Neural Networks And Genome Informatics

This book is a comprehensive reference in the field of neural networks and genome informatics. The tutorial of neural network foundations introduces basic neural network technology and terminology. This is followed by an in-depth discussion of special system designs for building neural networks for genome informatics, and broad reviews and evaluations of current state-of-the-art methods in the field. This book concludes with a description of open research problems and future research directions.

This book contains articles written by experts on a wide range of topics that are associated with the analysis and management of biological information at the molecular level. It contains chapters on RNA and protein structure analysis, DNA computing, sequence mapping, genome comparison, gene expression data mining, metabolic network modeling, and phyloinformatics. The important work of some representative researchers in bioinformatics is brought together for the first time in one volume. The topic is treated in depth and is related to, where applicable, other emerging technologies such as data mining and visualization. The goal of the book is to introduce readers to the principle techniques of bioinformatics in the hope that they will build on them to make new discoveries of their own. Contents: Exploring RNA Intermediate Conformations with the Massively Parallel Genetic Algorithm; Introduction to Self-Assembling DNA Nanostructures for Computation and Nanofabrication; Mapping Sequence to Rice FPC; Graph Theoretic Sequence Clustering Algorithms and their Applications to Genome Comparison; The Protein Information Resource for Functional Genomics and Proteomics; High-Grade Ore for Data Mining in 3D Structures; Protein Classification: A Geometric Hashing Approach; Interrelated Clustering: An Approach for Gene Expression Data Analysis; Creating Metabolic Network Models Using Text Mining and Expert Knowledge; Phyloinformatics and Tree Networks. Readership: Molecular biologists who rely on computers and mathematical scientists with interests in biology.

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.

This book provides a proficient guide on the relationship between Artificial Intelligence (AI) and healthcare and how AI is changing all aspects of the healthcare industry. It also covers how deep learning will help in diagnosis and the prediction of disease spread. The editors present a comprehensive review of research applying deep learning in health informatics in the fields of medical imaging, electronic health records, genomics, and sensing, and highlights various challenges in applying deep learning in health care. This book also includes applications and case studies across all areas of AI in healthcare data. The editors also aim to provide new theories, techniques, developments, and applications of deep learning, and to solve emerging problems in healthcare and other domains. This book is intended for computer scientists, biomedical engineers, and healthcare professionals researching and developing deep learning techniques. In short, the volume : Discusses the relationship between AI and healthcare, and how AI is changing the health care industry. Considers uses of deep learning in diagnosis and prediction of disease spread. Presents a comprehensive review of research applying deep learning in health informatics across multiple fields. Highlights challenges in applying deep learning in the field. Promotes research in ddeep llearning application in understanding the biomedical process. Dr.. M.A. Jabbar is a professor and Head of the Department AI&ML, Vardhaman College of Engineering, Hyderabad, Telangana, India. Prof. (Dr.) Ajith Abraham is the Director of Machine Intelligence Research Labs (MIR Labs), Auburn, Washington, USA. Dr.. Onur Dogan is an assistant professor at İzmir Bakırçay University, Turkey. Prof. Dr. Ana Madureira is the Director of The Interdisciplinary Studies Research Center at Instituto Superior de Engenharia do Porto (ISEP), Portugal. Dr.. Sanju Tiwari is a senior researcher at Universidad Autonoma de Tamaulipas, Mexico.

The Springer Handbook of Bio-/Neuro-Informatics is the first published book in one volume that explains together the basics and the state-of-the-art of two major science disciplines in their interaction and mutual relationship, namely: information sciences, bioinformatics and neuroinformatics. Bioinformatics is the area of science which is concerned with the information processes in biology and the development and applications of methods, tools and systems for storing and processing of biological information thus facilitating new knowledge discovery. Neuroinformatics is the area of science which is concerned with the information processes in biology and the development and applications of methods, tools and systems for storing and processing of biological information thus facilitating new knowledge discovery. The text contains 62 chapters organized in 12 parts, 6 of them covering topics from information science and bioinformatics, and 6 cover topics from information science and neuroinformatics. Each chapter consists of three main sections: introduction to the subject area, presentation of methods and advanced and future developments. The Springer Handbook of Bio-/Neuroinformatics can be used as both a textbook and as a reference for postgraduate study and advanced research in these areas. The target audience includes students, scientists, and practitioners from the areas of information, biological and neurosciences. With Forewords by Shun-ichi Amari of the Brain Science Institute, RIKEN, Saitama and Karlheinz Meier of the University of Heidelberg, Kirchhoff-Institute of Physics and Co-Director of the Human Brain Project.

This volume contains 18 peer-reviewed papers based on the presentations at the 10th Annual International Workshop on Bioinformatics and Systems Biology (IBSB 2010) held at Kyoto University from July 26 to July 28, 2010. This workshop started in 2001 as an event for doctoral students and young researchers to present and discuss their research results and approaches in bioinformatics and systems biology. It is part of a collaborative educational program involving leading institutions and leaders committed to the following programs: bull; Boston - Graduate Program in Bioinformatics, Boston University bull; Berlin - The International Research Training Group (IRTG) "Genomics and Systems Biology of Molecular Networks" bull; Kyoto - The JSPS International Training Program (ITP) "International Research and Training Program of Bioinformatics and Systems Biology" bull; Tokyo - Global COE Program "Center of Education and Research for Advanced Genome-Based Medicine"

This volume contains 18 peer-reviewed papers based on the presentations at the 10th Annual International Workshop on Bioinformatics and Systems Biology (IBSB 2010) held at Kyoto University from July 26 to July 28, 2010. This workshop started in 2001 as an event for doctoral students and young researchers to present and discuss their research results and approaches in bioinformatics and systems biology. It is part of a collaborative educational program involving leading institutions and leaders committed to the following programs:Boston — Graduate Program in Bioinformatics, Boston University Berlin — The International Research Training Group (IRTG) “Genomics and Systems Biology of Molecular Networks”Kyoto — The JSPS International Training Program (ITP) “International Research and Training Program of Bioinformatics and Systems Biology”Tokyo — Global COE Program “Center of Education and Research for Advanced Genome-Based Medicine”/a

This volume contains papers presented at the 19th International Conference on Genome Informatics (GIW 2008) held at the Marriott Surfers Paradise Resort, Gold Coast, Queensland, Australia from December 1 to 3, 2008. The GIW Series provides an international forum for the presentation and discussion of original research papers on all aspects of bioinformatics, computational biology and systems biology. Its scope includes biological sequence analysis, protein structure prediction, genetic regulatory networks, bioinformatic algorithms, comparative genomics, and biomolecular data integration and analysis. Boasting a history of 19 years, GIW is the longest-running international bioinformatics conference.