Many biological systems and objects are intrinsically fuzzy. Fuzzy set theory and fuzzy logic are ideal frameworks for describing some biological systems/objects and providing suitable computational methods for a wide...
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Many biological systems and objects are intrinsically fuzzy. Fuzzy set theory and fuzzy logic are ideal frameworks for describing some biological systems/objects and providing suitable computational methods for a widely range of bioinformatics problems. In this paper, we present two examples of using fuzzy set theory in bioinformatics, one in fuzzy measurement of ontological similarity and its application in bioinformatics, and the other in the application of the fuzzy k-nearest neighbor algorithm in protein secondary structure prediction. We also review other "fuzzy" methods for bioinformatics applications.
I will discuss the current state of progress in high performance computing, biomolecular simulation and algorithms as we are applying them to understanding a range of problems in the use of information technology to u...
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I will discuss the current state of progress in high performance computing, biomolecular simulation and algorithms as we are applying them to understanding a range of problems in the use of information technology to understand biological systems. Examples will include the use of pattern discovery algorithms to understand gene expression, the use of massively parallel supercomputing capabilities made available by the Blue Gene architecture to probe the dynamics of protein folding and trans membrane proteins and how this work will impact the translation of basic science into clinical research and ultimately into clinical practice.
Modern biology has become a science of information, analysis and prediction, coalescing into computational biology -- a single discipline at the crossroads of life sciences, informatics, and mathematics. New developme...
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Modern biology has become a science of information, analysis and prediction, coalescing into computational biology -- a single discipline at the crossroads of life sciences, informatics, and mathematics. New developments in information and communications technology as well as high-performance computing enable researchers to address new demanding scientific problems which seemed far out of reach only a few years ago. The computational requirements of most applications in computational biology differ significantly from the requirements of other users of highthroughput computing such as high energy physics. To address these needs, the SwissBioGrid initiative, a collaboration among several partner institutions with a broad spectrum of expertise, was started over a year ago. In this paper, we report on its current status and achievements as well as the lessons learned which are of interest to the wider e-Science and Grid communities.
This paper is focused on network and agent based intrusion detection systems. This paper includes an overview of several IDS implementations. Many approaches based on hidden Markov models and various forms of finite s...
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This paper is focused on network and agent based intrusion detection systems. This paper includes an overview of several IDS implementations. Many approaches based on hidden Markov models and various forms of finite state automata have been proposed to solve problem of detecting anomaly intrusion, a security attack in which an intruder assumes the identity of a legitimate user. It is proposed to give a general framework for IDS based on the application of techniques used in bioinformatics and agent technology. Our approach is focused on the application of techniques used in bioinformatics for a pair-wise sequence alignment and multiple sequence alignment to compare the monitored session with past user behavior. To achieve low false positive rate in this framework the intrusion can be detected by means of comparing the signature of the current user's session with already existing signatures of the potential intruder. The algorithms of computational biology such as approximation algorithm and Carillo-Lippman heuristic algorithm and sum-of-pairs scoring function are used to measure similarity between a sequence of commands produced by a potential intruder, the user signature and past intruder's signatures. Finally in this research work computationalbioinformatics techniques and agent technology are used to offer security in host and network to yield a promising combination of intrusion detection rate and false positive rate
bioinformatics algorithms such as sequence alignment methods based on profile-HMM (Hidden Markov Model) are popular but CPU-intensive. If large amounts of data are processed, a single computer often runs for many hour...
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ISBN:
(纸本)9781424430116
bioinformatics algorithms such as sequence alignment methods based on profile-HMM (Hidden Markov Model) are popular but CPU-intensive. If large amounts of data are processed, a single computer often runs for many hours or even days. High performance infrastructures such as clusters or computational Grids provide the techniques to speed up the process by distributing the workload to remote nodes, running parts of the work load in parallel. Biologists often do not have access to such hardware systems. Therefore, we propose a new system using a modern Grid approach to optimise an embarrassingly parallel problem. We achieve speed ups by at least two orders of magnitude given that we can use a powerful, world-wide distributed Grid infrastructure. For large-scale problems our method can outperform algorithms designed for mid-size clusters even considering additional latencies imposed by Grid infrastructures.
The following topics are dealt with: intelligent systems; systems modeling and control; manufacturing systems and industrial applications; Petri nets; human-machine systems; smart sensory networks; soft computing; rob...
The following topics are dealt with: intelligent systems; systems modeling and control; manufacturing systems and industrial applications; Petri nets; human-machine systems; smart sensory networks; soft computing; robotic systems and applications; image processing; intelligent transportation systems; enterprise information systems; grey systems; medical mechatronics; computational intelligence; infrastructure systems and services; modeling and automation; vehicle navigation and control; distributed intelligent systems; oceanology; pattern classification; conflict and risk analysis in systems management; vehicle dynamic systems and control; fuzzy systems; national/international security; bioinformatics; control systems; wireless sensor networks; multimedia systems; neural networks; nonlinear optimization of communication systems; fuzzy control; medical informatics; power systems; fuzzy systems; supply chain management; multi-agent systems; dynamic workflow modeling and management; intelligent Internet and media computing; service systems and service management; discrete event systems; intelligent control; granular computing; machine learning; decision support systems; uncertain systems.
Mobile IPv6 has been designed to manage movements of mobile nodes among wireless IPv6 networks. Nevertheless, a mobile node cannot receive IP packets on its new point of attachment until the handover completes. Theref...
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Sequence analysis is an important research method in bioinformatics. Constant time solutions on BSR can be found in the literature to many applications. In this paper, some problems of sequence analysis are involved, ...
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Sequence analysis is an important research method in bioinformatics. Constant time solutions on BSR can be found in the literature to many applications. In this paper, some problems of sequence analysis are involved, and the constant time solutions on BSR to them are proposed, which is the first constant time solutions to the problems on any model of computation
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