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检索条件"任意字段=IEEE Computational Systems Bioinformatics Conference"

共 881 条记录，以下是511-520 订阅

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Computer Science as a Lens on the Sciences: 07

Computer Science as a Lens on the Sciences:

引用

ieee WIC ACM International conference on Web Intelligence (WI)

作者： Richard M. Karp University of California Berkeley USA

ISBN: (纸本)9780769530260

This talk will trace the growing influence of fundamental ideas from computer science on the nature of research in a number of scientific fields. There is a growing awareness that information processing lies at the heart of the processes studied in fields as diverse as quantum mechanics, statistical physics, nanotechnology, neuroscience, linguistics, economics and sociology. Increasingly, mathematical models in these fields are expressed in algorithmic languages and describe algorithmic processes. The speaker will briefly describe connections between quantum computing and the foundations of quantum mechanics, and between statistical mechanics and phase transitions in computation. He will indicate how the growth of the Web has created new phenomena to be investigated by sociologists and economists. He will then focus in greater detail on computational molecular biology, where the view of living cells as complex information processing systems has become the dominant paradigm, and will discuss specific algorithmic problems arising in the sequencing of genomes, the comparative analysis of the resulting genomic sequences,the modeling of networks of interacting proteins, and the associations between genetic variation and disease.

关键词： Computer science Lenses Quantum computing Quantum mechanics Biology computing Information processing Cells (biology) Genomics bioinformatics Heart

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Multilayer in-place learning networks: Multitask invariance and adaptive lateral connections

Multilayer in-place learning networks: Multitask invariance ...

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ieee International conference on Development and Learning, ICDL

作者： Juyang Weng Tianyu Luwang Weiya Shi Hong Lu Mingmin Chi Xiangyang Xue Department of Computer Science and Engineering Fudan University Shanghai China Michigan State University East Lansing MI USA

In the fields of neuroscience, psychology, computer science, and developmental robotics, currently there is a lack of biologically plausible general-purpose in-place learning models that incrementally learn multiple sensorimotor tasks, to develop "soft" multi-task-shared invariances in the internal representations while the human or robot interacts with its environment. The multilayer in-place learning network (MILN) (Weng and Luciw, 2006; Weng et al., 2007) is a developmental network aiming at this ambitious goal. This biologically inspired developmental model for sensorimotor pathways provides an unusually efficient learning algorithm whose simplicity, low computational complexity, and generality are set apart from typical conventional learning algorithms. It explains how a biological cortical layer uses three types of adaptive connections, bottom-up, lateral, and top-down to accomplish this very challenging goal through the miraculous developmental experience. The work presented here concentrates on multitask invariance and recent work about the adaptive lateral connections of the network.

关键词： Nonhomogeneous media Biological system modeling Genomics bioinformatics Neurons Neuroscience Computer science Robot sensing systems Human robot interaction Support vector machines

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bioinformatics and fuzzy logic

Bioinformatics and fuzzy logic

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ieee International conference on Fuzzy systems

作者： Xu, Dong Bondugula, Rajkumar Popescu, Mihail Keller, James Univ Missouri Dept Comp Sci Columbia MO 65211 USA Univ Missouri CS Bond Life Sci Ctr Columbia MO 65211 USA Univ Missouri Hlth Management & Informat Dept Columbia MO 65211 USA Univ Missouri Dept Elect & Comp Engn Columbia MO 65211 USA

ISBN: (纸本)9780780394889

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. I We also review other "fuzzy" methods for bioinformatics applications.

关键词： Biological systems

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computational grid-based 3-tier ART1 data mining for bioinformatics applications

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3rd International conference on Fuzzy systems and Knowledge Discovery

作者： Cho, Kyu Cheol Park, Da Hye Lee, Jong Sik Inha Univ Sch Comp Sci & Engn Nam Ku Inchon 402751 South Korea

ISBN: (纸本)3540459162

computational Grid technology has been noticed as an issue to solve large-scale bioinformatics-related problems and improves data accuracy and processing speed on multiple computation platforms with distributed bioDATA sets. This paper focuses on a GPCR data mining processing which is an important bioinformatics application. This paper proposes a Grid-based 3-tier ART1 classifier which operates an ART1 clustering data mining using grid computational resources with distributed GPCR data sets. This Grid-based 3-tier ART1 classifier is able to process a large-scale bioinformatics application in guaranteeing high bioDATA accuracy with reasonable processing resources. This paper evaluates performance of the Grid-based ART1 classifier in comparing to the ART1-based classifier and the ART1 optimum classifier. The data mining processing time of the Grid-based ART1 classifier is 18% data mining processing time of the ART1 optimum classifier and is the 12% data mining processing time of the ART1-based classifier. And we evaluate performance of the Grid-based 3-tier ART1 classifier in comparing to the Grid-based ART1 classifier. As data sets become larger, data mining processing time of the Grid-based 3-tier ART1 classifier more decrease than that of the Grid-based ART1 classifier. computational Grid in bioinformatics applications gives a great promise of high performance processing with large-scale and geographically distributed bioDATA sets.

关键词： Data mining

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Front gene to drug: A proof of concept for a plausible computational pathway

Front gene to drug: A proof of concept for a plausible compu...

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ISDA 2006: Sixth International conference on Intelligent systems Design and Applications

作者： Shenoy, Sandhya Jayaram, B. Latha, N. Narang, Pooja Jain, Tarun Bhushan, Kumkum Shaikh, Saher Afshan Bose, Surojit Sharma, Pankaj Singhal, Poonam Gandhimathi, A. Agrawal, Praveen Pandey, Vidhu Dutta, Samrat Sandhu, Gurvisha Gupta, Anuj Shekhar, Shashank Tripathi, Shailesh Department of Chemistry Supercomputing Facility for Bioinformatics and Computational Biology Indian Institute of Technology Hauz Khas New Delhi-110016 India

ISBN: (纸本)0769525288

The last decade has witnessed an exponential growth of sequence information in the field of biological macromolecules such as proteins and nucleic acids and their interactions with other molecules. computational analyses for structure-function predictions based on such information are increasingly becoming an essential and integral part of modern biology. With rapid advances in the area, there is a growing need to develop efficient versatile bioinformatics software packages, which are hypothesis driven. 'Gene to Drug' is an attempt in this pursuit and an integration of heterologous applications of different technologies developed in-house and their translation into in silico products that cater to a majority of bioinformatics applications. This paper briefly presents the science behind Gene to Drug and how grid services and high performance computing platforms can be harnessed to bridge the gap between biomolecular sequence, structure and function. © 2006 ieee.

关键词： Macromolecules

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Grid approach to embarrassingly parallel CPU-intensive bioinformatics problems

Grid approach to embarrassingly parallel CPU-intensive bioin...

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e-Science 2006 - 2nd ieee International conference on e-Science and Grid Computing

作者： Stockinger, Heinz Pagni, Marco Cerutti, Lorenzo Falquet, Laurent Swiss Institute of Bioinformatics Vital-IT Quartier Sorge - Batiment Genopode CH-1015 Lausanne Switzerland

ISBN: (纸本)0769527345

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. © 2006 ieee.

关键词： Grid computing

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e-Science 2006 - Second ieee International conference on e-Science and Grid Computing

e-Science 2006 - Second IEEE International Conference on e-S...

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e-Science 2006 - 2nd ieee International conference on e-Science and Grid Computing

ISBN: (纸本)0769527345

The proceedings contain 152 papers. The topics discussed include: benefits of e-science for the physiome project;grid enabling data de-duplication;emerging technologies and applications for e-science;grid based flood prediction virtual organization;complex dynamics in the plankton: computational science applied to the world's oceans;national grid initiatives: lessons learned and recommendations;dynamic infrastructure for systems level science;from bioinformatics towards e-bioscience;grid organizational memory: a versatile solution for ontology management in the grid;interactive workflows in a virtual laboratory for e-bioscience: the SigWin-Detector Tool for gene expression analysis;adapting and evaluating commercial workflow engines for e-science;communication over a secured heterogeneous grid with the GriddLeS runtime environment;and domain based access control model for distributed collaborative applications.

关键词： Grid computing

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Information distance

Information distance

引用

2006 ieee International conference on Granular Computing

作者： Li, Ming Department of Bioinformatics University of Waterloo Canada

ISBN: (纸本)1424401348

We live an information society. Internet has created the cyber, or information, space. In the classical Newton world, we know how to measure physical distances. Have you thought about the equally fundamental question of how to measure the information distance between two objects: two documents, two letters, two emails, two music scores, two languages, two programs, two pictures, two systems, or two genomes? Such a measurement should not be application dependent. Just like in the classical world, we do not measure distances sometimes by the amount of time a bird flies and sometimes by the number of pebbles lining up on the Santa Barbara beach. A good information distance metric must be application-independent and universally minorize all other "reasonable" definitions for specific applications. From a simple and accepted assumption in thermodynamics, we derive a universal information distance [1, 5] and a general method to measure similarities between two sequences [3, 4]. We then apply the theory to infer the evolutionary histories of mammals [3], chain letters [2], languages, and programs (plagiarism detection), and obtain a parameter-free data mining paradigm [6], among many recent applications. © 2006 ieee.

关键词： Information technology

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Nonlinear system identification provides insight into protein folding

Nonlinear system identification provides insight into protei...

引用

19th ieee Canadian conference on Electrical and Computer Engineering

作者： Green, James R. Korenberg, Michael J. Carleton Univ Syst & Comp Engn Ottawa ON K1S 5B6 Canada Queens Univ Elect & Dept Comp Ottawa ON K1S 5B6 Canada

ISBN: (纸本)9781424400379

Much like the shape of a tool suggests its intended purpose, knowledge of a protein's structure can provide substantial insight into its function. Therefore, computational prediction of protein structure based solely on protein sequence data is a challenge of fundamental importance to biomedical research. An effective solution promises significant advances in computational drug discovery and an increased understanding of complex disease processes such as cancer. We have recently developed a novel approach to determining the secondary structure of proteins from protein sequence data which makes use of Parallel Cascade Identification (M), a powerful method of nonlinear system identification. PCI is used to create two layers of dynamic nonlinear systems that map divergent evolutionary profile input data into secondary structure assignment output data. PCI prediction accuracy compares well with eleven top contemporary methods over a dataset of new protein structures. Furthermore, PCI is a highly effective means to combine multiple experts achieving the highest observed accuracy over two test datasets and also the lowest rate of occurrence of a particularly detrimental class of errors. One limitation of the PCI classifiers is that approximately 13% of all amino acids cannot readily be assigned predictions due to settling times introduced by the dynamic linear component in each cascade model. In this paper we describe a number of methods designed to overcome this limitation. While zero-padding of the input sequence data proved to be the most effective solution in terms of prediction accuracy, an analysis of causal, anti-causal, and mixed cascades provides interesting insights into the biological mechanism of protein folding.

关键词： protein secondary structure prediction nonlinear system identification parallel cascade identification bioinformatics

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Locality and parallelism optimization for dynamic programming algorithm in bioinformatics

Locality and parallelism optimization for dynamic programmin...

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2006 ACM/ieee conference on Supercomputing, SC'06

作者： Tan, Guangming Feng, Shengzhong Sun, Ninghui Key Laboratory of Computer System and Architecture Institute of Computing Technology Chinese Academy of Sciences Graduate School Chinese Academy of Sciences

ISBN: (纸本)0769527000

Dynamic programming has been one of the most efficient approaches to sequence analysis and structure prediction in biology. However, their performance is limited due to the drastic increase in both the number of biological data and variety of the computer architectures. With regard to such predicament, this paper creates excellent algorithms aimed at addressing the challenges of improving memory efficiency and network latency tolerance for nonserial polyadic dynamic programming where the dependences are nonuniform. By relaxing the nonuniform dependences, we proposed a new cache oblivious scheme to enhance its performance on memory hierarchy architectures. Moreover we develop and extend a tiling technique to parallelize this nonserial polyadic dynamic programming using an alternate block-cyclic mapping strategy for balancing the computational and memory load, where an analytical parameterized model is formulated to determine the tile volume size that minimizes the total execution time and an algorithmic transformation is used to schedule the tile to overlap communication with computation to further minimize communication overhead on parallel architectures. The numerical experiments were carried out on several high performance computer systems. The new cache-oblivious dynamic programming algorithm achieve 2-10 speedup and the parallel tiling algorithm with communication-computation overlapping shows a desired potential for fine-grained parallel computing on massively parallel computer systems. © 2006 ieee.

关键词： Dynamic programming

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