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Pattern Recognition and Machine Learning (Information Science and Statistics)
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New Directions in Statistical Physics: Econophysics, Bioinformatics, and Pattern Recognition
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Pattern Recognition in Bioinformatics: Second IAPR International Workshop, PRIB 2007, Singapore, October 1-2, 2007, Procee…
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Pattern Recognition in Bioinformatics: 9th IAPR International Conference, PRIB 2014, Stockholm, Sweden, August 21-23, 201…
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Scalable Pattern Recognition Algorithms: Applications in Computational Biology and Bioinformatics
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Granular Neural Networks, Pattern Recognition and Bioinformatics (Studies in Computational Intelligence, 712)
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Pattern Recognition in Bioinformatics: 8th IAPR International Conference, PRIB 2013, Nice, France, June 17-20, 2013. Proce…
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Pattern Recognition in Bioinformatics: 7th IAPR International Conference, PRIB 2012, Tokyo, Japan, November 8-10, 2012, Pr…
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Pattern Recognition in Bioinformatics: 6th IAPR International Conference, PRIB 2011, Delft, The Netherlands, November 2-4,…
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Pattern Recognition in Bioinformatics: 5th IAPR International Conference, PRIB 2010, Nijmegen, The Netherlands, September …
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Pattern Recognition in Bioinformatics: Third IAPR International Conference, PRIB 2008, Melbourne, Australia, October 15-1…
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Pattern Recognition in Bioinformatics: International Workshop, PRIB 2006, Hong Kong, China, August 20, 2006, Proceedings (…
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Pattern Recognition in Bioinformatics : 6th Iapr International Conference, Prib 2011 Delft, The Netherlands, November 2-4, 2011 Proceedings (Paperback)
Pattern Recognition in Bioinformatics: 6th IAPR International Conference, PRIB 2011 Delft, The Netherlands, November 2-4, 2011 Proceedings • ISBN:9783642248542 • Format:Paperback • Publication Date:2011-10-21
Cluster Analysis for Data Mining and System Identification (Hardcover)
This book identifies fuzzy cluster analysis as a good approach to solving complex data mining and system identification problems. It illustrates how advanced fuzzy clustering algorithms can be used not only for partitioning of the data, but it can be used for visualization, regression, classification and time-series analysis. Data clustering is a common technique for statistical data analysis, which is used in many fields, including machine learning, data mining, pattern recognition, image analysis and bioinformatics. Clustering is the classification of similar objects into different groups, or more precisely, the partitioning of a data set into subsets (clusters), so that the data in each subset (ideally) share some common trait often proximity according to some defined distance measure. • Author: J\\u0026aacute;nos Abonyi,Bal\\u0026aacute;zs Feil • ISBN:9783764379872 • Format:Hardcover • Publication Date:2007-06-22
Computational Methods in Systems Biology: International Conference CMSB 2007, Edinburgh, Scotland, September 20-21, 2007, Proceedings / Edition 1 – Paperback
Computational Methods in Systems Biology: International Conference CMSB 2007, Edinburgh, Scotland, September 20-21, 2007, Proceedings / Edition 1
Lecture Notes in Computer Science / Lecture Notes in Bioinfo: Pattern Recognition in Bioinformatics : International Workshop, Prib 2006, Hong Kong, China, August 20, 2006, Proceedings (Series #4146) (Paperback)
The field of bioinformatics has two main objectives: the creation and maintenance of biological databases, and the discovery of knowledge from life sciences data in order to unravel the mysteries of biological function, leading to new drugs and therapies for human disease. Life sciences data come in the form of biological sequences, structures, pathways, or literature. One major aspect of discovering biological knowledge is to search, predict, or model specific patterns of a given dataset, which have some relevance to an important biological phenomenon or another dataset. To date, many pattern recognition algorithms have been applied or catered to address a wide range of bioinformatics problems. The 2006 Workshop of Bioinform
atics in Pattern Recognition (PRIB 2006) marks the beginning of a series of workshops that is aimed at gathering researchers applying pattern recognition algorithms in an attempt to resolve problems in computational biology and bioinformatics. This volume presents the proceedings of Workshop PRIB 2006 held in Hong Kong, China, on August 20, 2006. It includes 19 technical contributions that were selected by the Program Committee from 43 submissions. We give a brief introduction to pattern recognition in bioinformatics in the first paper. The rest of the volume consists of three parts. Part 1: signal and motif detection, and gene selection. Part 2: models of DNA, RNA, and protein structures. Part 3: biological databases and imaging. • ISBN:9783540374466 • Format:Paperback • Publication Date:2006-09-01
Studies in Computational Intelligence: Granular Neural Networks, Pattern Recognition and Bioinformatics (Series #712) (Hardcover)
Introduction to Granular Computing, Pattern Recognition and Data Mining.- Classification using Fuzzy Rough Granular Neural Networks.- Clustering using Fuzzy Rough Granular Self-Organizing Map.- Fuzzy Rough Granular Neural Network and Unsupervised Feature Selection. • Author: Sankar K Pal,Shubhra S Ray,Avatharam Ganivada • ISBN:9783319571133 • Format:Hardcover • Publication Date:2017-06-02
Bioinformatics: Updated Features and Applications (Hardcover)
An interdisciplinary bioinformatics science aims to develop methodology and analysis tools to explore large-volume of biological data using conventional and modern computer science, statistics, and mathematics, as well as pattern recognition, reconstruction, machine learning, simulation and iterative approaches, molecular modeling, folding, networking, and artificial intelligence. Written by international team of life scientists, this Bioinformatics book provides some updates on bioinformatics methods, resources, approaches, and genome analysis tools useful for molecular sciences, medicine and drug designs, as well as plant sciences and agriculture. I trust chapters of this book should provide advanced knowledge for university students, life science researchers, and interested readers on some latest developments in the bioinformatics field. Bioinformatics: Updated Features and Applications (Hardcover)
