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检索条件"任意字段=IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology"

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Controlling cooperative and conflicting continuous actions with a Gene Regulatory Network

Controlling cooperative and conflicting continuous actions w...

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ieee symposium on computational intelligence and Games, CIG

作者： Sylvain Cussat-Blanc Stéphane Sanchez Yves Duthen University of Toulouse-IRIT Toulouse France DEMO Laboratory Volen National Center for Complex System Brandeis University MS018 Waltham MA USA

Artificial Gene Regulatory Networks (GRN) usually simulate cell behavior in developmental models. However, since 2003, GRN based controllers have been applied to robots to solve problems with few sensors and actuators. In this paper, we present our first steps toward an effective GRN-based controller for intelligent agents in video games. We will also introduce an experiment, the Radbot, where a robot has to handle and manage simultaneously four conflicting and cooperative continuous actions. Finally, we will show how a GRN-based controller can be evolved to solve the Radbot experiment.

关键词： Proteins Genomics bioinformatics Mathematical model Robots Cooling Games

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The ProGenGrid virtual laboratory for bioinformatics

The ProGenGrid virtual laboratory for bioinformatics

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Annual ieee symposium on Computer-Based Medical Systems

作者： Maria Mirto Marco Passante Giovanni Aloisio Euro Mediterranean Center for Climate Change (CMCC) University of Salento Lecce Lecce Italy

A virtual laboratory (VL) is an environment where the applications are available as reusable components and are exploited within (“in silico”) experiments. The purpose of a virtual laboratory is to support collaborative work of all the people who are involved in any stage of the experimental process. Problem Solving Environment (PSE) is an approach and a technology that is used for the definition and composition of complex applications, hiding programming and configuration details to the user that can concentrate instead only on the specific biological problem. PSE allows building virtual laboratories specialized for a specific domain, such as bioinformatics. At the University of Salento, we have developed ProGenGrid (Proteomics and Genomics Grid), a system which aims to provide a virtual laboratory where e-scientists can simulate biological experiments, composing existing analysis and visualization tools, monitoring their execution, storing the intermediate and final output and finally, if needed, saving the model of the experiment for updating or reproducing it at a later time. Different bioinformatics services and workflows have been deployed in the LIBI (International Laboratory of bioinformatics) project, aiming at setting up an advanced bioinformatics and computational biology laboratory, focusing on basic and applied research in modern biology and biotechnologies. In this paper we present recent developments in the ProGenGrid system, with a special focus on the possibility to configure a computational grid by using the workflow editor. This new feature of the system allows to the user to create his/her own personal grid on-the-fly, by adding, removing, or updating its computer configuration.

关键词： bioinformatics Laboratories Middleware Monitoring Proteins

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Object recognition on satellite images with biologically-inspired computational approaches

Object recognition on satellite images with biologically-ins...

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International symposium on Applied computational intelligence and Informatics ( SACI)

作者： M.I. Sina P. Payeur A.-M. Cretu Electrical Engineering and Computer Science University of Ottawa Ottawa Canada

The human vision system is often significantly superior in extracting and interpreting visual information when compared to classical computer vision systems. The exploitation of existing knowledge about human perception is expected to improve the performance of computational vision systems. computational visual attention has been reported to improve scene understanding performance. This paper discusses some of the difficulties faced by the current generation of visual attention systems when applied on satellite images. Next, a novel technique for top-down attention is devised which is based on the energy of bottom-up feature maps and overcomes some of the limitations of previous approaches. The computed top-down map is then used as a method of object localization in the object recognition phase that makes use of texture and shape information using local binary patterns, Legendre moments and Hu moment invariants. The proposed algorithm is shown to perform better than other similar systems on satellite images in many aspects.

关键词： biology Green products Image color analysis Image segmentation Vectors Image recognition

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Quantitative visualization in the computational biological sciences

Quantitative visualization in the computational biological s...

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Pacific (formerly Asia-Pacific APVIS) Visualization symposium

作者： Chandrajit Bajaj University of Texas Austin USA

Discoveries in computational molecular - cell biology and bioinformatics promise to provide new therapeutic interventions to disease. With the rapid growth of sequence and structural information for thousands of proteins and hundreds of cell types, computational processing are a restricting factor in obtaining quantitative understanding of molecular-cellular function. Processing and analysis is necessary both for input data (often from imaging) and simulation results. To make biological conclusions, this data must be input to and combined with results from computational analysis and simulations. Furthermore, as parallelism is increasingly prevalent, utilizing the available processing power is essential to development of scalable solutions needed for realistic scientific inquiry. However, complex image processing and even simulations performed on large clusters, multi-core CPU, GPU-type parallelization means that naïve cache unaware algorithms may not efficiently utilize available hardware. Future gains thus require improvements to a core suite of algorithms underpinning the data processing, simulation, optimization and visualization needed for scientific discovery. In this talk, I shall highlight current progress on these algorithms as well as provide several challenges for the visualization community.

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Keynote lectures

Keynote lectures

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ieee symposium on bioinformatics and Bioengineering (BIBE)

作者： Metin Akay Yuan-Ting Zhang Konstantina S. Nikita Miguel Andrade Christos Ouzounis University of Houston Houston TX US EE-CUHK Hong Kong China and Director of the Key Lab for Health Informatics of Chinese Academy of Sciences (HICAS) at SIAT Shenzhen China Electrical Engineering at the N.T.U.A. Athens Greece Computational Biology and Data Mining group Max Delbrück Center for Molecular Medicine Berlin Germany Centre for Research & Technology Hellas (CERTH) Thessalonica Greece

These tutorials/keynote speeches discuss the following: the effects of nicotine exposure on the complexity and the genetic patterns of dopamine neurons in VTA; from 6-Ps medicine to cardiovascular health informatics; computer-aided interpretation of vascular images towards valid diagnosis and risk stratification of atherosclerosis; turning data into predictions of gene and protein function; from reading to writing (and rewriting) the code of life: the future of biology - scientific, ethical, legal, civil and social issues.

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SlimCodeML: An Optimized Version of CodeML for the Branch-Site Model

SlimCodeML: An Optimized Version of CodeML for the Branch-Si...

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ieee International symposium on Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Hannes Schabauer Mario Valle Christoph Pacher Heinz Stockinger Alexandros Stamatakis Marc Robinson-Rechavi Ziheng Yang Nicolas Salamin University of Lausanne Department of Ecology and Evolution and SIB Swiss Institute of Bioinformatics (CH) Swiss National Supercomputing Centre Scientific Computing Group (CH) AIT Austrian Institute of Technology Safety & Security Department (AT) SIB Swiss Institute of Bioinformatics Vital-IT Group (CH) Heidelberg Institute for Theoretical Studies Scientific Computing Group (DE) Department of Biology University College London (UK)

CodeML (part of the PAML package) implements a maximum likelihood-based approach to detect positive selection on a specific branch of a given phylogenetic tree. While CodeML is widely used, it is very compute-intensive. We present SlimCodeML, an optimized version of CodeML for the branch-site model. Our performance analysis shows that SlimCodeML substantially outperforms CodeML (up to 9.38 times faster), especially for large-scale genomic analyses.

关键词： Symmetric matrices Phylogeny computational modeling Matrices Vectors bioinformatics Genomics

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Fast searching in biological sequences using multiple hash functions

Fast searching in biological sequences using multiple hash f...

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ieee symposium on bioinformatics and Bioengineering (BIBE)

作者： Simone Faro Thierry Lecroq Dip. di Matematica e Informatica Università di Catania Catania Italy LITIS EA 4108 Université de Rouen France

With the availability of large amounts of DNA data, exact matching of nucleotide sequences has become an important application in modern computational biology and in meta-genomics. In this paper we present an efficient method based on multiple hashing functions which improves the performance of existing string matching algorithms when used for searching DNA sequences. From our experimental results it turns out that the new proposed technique leads to algorithms which are up to 8 times faster than the best algorithm known for matching multiple patterns. It turns out also that the gain in performances is larger when searching for larger sets. Thus, considering the fact that the number of reads produced by next generation sequencing equipments is ever growing, the new technique serves a good basis for massive multiple long pattern search applications.

关键词： DNA Pattern matching bioinformatics Genomics Computers Standards

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In-silico organogenesis: Image-driven modelling of limb development

In-silico organogenesis: Image-driven modelling of limb deve...

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ieee International symposium on Biomedical Imaging

作者： James Sharpe EMBL-CRG Systems Biology Program Centre for Genomic Regulation ICREA Barcelona Spain

Mesoscopic imaging techniques, such as optical projection tomography (OPT) and single plane illumination microsopy (SPIM), are becoming invaluable tools to understand multicellular development. Our lab has worked on both of these technologies, with a focus on obtaining new data sets to be used as the basis of dynamical computer simulations. Here I will describe our work to transform a classical model of developmental biology - the developing vertebrate limb bud - into a quantitative model system for image-driven multiscale modeling. In particular, we have developed: (a) 3D and 4D quantitative data-capture tools [1], and (b) new multiscale simulation software. This integrated approach is allowing us to combine two of the primary questions of organogenesis: mechanical morphogenesis (the active cellular movements which lead to shaping of the tissue [2,3]), and molecular patterning (the spatial regulatory networks which control gene expression - [3] and unpublished work).

关键词： Biological system modeling computational modeling Systems biology Genomics bioinformatics Abstracts

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A distributed software package for global sensitivity analysis of biological models

A distributed software package for global sensitivity analys...

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ieee symposium on bioinformatics and Bioengineering (BIBE)

作者： Quang Tung Thai Seokjong Yu Yongseong Cho Department of Supercomputing Korea Institute of Science and Technology Information (KISTI) Daejeon Korea South

Mathematical modeling is a vital tool for studying biological systems. Due to the system complexity and technical challenges in molecular level measurement, it is commonly the case that a large number of model parameters have uncertain values. Analyzing model dynamics from a single estimated parameter set is insufficient and liable for misleading results. Global sensitivity analysis (GSA) has been recommended as a must-have step in the process of developing reliable models. However, the technique comes at high computation costs as it is based on Monte Carlo simulation which requires a large number of model evaluations and manipulating on massive data for sensitivity estimation. In this work, we develop a software package for global sensitivity estimation of biological models. The software is deployed on KISTI high performance computing (HPC) cluster environment to provide web-service to system biology modelers.

关键词： Biological system modeling Mathematical model computational modeling Sensitivity analysis Analytical models

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Discovery of MicroRNA markers: An SVM-based multiobjective feature selection approach

Discovery of MicroRNA markers: An SVM-based multiobjective f...

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ieee symposium on computational intelligence in bioinformatics and computational biology

作者： Mukhopadhyay, Anirban Maulik, Ujjwal Bandyopadhyay, Sanghamitra Department of Computer Science and Engineering University of Kalyani Kalyani-741235 India Department of Computer Science and Engineering Jadavpur University Kolkata-700032 India Machine Intelligence Unit Indian Statistical Institute Kolkata-700108 India

ISBN: (纸本)9781424498970

MicroRNAs (miRNAs) are small non-coding RNAs that have been shown to play important roles in gene regulation and various biological processes. The abnormal expression of some specific miRNAs often results in the development of cancer. In this article, we have utilized a multiobjective genetic algorithm-based feature selection algorithm wrapped with support vector machine (SVM) classifier for selecting promising miRNAs having differential expression in benign and malignant tissue samples. Subsequently, the non-dominated sets of promising miRNAs are aggregated into a single most promising miRNA subset. Finally, the Signal-to-Noise Ratio (SNR) statistic has been applied on the obtained miRNA subset for identifying potential miRNA markers that distinguish the two classes (benign and malignant) of tissue samples. The performance has been demonstrated on four real-life miRNA expression datasets for different SVM kernel functions and the identified miRNA markers are reported. © 2011 ieee.

关键词： Support vector machines

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