Datum vypracování: 2004-10-21


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Language: English

Abstract: Next generation applications and architectures (for example, Grids) are driving radical changes in the nature of traffic, service models, technology, and cost, creating opportunities for an advanced communications infrastructure to tackle next generation data services. To take advantage of these trends and opportunities, research communities are creating new architectures, such as the Open Grid Service Architecture (OGSA), which are being implemented in new prototype advanced infrastructures. The DWDM-RAM project, funded by DARPA, is actively addressing the challenges of next generation applications. DWDM-RAM is an architecture for data-intensive services enabled by next generation dynamic optical networks. It develops and demonstrates a novel architecture for new data communication services, within the OGSA context, that allows for managing extremely large sets of distributed data. Novel features move network services beyond notions of the network as a managed resource, for example, by including capabilities for dynamic on-demand provisioning and advance scheduling. DWDM-RAM encapsulates optical network resources (Lambdas, lightpaths) into a Grid Service and integrates their management within the Open Grid Service Architecture. Migration to emerging standards such as WS-Resource Framework (WS-RF) should be staright forward. In initial applications, DWDM-RAM targets specific data-intensive services such as rapid, massive data transfers used by large scale eScience applications, including: high-energy physics, geophysics, life science, bioinformatics, genomics, medical morphometry, tomography, microscopy imaging, astronomical and astrophysical imaging, complex modeling, and visualization.

44)


Soft Semantic Web services agent
Wang, Haibin; Zhang, Yan-Qing; Sunderraman, Rajshekhar
Department of Computer Science Georgia State University, Atlanta, GA 30302, United States
Conference: NAFIPS 2004 - Annual Meeting of the North American Fuzzy Information Processing Society: Fuzzy Sets in the Heart of the Canadian Rockies , Banff, Alta, Canada , 20040627-20040630 , (Sponsor: IEEE Systems, Man, and Cybernetics Society; North American Fuzzy Information Processing Society,NAFIPS; Institute of Electrical and Electronics Engineers, IEEE)
Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS NAFIPS 2004 - Annual Meeting of the North American Fuzzy Information Processing Society: Fuzzy Sets in the Heart of the Canadian Rockies v 1 2004. , 2004
Language: English

Abstract: Web services play an active role in the business integration and other fields such as bioinformatics. Current Web services technologies such as WSDL, UDDI, BPEL4WS and BSML are not semantic-oriented. Several proposals have been proposed to develop Semantic Web services to facilitate the discovery of relevant Web services. In our vision, with the mature of Semantic Web services technologies, there will be a lot of public or private Semantic Web services Registries based on specific ontologies. These Registries may provide a lot of similar Web services. So how to provide the high quality of service (QoS) Semantic Web services for specific domain using these Registries will be a challenge task. Different domains have different requirements of QoS, it is impractical to use classical mathematical modeling methods to evaluate the QoS of Semantic Web services. In this paper, we propose a framework called Soft Semantic Web services Agent (SSWSA) for providing high QoS Semantic Web services using soft computing methodology. And we will use fuzzy neural network with GA learning algorithm as our study case. Simulation result shows that the SSWSA could handle fuzzy and uncertain QoS metrics effectively.

45)


Asynchronous HMM with applications to speech recognition
Garg, Ashutosh; Balakrishnan, Sreeram; Vaithyanathan, Shivakumar
IBM Almaden Research Center, San Jose, CA 95120, United States
Conference: Proceedings - IEEE International Conference on Acoustics, Speech, and Signal Processing , Montreal, Que, Canada , 20040517-20040521 , (Sponsor: Institute of Electrical and Electronics Engineers,)
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings Proceedings - IEEE International Conference on Acoustics, Speech, and Signal Processing v 1 2004. , 2004
Language: English

Abstract: We develop a novel formalism for modeling speech signals which are irregularly or incompletely sampled. This situation can arise in real world applications where the speech signal is being transmitted over an error prone channel where parts of the signal can be dropped. Typical speech systems based on Hidden Markov Models, cannot handle such data since HMMs rely on the assumption that observations are complete and made at regular intervals. In this paper we introduce the asynchronous HMM, a variant of the inhomogenous HMM commonly used in Bioinformatics, and show how it can be used to model irregularly or incompletely sampled data. A nested EM algorithm is presented in brief which can be used to learn the parameters of this asynchronous HMM. Evaluation on real world speech data that has been modified to simulate channel errors, shows that this model and its variants significantly outperforms the standard HMM and methods based on data interpolation.

46)


Toward large-scale modeling of the microbial cell for computer simulation
Ishii, Nobuyoshi; Robert, Martin; Nakayama, Yoichi; Kanai, Akio; Tomita, Masaru
Conference: Highlights from the ECB11: Building Bridges Between Bioscience , Basel, Switzerland , 20030801-20030801
Journal of Biotechnology v 113 n 1-3 Sep 30 2004. p 281-294 , 2004
Language: English

Abstract: In the post-genomic era, the large-scale, systematic, and functional analysis of all cellular components using transcriptomics, proteomics, and metabolomics, together with bioinformatics for the analysis of the massive amount of data generated by these "omics" methods are the focus of intensive research activities. As a consequence of these developments, systems biology, whose goal is to comprehend the organism as a complex system arising from interactions between its multiple elements, becomes a more tangible objective. Mathematical modeling of microorganisms and subsequent computer simulations are effective tools for systems biology, which will lead to a better understanding of the microbial cell and will have immense ramifications for biological, medical, environmental sciences, and the pharmaceutical industry.In this review, we describe various types of mathematical models (structured, unstructured, static, dynamic, etc.), of microorganisms that have been in use for a while, and others that are emerging. Several biochemical/cellular simulation platforms to manipulate such models are summarized and the E-Cell system**1 developed in our laboratory is introduced. Finally, our strategy for building a "whole cell metabolism model", including the experimental approach, is presented. copy 2004 Elsevier B.V. All rights reserved.

47)


Bringing planning to autonomic applications with ABLE
Srivastava, Biplav; Bigus, Joseph P.; Schlosnagle, Donald A.
IBM India Research Laboratory IIT Delhi, Hauz Khas, New Delhi 110016, India
Conference: Proceedings - International Conference on Autonomic Computing , New York, NY, United States , 20040517-20040518 , (Sponsor: IEEE Computer Society; IBM; Sun Microsystems; National Science Foundation)
Proceedings - International Conference on Autonomic Computing Proceedings - International Conference on Autonomic Computing 2004. , 2004
Language: English

Abstract: Planning has received tremendous interest as a research area within AI over the last three decades but it has not been applied commercially as widely as its other AI counterparts like learning or data mining. The reasons are many: the utility of planning in business applications was unclear, the planners used to work best in small domains and there was no general purpose planning and execution infrastructure widely available. Much has changed lately. Compelling applications have emerged, e.g., computing systems have become so complex that the IT industry recognizes the necessity of deliberative methods to make these systems self-configuring, self-healing, self-optimizing and self-protecting. Planning has seen an upsurge in the last decade with new planners that are orders of magnitude faster than before and are able to scale this performance to complex domains, e.g., those with metric and temporal constraints. However, planning and execution infrastructure is still tightly tied to a specific application which can have its own idiosyncrasies. In this paper, we fill the infrastructural gap by providing a domain independent planning and execution environment that is implemented in the ABLE agent building toolkit, and demonstrate its ability to solve practical business applications. The planning-enabled ABLE is publicly available and is being used to solve a variety of planning applications in IBM including the self-management/autonomic computing scenarios.

48)


Design and implementation of a computational Grid for bioinformatics
Yang, Chao-Tung; Kuo, Yu-Lun; Lai, Chuan-Lin
High-Perf. Computing Laboratory Department of Computer Science Tunghai University, Taichung, 407, Taiwan
Conference: Proceedings - 2004 IEEE International Conference on e-Technology, e-Commerce and e-Service, EEE 2004 , Taipei, Taiwan , 20040328-20040331 , (Sponsor: IEEE Task Committee on E-Commerce; Fu-Jen University of Taiwan; BIKMrdc of Fu-Jen University; Academia Sinica; National Science Council of Taiwan)
Proceedings - 2004 IEEE International Conference on e-Technology, e-Commerce and e-Service, EEE 2004 Proceedings - 2004 IEEE International Conference on e-Technology, e-Commerce and e-Service, EEE 2004 2004. , 2004
Language: English

Abstract: The popular technologies, internet computing and Grid technologies promise to change the way we tackle complex problems. They will enable large-scale aggregation and sharing of computational, data and other resources across institutional boundaries. And harnessing these new technologies effectively will transform scientific disciplines ranging from high-energy physics to the life sciences. The computational analysis of biological sequences is a kind of computation driven science. Cause the biology data growing quickly and these databases are heterogeneous. We can use the grid system sharing and integrating the heterogeneous biology database. As we know, bioinformatics tools can speed up analysis the large-scale sequence data, especially about sequence alignment and analysis. The FASTA is a tool for aligning multiple protein or nucleotide sequences. These two bioinformatics software which we used is a distributed and parallel version. The software uses a message-passing library called MPI (Message Passing Interface) and runs on distributed workstation clusters as well as on traditional parallel computers. A grid computing environment is proposed and constructed on multiple Linux PC Clusters by using Globus Toolkit (GT) and SUN Grid Engine (SGE). The experimental results and performances of the bioinformatics tool using on grid system are also presented in this paper.

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Proceedings - Fourth IEEE symposium on bioinformatics and bioengineering, BIBE 2004
Anon (Ed.)
Conference: Proceedings - Fourth IEEE Symposium on Bioinformatics and Bioengineering, BIBE 2004 , Taichung, Taiwan , 20040519-20040521 , (Sponsor: IEEE Computer Society; IEEE Neural Networks Society; Taichung Healthcare and Management University, Taiwan; Ministry of Education, Taiwan; National Sciences Council, Taiwan; Institute for Information Industry, Taiwan)
Proceedings - Fourth IEEE Symposium on Bioinformatics and Bioengineering, BIBE 2004 Proceedings - Fourth IEEE Symposium on Bioinformatics and Bioengineering, BIBE 2004 2004. , 2004
Language: English

Abstract: The proceedings contains 73 papers from the conference on Fourth IEEE Symposium on Bioinformatics and Bioengineering, BIBE 2004. The topics discussed include: techniques for enhancing computation of DNA curvature molecules; towards automating an interventional radiological procedure; reducing the computational load of energy evaluations for protein folding; segmentation of the sylvian fissure in brain MR images; biomedical ontologies in post-genomic information systems; identifying significant genes from microarray data; good spaced seeds for homology search; and estimating seed sensitivity on homogeneous alignments.

50)


SemanticObjects and biomedical informatics
Kitazawa, Atsushi; Yoshimura, Masayoshi
Conference: Proceedings - Fourth IEEE Symposium on Bioinformatics and Bioengineering, BIBE 2004 , Taichung, Taiwan , 20040519-20040521 , (Sponsor: IEEE Computer Society; IEEE Neural Networks Society; Taichung Healthcare and Management University, Taiwan; Ministry of Education, Taiwan; National Sciences Council, Taiwan; Institute for Information Industry, Taiwan)
Proceedings - Fourth IEEE Symposium on Bioinformatics and Bioengineering, BIBE 2004 Proceedings - Fourth IEEE Symposium on Bioinformatics and Bioengineering, BIBE 2004 2004. , 2004
Language: English

Abstract: The use of SemanticObjects (SO) in biomedical informatics is discussed. SO is a virtual database supporting object relational data model accommodating nested relational data. It is observed that advances in biomedical informatics will lead to a new generation of database, knowledge base, software engineering, security, user interface and operating system technologies. Bioinformatics requires intelligent algorithm be developed to solve complex biomedical problems and also new tools to assist physicians and biologists to manage and utilize the large amount of information available.

51)


Automating the determination of open reading frames in genomic sequences using the web service techniques - A case study using SARS Coronavirus
Chang, Paul Hsueh-Min; Soo, Von-Wun; Chen, Tai-Yu; Lai, Wei-Shen; Su, Shiun-Cheng; Huang, Yu-Ling
Department of Computer Science National Tsing-Hua University, Hsinchu, 300, Taiwan
Conference: Proceedings - Fourth IEEE Symposium on Bioinformatics and Bioengineering, BIBE 2004 , Taichung, Taiwan , 20040519-20040521 , (Sponsor: IEEE Computer Society; IEEE Neural Networks Society; Taichung Healthcare and Management University, Taiwan; Ministry of Education, Taiwan; National Sciences Council, Taiwan; Institute for Information Industry, Taiwan)
Proceedings - Fourth IEEE Symposium on Bioinformatics and Bioengineering, BIBE 2004 Proceedings - Fourth IEEE Symposium on Bioinformatics and Bioengineering, BIBE 2004 2004. , 2004
Language: English

Abstract: As more and more new genome sequences were reported nowadays, analyzing the functions of a new genome sequence becomes more and more desirable and compelling. However, the determination of the functions of a genomic sequence is not an easy task. Even with several bioinformatic tools, the task is still a labor-intensive one. This is because human experts have to intervene during the processing of using these tools. For efficiency, immediacy and reduction of human labor, a system of automating the analyzing process is proposed. We take the automated determination of Open Reading Frames of a genomic sequence as the domain tasks that involve using a number of computational tools and interpreting the results returned from the tools. A service-oriented approach is taken, in which analyzing tools are wrapped as Web services and described in Semantic Web languages including OWL and OWL-S. The SARS Coronavirus genomic sequence is taken as a test case for our approaches. We are in the process of building an agent-based system for automating the tasks, in which an intelligent agent is responsible for understanding purposes of the Web services by parsing the service descriptions, and carrying out the interpretation tasks according to a workflow.

52)


Efficient filtration of sequence similarity search through singular value decomposition
Aghili, S. Alireza; Sahin, Ozgur D.; Agrawal, Divyakant; El Abbadi, Amr
Department of Computer Science Univ. of California Santa Barbara, Santa Barbara, CA 93106, United States
Conference: Proceedings - Fourth IEEE Symposium on Bioinformatics and Bioengineering, BIBE 2004 , Taichung, Taiwan , 20040519-20040521 , (Sponsor: IEEE Computer Society; IEEE Neural Networks Society; Taichung Healthcare and Management University, Taiwan; Ministry of Education, Taiwan; National Sciences Council, Taiwan; Institute for Information Industry, Taiwan)
Proceedings - Fourth IEEE Symposium on Bioinformatics and Bioengineering, BIBE 2004 Proceedings - Fourth IEEE Symposium on Bioinformatics and Bioengineering, BIBE 2004 2004. , 2004
Language: English

Abstract: Similarity search in textual databases and bioinformatics has received substantial attention in the past decade. Numerous filtration and indexing techniques have been proposed to reduce the curse of dimensionality. This paper proposes a novel approach to map the problem of whole-genome sequence similarity search into an approximate vector comparison in the well-established multidimensional vector space. We propose the application of the Singular Value Decomposition (SVD) dimensionality reduction technique as a pre-processing filtration step to effectively reduce the search space and the running time of the search operation. Our empirical results on a Prokaryote and a Eukaryote DNA contig dataset, demonstrate effective filtration to prune non-relevant portions of the database with up to 2.3 times faster running time compared with q-gram approach. SVD filtration may easily be integrated as a pre-processing step for any of the well-known sequence search heuristics as BLAST, QUASAR and FastA. We analyze the precision of applying SVD filtration as a transformation-based dimensionality reduction technique, and finally discuss the imposed trade-offs.

53)


An IDC-based algorithm for efficient homology filtration with guaranteed seriate coverage
Lee, Hsiao Ping; Shih, Ching Hua; Tsai, Yin Te; Sheu, Tzu Fang; Tang, Chuan Yi
Department of Computer Science National Tsing-Hua University, Hsinchu, Taiwan
Conference: Proceedings - Fourth IEEE Symposium on Bioinformatics and Bioengineering, BIBE 2004 , Taichung, Taiwan , 20040519-20040521 , (Sponsor: IEEE Computer Society; IEEE Neural Networks Society; Taichung Healthcare and Management University, Taiwan; Ministry of Education, Taiwan; National Sciences Council, Taiwan; Institute for Information Industry, Taiwan)
Proceedings - Fourth IEEE Symposium on Bioinformatics and Bioengineering, BIBE 2004 Proceedings - Fourth IEEE Symposium on Bioinformatics and Bioengineering, BIBE 2004 2004. , 2004
Language: English

Abstract: The homology search within genomic databases is a fundamental and crucial work for biological knowledge discovery. With exponentially increasing sizes and accesses of databases, the filtration approach, which filters impossible homology candidates to reduce the time for homology verification, becomes more important in bioinformatics. Most of known gram-based filtration approaches, like QUASAR, in the literature have limited error tolerance and would conduct potentially higher false-positives. In this paper, we present an IDC-based lossless filtration algorithm with guaranteed seriate coverage and error tolerance for efficient homology discovery. In our method, the original work of homology extraction with requested seriate coverage and error levels is transformed to a longest increasing subsequence problem with range constraints, and an efficient algorithm is proposed for the problem in this paper. The experimental results show that the method significantly outperforms QUASAR. On some comparable sensitivity levels, our homology filter would make the discovery more than three orders of magnitude faster than that QUASAR does, and more than four orders faster than the exhaustive search.

54)


ARMEDA II: Supporting genomic medicine through the integration of medical and genetic databases
Garcia-Remesal, M.; Maojo, V.; Billhardt, H.; Crespo, J.; Alonso-Calvo, R.; Perez-Rey, D.; Martin, F.; Sousa, A.
Biomedical Informatics Group Polytechnical University of Madrid, Madrid, Spain
Conference: Proceedings - Fourth IEEE Symposium on Bioinformatics and Bioengineering, BIBE 2004 , Taichung, Taiwan , 20040519-20040521 , (Sponsor: IEEE Computer Society; IEEE Neural Networks Society; Taichung Healthcare and Management University, Taiwan; Ministry of Education, Taiwan; National Sciences Council, Taiwan; Institute for Information Industry, Taiwan)
Proceedings - Fourth IEEE Symposium on Bioinformatics and Bioengineering, BIBE 2004 Proceedings - Fourth IEEE Symposium on Bioinformatics and Bioengineering, BIBE 2004 2004. , 2004
Language: English

Abstract: In this paper we present ARMEDA II, a project designed to integrate distributed heterogeneous medical and genetic databases in support of genomic medicine. In this project, we have followed a "virtual repository" or VR approach. Although VRs are entities that do not contain any data, but metadata, they give users the perception of being working with local repositories that integrate data from different and remote sources. Our approach is based on two basic operators employed to connect new databases to the system: mapping and unification. The mapping process produces what is called the "virtual conceptual schema" of the newly created VR while the unification process provides tools to create an integrated virtual schema for at least two pre-existing VRs. We tested the current implementation of ARMEDA II using two tumor databases, one containing information from a hospital and the other containing genetic data associated to the tumor samples. The performance of the system was also evaluated using a pre-created set of 30 queries. For all queries the test yielded promising results since the system successfully retrieved the correct information. The ARMEDA II project is the current version of an ongoing project developed in the framework of an European Commission funded project.

55)


European support to biomedical informatics development: In pursue of genomic medicine
Sanz, Ferran; Diaz, Carlos; Martin-Sanchez, Fernando; Bonis, Julio
Biomed. Informatics Research Group Munic. Inst. of Medical Research IMIM, Barcelona, Spain
Conference: Proceedings - Fourth IEEE Symposium on Bioinformatics and Bioengineering, BIBE 2004 , Taichung, Taiwan , 20040519-20040521 , (Sponsor: IEEE Computer Society; IEEE Neural Networks Society; Taichung Healthcare and Management University, Taiwan; Ministry of Education, Taiwan; National Sciences Council, Taiwan; Institute for Information Industry, Taiwan)
Proceedings - Fourth IEEE Symposium on Bioinformatics and Bioengineering, BIBE 2004 Proceedings - Fourth IEEE Symposium on Bioinformatics and Bioengineering, BIBE 2004 2004. , 2004
Language: English


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