 pages

File Size : 15,92 MB

Release : 2021-06-13

Category : Computers

ISBN : 0128217812

Get eBook

Book Description

Machine Learning, Big Data, and IoT for Medical Informatics focuses on the latest techniques adopted in the field of medical informatics. In medical informatics, machine learning, big data, and IOT-based techniques play a significant role in disease diagnosis and its prediction. In the medical field, the structure of data is equally important for accurate predictive analytics due to heterogeneity of data such as ECG data, X-ray data, and image data. Thus, this book focuses on the usability of machine learning, big data, and IOT-based techniques in handling structured and unstructured data. It also emphasizes on the privacy preservation techniques of medical data. This volume can be used as a reference book for scientists, researchers, practitioners, and academicians working in the field of intelligent medical informatics. In addition, it can also be used as a reference book for both undergraduate and graduate courses such as medical informatics, machine learning, big data, and IoT. Explains the uses of CNN, Deep Learning and extreme machine learning concepts for the design and development of predictive diagnostic systems. Includes several privacy preservation techniques for medical data. Presents the integration of Internet of Things with predictive diagnostic systems for disease diagnosis. Offers case studies and applications relating to machine learning, big data, and health care analysis.



Artificial Intelligence in Medicine

Author : David Riaño

Publisher : Springer

Page : 431 pages

File Size : 17,62 MB

Release : 2019-06-19

Category : Computers

ISBN : 303021642X

Get eBook

Book Description

This book constitutes the refereed proceedings of the 17th Conference on Artificial Intelligence in Medicine, AIME 2019, held in Poznan, Poland, in June 2019. The 22 revised full and 31 short papers presented were carefully reviewed and selected from 134 submissions. The papers are organized in the following topical sections: deep learning; simulation; knowledge representation; probabilistic models; behavior monitoring; clustering, natural language processing, and decision support; feature selection; image processing; general machine learning; and unsupervised learning.



Handbook of Statistical Systems Biology

Author : Michael Stumpf

Publisher : John Wiley & Sons

Page : 624 pages

File Size : 34,41 MB

Release : 2011-09-09

Category : Science

ISBN : 1119952042

Get eBook

Book Description

Systems Biology is now entering a mature phase in which the key issues are characterising uncertainty and stochastic effects in mathematical models of biological systems. The area is moving towards a full statistical analysis and probabilistic reasoning over the inferences that can be made from mathematical models. This handbook presents a comprehensive guide to the discipline for practitioners and educators, in providing a full and detailed treatment of these important and emerging subjects. Leading experts in systems biology and statistics have come together to provide insight in to the major ideas in the field, and in particular methods of specifying and fitting models, and estimating the unknown parameters. This book: Provides a comprehensive account of inference techniques in systems biology. Introduces classical and Bayesian statistical methods for complex systems. Explores networks and graphical modeling as well as a wide range of statistical models for dynamical systems. Discusses various applications for statistical systems biology, such as gene regulation and signal transduction. Features statistical data analysis on numerous technologies, including metabolic and transcriptomic technologies. Presents an in-depth presentation of reverse engineering approaches. Provides colour illustrations to explain key concepts. This handbook will be a key resource for researchers practising systems biology, and those requiring a comprehensive overview of this important field.



Supply Chain Management: Concepts, Methodologies, Tools, and Applications

Author : Management Association, Information Resources

Publisher : IGI Global

Page : 1880 pages

File Size : 45,98 MB

Release : 2012-12-31

Category : Business & Economics

ISBN : 1466626755

Get eBook

Book Description

In order to keep up with the constant changes in technology, business have adopted supply chain management to improve competitive strategies on a strategic and operational level. Supply Chain Management: Concepts, Methodologies, Tools, and Applications is a reference collection which highlights the major concepts and issues in the application and advancement of supply chain management. Including research from leading scholars, this resource will be useful for academics, students, and practitioners interested in the continuous study of supply chain management and its influences.



Hybrid Artificial Intelligent Systems

Author : Francisco Javier de Cos Juez

Publisher : Springer

Page : 765 pages

File Size : 26,72 MB

Release : 2018-06-09

Category : Computers

ISBN : 331992639X

Get eBook

Book Description

This volume constitutes the refereed proceedings of the 13th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2018, held in Oviedo, Spain, in June 2018. The 62 full papers published in this volume were carefully reviewed and selected from 104 submissions. They are organized in the following topical sections: Neurocomputing, fuzzy systems, rough sets, evolutionary algorithms, Agents andMultiagent Systems, and alike.



Pattern Recognition in Computational Molecular Biology

Author : Mourad Elloumi

Publisher : John Wiley & Sons

Page : 654 pages

File Size : 38,20 MB

Release : 2015-12-24

Category : Technology & Engineering

ISBN : 1119078865

Get eBook

Book Description

A comprehensive overview of high-performance pattern recognition techniques and approaches to Computational Molecular Biology This book surveys the developments of techniques and approaches on pattern recognition related to Computational Molecular Biology. Providing a broad coverage of the field, the authors cover fundamental and technical information on these techniques and approaches, as well as discussing their related problems. The text consists of twenty nine chapters, organized into seven parts: Pattern Recognition in Sequences, Pattern Recognition in Secondary Structures, Pattern Recognition in Tertiary Structures, Pattern Recognition in Quaternary Structures, Pattern Recognition in Microarrays, Pattern Recognition in Phylogenetic Trees, and Pattern Recognition in Biological Networks. Surveys the development of techniques and approaches on pattern recognition in biomolecular data Discusses pattern recognition in primary, secondary, tertiary and quaternary structures, as well as microarrays, phylogenetic trees and biological networks Includes case studies and examples to further illustrate the concepts discussed in the book Pattern Recognition in Computational Molecular Biology: Techniques and Approaches is a reference for practitioners and professional researches in Computer Science, Life Science, and Mathematics. This book also serves as a supplementary reading for graduate students and young researches interested in Computational Molecular Biology.



Bayesian and grAphical Models for Biomedical Imaging

Author : M. Jorge Cardoso

Publisher : Springer

Page : 139 pages

File Size : 19,47 MB

Release : 2014-09-22

Category : Computers

ISBN : 3319122894

Get eBook

Book Description

This book constitutes the refereed proceedings of the First International Workshop on Bayesian and grAphical Models for Biomedical Imaging, BAMBI 2014, held in Cambridge, MA, USA, in September 2014 as a satellite event of the 17th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2014. The 11 revised full papers presented were carefully reviewed and selected from numerous submissions with a key aspect on probabilistic modeling applied to medical image analysis. The objectives of this workshop compared to other workshops, e.g. machine learning in medical imaging, have a stronger mathematical focus on the foundations of probabilistic modeling and inference. The papers highlight the potential of using Bayesian or random field graphical models for advancing scientific research in biomedical image analysis or for the advancement of modeling and analysis of medical imaging data.