Neural Networks And Genome Informatics
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Neural Networks and Genome Informatics
Author: Catherine H. Wu
language: en
Publisher: Elsevier Science Limited
Release Date: 2000
A reference in the field of neural networks and genome informatics. It includes a tutorial of neural network foundations that introduces basic neural network technology and terminology. It features a discussion of special system designs for building neural networks for genome informatics, and also reviews and evaluations of methods in the field.
Handbook on Neural Information Processing
Author: Monica Bianchini
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-04-12
This handbook presents some of the most recent topics in neural information processing, covering both theoretical concepts and practical applications. The contributions include: Deep architectures Recurrent, recursive, and graph neural networks Cellular neural networks Bayesian networks Approximation capabilities of neural networks Semi-supervised learning Statistical relational learning Kernel methods for structured data Multiple classifier systems Self organisation and modal learning Applications to content-based image retrieval, text mining in large document collections, and bioinformatics This book is thought particularly for graduate students, researchers and practitioners, willing to deepen their knowledge on more advanced connectionist models and related learning paradigms.
Post-genome Informatics
The genome projects have now entered a rapid production phase with complete genome sequences and complete gene catalogues already available for a number of organisms and an increasing number expected shortly. In addition the new DNA and protein chip technologies can produce functional data about genes such as gene expression profiles at a rapid rate. There is therefore a large and ever increasing amount of data about genes and molecules. However there is still a huge gap between information at the molecular level and information at the level of integrated biological systems. It is this gap that is addressed in Post-genome Informatics. Post-genome informatics is the analysis of biological functions in terms of the network of interacting molecules and genes with the aim of understanding how a biological system is organized from its individual building blocks. As well as containing a comprehensive survey of the database and computational technologies relevant to molecular sequence analysis, Post-genome Informatics will provide the reader with a conceptual framework and practical methods for the representation and computation of molecular networks.