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During the 1980s and early 1990s there was signi?cant work in the design and implementation of hardware neurocomputers. Nevertheless, most of these efforts may be judged to have been unsuccessful: at no time have have ha- ware neurocomputers been in wide use. This lack of success may be largely attributed to the fact that earlier work was almost entirely aimed at developing custom neurocomputers, based on ASIC technology, but for such niche - eas this technology was never suf?ciently developed or competitive enough to justify large-scale adoption. On the other hand, gate-arrays of the period m- tioned were never large enough nor fast enough for serious arti?cial-neur- network (ANN) applications. But technology has now improved: the capacity and performance of current FPGAs are such that they present a much more realistic alternative. Consequently neurocomputers based on FPGAs are now a much more practical proposition than they have been in the past. This book summarizes some work towards this goal and consists of 12 papers that were selected, after review, from a number of submissions. The book is nominally divided into three parts: Chapters 1 through 4 deal with foundational issues; Chapters 5 through 11 deal with a variety of implementations; and Chapter 12 looks at the lessons learned from a large-scale project and also reconsiders design issues in light of current and future technology.

Neural networks (Computer science) --- Field programmable gate arrays. --- Field programmable logic arrays --- FPGAs --- Gate array circuits --- Programmable logic devices --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Artificial intelligence --- Natural computation --- Soft computing --- Systems engineering. --- Computer science. --- Engineering design. --- Software engineering. --- Computer engineering. --- Circuits and Systems. --- Computer Science, general. --- Engineering Design. --- Special Purpose and Application-Based Systems. --- Electrical Engineering. --- Processor Architectures. --- Informatics --- Science --- Engineering systems --- System engineering --- Engineering --- Industrial engineering --- System analysis --- Computers --- Computer software engineering --- Design, Engineering --- Industrial design --- Strains and stresses --- Design and construction --- Design --- Electronic circuits. --- Special purpose computers. --- Electrical engineering. --- Microprocessors. --- Minicomputers --- Electric engineering --- Special purpose computers --- Electron-tube circuits --- Electric circuits --- Electron tubes --- Electronics

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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 Bioinformatics 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.

Bioinformatics --- Computational biology --- Computer vision in medicine --- Bio-informatique --- Vision par ordinateur en médecine --- Congresses. --- Congrès --- Congresses --- Computational Biology --- Biology --- Biological Science Disciplines --- Natural Science Disciplines --- Disciplines and Occupations --- Computer Science --- Biology - General --- Engineering & Applied Sciences --- Health & Biological Sciences --- Life sciences. --- Database management. --- Information storage and retrieval. --- Artificial intelligence. --- Pattern recognition. --- Bioinformatics. --- Life Sciences. --- Computational Biology/Bioinformatics. --- Pattern Recognition. --- Database Management. --- Artificial Intelligence (incl. Robotics). --- Information Storage and Retrieval. --- Bio-informatics --- Biological informatics --- Information science --- Systems biology --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Data base management --- Data services (Database management) --- Database management services --- DBMS (Computer science) --- Generalized data management systems --- Services, Database management --- Systems, Database management --- Systems, Generalized database management --- Biosciences --- Sciences, Life --- Science --- Data processing --- Optical pattern recognition. --- Information storage and retrieva. --- Artificial Intelligence. --- Optical data processing --- Pattern perception --- Perceptrons --- Visual discrimination --- Information storage and retrieval systems. --- Automatic data storage --- Automatic information retrieval --- Automation in documentation --- Computer-based information systems --- Data processing systems --- Data storage and retrieval systems --- Discovery systems, Information --- Information discovery systems --- Information processing systems --- Information retrieval systems --- Machine data storage and retrieval --- Mechanized information storage and retrieval systems --- Computer systems --- Electronic information resources --- Data libraries --- Digital libraries --- Information organization --- Information retrieval

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The advancements of computational and informational techniques have enabled in silico testing of many lab-based experiments in life sciences before performing them in in vitro or in vivo. Though computational techniques are not capable of mimicking all wet-lab experiments, bioinformatics will inevitably play a major role in future medical practice. For example, in the pursuit of new drugs it can reduce the costs and complexity involved in expensive wet-lab experiments. It is expected that by 2010, sequencing of individual genomes will be affordable generating an unprecedented increase of life sciences data, in the form of sequences, expressions, networks, images, literature. Pattern recognition techniques lie at the heart of discovery of new insights into biological knowledge, as the presence of particular patterns or structure is often an indication of its function. The aim of the workshop series Pattern Recognition in Bioinformatics (PRIB) is to bring pattern recognition scientists and life scientists together to promote pattern recognition applications to solve life sciences problems. This volume presents the proceedings of the 2nd IAPR Workshop PRIB 2007 held in Singapore, October 1–2, 2007. It includes 38 technical contributions that were selected by the International Program Committee from 125 submissions. Each of these rigorously reviewed papers was presented orally at the workshop. The proceedings consists of six parts. Part 1: Sequence Analysis; Part 2: Prediction of Protein Structure, Interaction, and Localization; Part 3: Gene Expression Analysis; Part 4: Pathway Analysis; Part 5: Medical Informatics; and Part 6: Bioimaging.

Biomathematics. Biometry. Biostatistics --- Bioinformatics --- Computational biology --- Computer vision in medicine --- Bio-informatique --- Vision par ordinateur en médecine --- Congresses. --- Congrès --- Congresses --- Pattern Recognition, Automated --- Computational Biology --- Gene Expression --- Sequence Analysis --- Information Science --- Genetic Techniques --- Biology --- Genetic Processes --- Genetic Phenomena --- Biological Science Disciplines --- Investigative Techniques --- Analytical, Diagnostic and Therapeutic Techniques and Equipment --- Natural Science Disciplines --- Phenomena and Processes --- Disciplines and Occupations --- Computer Science --- Biology - General --- Engineering & Applied Sciences --- Health & Biological Sciences --- Computational bioCongresses. --- Life sciences. --- Mathematical statistics. --- Database management. --- Data mining. --- Artificial intelligence. --- Bioinformatics. --- Biochemistry. --- Life Sciences. --- Biochemistry, general. --- Database Management. --- Artificial Intelligence (incl. Robotics). --- Data Mining and Knowledge Discovery. --- Computational Biology/Bioinformatics. --- Probability and Statistics in Computer Science. --- Biological chemistry --- Chemical composition of organisms --- Organisms --- Physiological chemistry --- Chemistry --- Medical sciences --- Bio-informatics --- Biological informatics --- Information science --- Systems biology --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Data base management --- Data services (Database management) --- Database management services --- DBMS (Computer science) --- Generalized data management systems --- Services, Database management --- Systems, Database management --- Systems, Generalized database management --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Biosciences --- Sciences, Life --- Science --- Composition --- Data processing --- Statistical methods --- Computer science. --- Artificial Intelligence. --- Informatics