Computational Neurogenetic Modeling

1. Auflage. Softcover version of original hardcover Auflage 2007
ISBN: 978-1-4419-4301-9
Verlag: Springer US

Buch, Englisch, 290 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 476 g

Reihe: Topics in Biomedical Engineering. International Book Series

Computational Neurogenetic Modeling is a student text, introducing the scope and problems of a new scientific discipline - Computational Neurogenetic Modeling (CNGM). CNGM is concerned with the study and development of dynamic neuronal models for modeling brain functions with respect to genes and dynamic interactions between genes. These include neural network models and their integration with gene network models. This new area brings together knowledge from various scientific disciplines, such as computer and information science, neuroscience and cognitive science, genetics and molecular biology, as well as engineering.

Zielgruppe

Research

Autoren/Hrsg.

Kasabov, Nikola K.

Benuskova, Lubica

Fachgebiete

• Naturwissenschaften Biowissenschaften Biowissenschaften Neurobiologie, Verhaltensbiologie
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
• Naturwissenschaften Biowissenschaften Molekularbiologie
• Mathematik | Informatik EDV | Informatik Angewandte Informatik Bioinformatik
• Naturwissenschaften Biowissenschaften Angewandte Biologie Bioinformatik
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Vorklinische Medizin: Grundlagenfächer Humangenetik

Inhaltsverzeichnis

Computational Neurogenetic Modeling (CNGM): A Brief Introduction.- Organization and Functions of the Brain.- Neuro-Information Processing in the Brain.- Artificial Neural Networks (ANN).- Evolving Connectionist Systems (ECOS).- Evolutionary Computation for Model and Feature Optimization.- Gene/Protein Interactions — Modeling Gene Regulatory Networks (GRN).- CNGM as Integration of GPRN, ANN and Evolving Processes.- Application of CNGM to Learning and Memory.- Applications of CNGM and Future Development.

Über Autor(innen)

Lubica Benuskova is currently Senior Research Fellow at the Knowledge Engineering & Discovery Research Institute (KEDRI, www.kedri.info), Auckland University of Technology (AUT) in Auckland, New Zealand. She is also Associate Professor of Applied Informatics at the Faculty of Mathematics, Physics and Informatics at Comenius (Komensky) University in Bratislava, Slovakia. Her research interests are in the areas of computational neuroscience, cognitive science, neuroinformatics, computer and information sciences.

Nikola Kasabov is the Founding Director and Chief Scientist of KEDRI, and a Professor and Chair of Knowledge Engineering at the School of Computer and Information Sciences at AUT. He is a leading expert in computational intelligence and knowledge engineering and has published more than 400 papers, books and patents in the areas of neural and hybrid intelligent systems, bioinformatics and neuroinformatics, speech-, image and multimodal information processing. He is a Fellow of the Royal Society of New Zealand, Senior Member of IEEE, Vice President of the International Neural Network Society and a Past President of the Asia-Pacific Neural Network Assembly.