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

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Efficient basin hopping in the protein energy surface 2012

Efficient basin hopping in the protein energy surface

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2012 ieee International conference on bioinformatics and Biomedicine, BIBM2012

作者： Olson, Brian Shehu, Amarda Department of Computer Science George Mason University Fairfax VA 22030 United States Department of Bioinformatics and Computational Biology George Mason University Fairfax VA 22030 United States Department of Bioengineering George Mason University Fairfax VA 22030 United States

ISBN: (纸本)9781467325585

The vast and rugged protein energy surface can be effectively represented in terms of local minima. The basin-hopping framework, where a structural perturbation is followed by an energy minimization, is particularly suited to obtaining this coarse-grained representation. Basin hopping is effective for small systems both in locating lower-energy minima and obtaining conformations near the native structure. The efficiency decreases for large systems. Our recent work improves efficiency on large systems through molecular fragment replacement. In this paper, we conduct a detailed investigation of two components in basin hopping, perturbation and minimization, and how they work in concert to affect the sampling of near-native local minima. We show that controlling the magnitude of perturbation jumps is related to the ability to effectively steer the exploration towards conformations near the protein native state. In minimization, we show that a simple greedy search is just as effective as Metropolis Monte Carlo-based minimization. Finally, we show that an evolutionary-inspired approach based on the Pareto front is particularly effective in reducing the ensemble of sampled local minima and obtains a simpler representation of the probed energy surface. © 2012 ieee.

关键词： Proteins

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SAMasGC: Sequencing Analysis with a Multiagent System and Grid Computing

SAMasGC: Sequencing Analysis with a Multiagent System and Gr...

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6th International conference on Practical Applications of computational Biology and bioinformatics (PACBB)

作者： Gonzalez, Roberto Zato, Carolina Benito, Rocio Hernandez, Maria Hernandez, Jesus M. De Paz, Juan F. Univ Salamanca Dept Comp Sci Plaza Merced S-N E-37008 Salamanca Spain Univ Salamanca CSIC Ctr Canc Res IBMCC Salamanca Spain Hosp Univ Salamanca Hematol Serv Salamanca Spain

ISBN: (纸本)9783642288388

Advances in bioinformatics have contributed towards a significant increase in available information. Information analysis requires the use of distributed computing systems to best engage the process of data analysis. This study proposes a multiagent system that incorporates grid technology to facilitate distributed data analysis by dynamically incorporating the roles associated to each specific case study. The system was applied to genetic sequencing data to extract relevant information about insertions, deletions or polymorphisms.

关键词： Multiagent system Grid Computing genetic sequencing distributed computing bioinformatics

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Efficient Processing of Models for Large-scale Shotgun Proteomics Data

Efficient Processing of Models for Large-scale Shotgun Prote...

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8th ieee International conference on Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom)

作者： Grover, Himanshu Gopalakrishnan, Vanathi Univ Pittsburgh Dept Biomed Informat Pittsburgh PA 15206 USA Univ Pittsburgh Intelligent Syst Program Pittsburgh PA 15206 USA Univ Pittsburgh Computat & Syst Biol Dept Pittsburgh PA 15206 USA

ISBN: (纸本)9781467327404;9781467327404

Mass-spectrometry (MS) based proteomics has become a key enabling technology for the systems approach to biology, providing insights into the protein complement of an organism. bioinformatics analyses play a critical role in interpretation of large, and often replicated, MS datasets generated across laboratories and institutions. A significant amount of computational effort in the workflow is spent on the identification of protein and peptide components of complex biological samples, and consists of a series of steps relying on large database searches and intricate scoring algorithms. In this work, we share our efforts and experience in efficient handling of these large MS datasets through database indexing and parallelization based on multiprocessor architectures. We also identify important challenges and opportunities that are relevant specifically to the task of peptide and protein identification, and more generally to similar multi-step problems that are inherently parallelizable.

关键词： bioinformatics High-throughput Proteomics Indexing Multiprocessing Parallelization

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A GRASP-based heuristic for the project portfolio selection problem

A GRASP-based heuristic for the project portfolio selection ...

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15th ieee International conference on computational Science and Engineering, CSE 2012 and 10th ieee/IFIP International conference on Embedded and Ubiquitous Computing, EUC 2012

作者： Mira, Cleber Feijão, Pedro Souza, Maria Angélica Moura, Arnaldo Meidanis, João Lima, Gabriel Schmitz, Rafael Bossolan, Renato P. Freitas, Ítalo T. Scylla Bioinformatics Campinas Brazil Institute of Computing Unicamp Campinas Brazil AES-Tietê Brazil Mechanical Engineering Department Unicamp Campinas Brazil

ISBN: (纸本)9780769549149

The project portfolio selection (PPS) problem consists of constructing a project portfolio, that is, a selection of projects scheduled over a period of time using various, potentially conflicting, criteria and resource constraints. The PPS is a well-known problem, recurrently occurring in several applications, with a rich history of approaches for modeling it and a large number of techniques for solving it. In this work we present a model for the PPS problem based on a real-world situation of selection and scheduling of projects in the power generation industry. We also propose a heuristic, based on the metaheuristic GRASP, to solve the problem, and assess its quality and performance through computational experiments. We describe the implementation of a decision support system prototype for the PPS problem that uses the proposed heuristic and includes several usability features that may help decision makers through the selection process. © 2012 ieee.

关键词： Decision support systems

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An energy-aware bioinformatics application for assembling short reads in high performance computing systems

An energy-aware bioinformatics application for assembling sh...

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2012 10th Annual International conference on High Performance Computing and Simulation, HPCS 2012

作者： Warnke, Julia Pawaskar, Sachin Ali, Hesham College of Information Science and Technology University of Nebraska at Omaha Omaha NE 68182 United States

ISBN: (纸本)9781467323598

Current biomedical technologies are producing massive amounts of data on an unprecedented scale. The increasing complexity and growth rate of biological data has made bioinformatics data processing and analysis a key and computationally intensive task. High performance computing (HPC) has been successfully applied to major bioinformatics applications to reduce computational burden. However, a naïve approach for developing parallel bioinformatics applications may achieve a high degree of parallelism while unnecessarily expending computational resources and consuming high levels of energy. As the wealth of biological data and associated computational burden continues to increase, there has become a need for the development of energy efficient computational approaches in the bioinformatics domain. To address this issue, we have developed an energy-aware scheduling (EAS) model to run computationally intensive applications that takes both deadline requirements and energy factors into consideration. An example of a computationally demanding process that would benefit from our scheduling model is the assembly of short sequencing reads produced by next generation sequencing technologies. Next generation sequencing produces a very large number of short DNA reads from a biological sample. Multiple overlapping fragments must be aligned and merged into long stretches of contiguous sequence before any useful information can be gathered. The assembly problem is extremely difficult due to the complex nature of underlying genome structure and inherent biological error present in current sequencing technologies. We apply our EAS model to a newly proposed assembly algorithm called Merge and Traverse, giving us the ability to generate speedup profiles. Our EAS model was also able to dynamically adjust the number of nodes needed to meet given deadlines for different sets of reads. © 2012 ieee.

关键词： bioinformatics

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Development of Multi-compartment Model of the Liver Using Image-based Meshing Software

Development of Multi-compartment Model of the Liver Using Im...

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34th Annual International conference of the ieee Engineering-in-Medicine-and-Biology-Society (EMBS)

作者： Barthod-Malat, Annick Kopylova, Veronika Podoprigora, Gennady I. Nartsissov, Yaroslav R. Angoue, Orland Young, Philippe G. Crolet, Jean-Marie Blagosklonov, Oleg Univ Hosp Inst Engn Franche Comte F-25030 Besancon France

ISBN: (纸本)9781457717871

Computer simulation of biological systems for in silico validation has the potential of increasing the efficiency of pharmaceutical research and development by expanding the number of parameters tested virtually. Then only the most interesting subset of these has to be probed in vivo. By focusing on variables with the greatest influence on clinical end points, valuable drug targets can be advanced more quickly. A large number of methods have been developed to rebuild a three-dimensional (3D) model of a liver, mostly to prepare a liver surgery. These models are often not accurate and most of the them don't take into account the fluidics inside the vessels. The aim of this work is to provide an accurate computational multi-compartement model of the healthy and the pathological liver with their network of blood vessels (vasculature) using a finite-element-modeling software. Computed tomography (CT) slices, in DICOM format, from two different patients were used to provide the datasets of transverse images for the modeling. Each dataset of images was segmented in order to extract the liver's shape and define the vein and artery networks. On CT images, the contrast between the liver and the nearby organs (background) is very low because all these structures are a similar density. Thus, we used semi-automatic tools to determine liver contours. Manual segmentation was used as a last resort. Then, strong filtering (bilateral filter) and confidence-connected-region-growing algorithm were applied to rebuild from each - healthy and pathological - liver a multi-compartment model including parenchyma, arteries and veins. The precision of the obtained vasculature model allowed anatomical classification of hepatic segments and the quantification of their volumes. Although our study demonstrated the difficulties in use of CT images for computational modeling of the liver, it also confirmed that semi-automatic tools can be used to develop anatomically accurate models of hepatic vascu

关键词： bioinformatics

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6th International conference on Practical Applications of computational Biology and bioinformatics

6th International Conference on Practical Applications of Co...

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6th International conference on Practical Applications of computational Biology and bioinformatics, PACBB'12

ISBN: (纸本)9783642288388

The proceedings contain 32 papers. The topics discussed include: prognostic prediction using clinical expression time series: towards a supervised learning approach based on meta-biclusters;parallel e-CCC-biclustering: mining approximate temporal patterns in gene expression time series using parallel biclustering;parameter influence in genetic algorithm optimization of support vectormachines;biological knowledge integration in DNA microarray gene expression classification based on rough set theory;quantitative assessment of estimation approaches for mining over incomplete data in complex biomedical spaces: a case study on cerebral aneurysms;case-based reasoning to classify endodontic retreatments;a comparative analysis of balancing techniques and attribute reduction algorithms;sliced model checking for phylogenetic analysis;and a systematic approach to the interrogation and sharing of standardized biofilm signatures.

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The emerging field of synthetic biology: A review

The emerging field of synthetic biology: A review

引用

2012 4th International conference on Intelligent and Advanced systems, ICIAS 2012

作者： Habibi, Narjeskhatoon Hashim, Siti Zaiton Mohd Rodriguez, Cesar A. Mohamad, Mohd Saberi Bin Deris, Safaai Bin Soft Computing Research Group Faculty of Computer Science and Information Systems Universiti Teknologi Malaysia Malaysia Genome Compiler Corporation United States Artificial Intelligence And. Bioinformatics Laboratory Faculty of Computer Science and Information Systems Universiti Teknologi Malaysia Malaysia

ISBN: (纸本)9781457719677

Synthetic biology which is concerned with engineering organisms to perform novel functions and developing the ways by which organisms can be engineered easily and robustly, is a relatively young field with a large potential for growth. Much of the work in the field involves design and construction of genetic circuitry, the piecing together of biological parts, such as promoters and ribosome binding sites, to form the basis for biological devices which are organisms that have an engineered, well-specified input-output behavior. The idea in synthetic biology is applying engineering principles, such as hierarchical design, modular reusable parts and standard interfaces to construct bio-systems. The results of these engineering efforts can be of great value to human interests such as medicine and industry. In this paper first some related terms and resources for synthetic biology are described. Then existing computational tools and methods for synthetic biology are explored. It is followed by a discussion on current challenges in the field and future directions and finally by conclusion. © 2012 ieee.

关键词： Binding sites

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Predicting protein-RNA residue-base contacts using two-dimensional conditional random field

Predicting protein-RNA residue-base contacts using two-dimen...

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2012 ieee 6th International conference on systems Biology, ISB 2012

作者： Hayashida, Morihiro Kamada, Mayumi Song, Jiangning Akutsu, Tatsuya Bioinformatics Center Institute for Chemical Research Kyoto University Gokasho Uji Kyoto 611-0011 Japan Department of Biochemistry and Molecular Biology Monash University Clayton VIC 3800 Australia Tianjin Institute of Industrial Biotechnology Chinese Academy of Sciences Tianjin 300308 China

ISBN: (纸本)9781467343985

Understanding of interactions between proteins and RNAs is essential to reveal networks and functions of molecules in cellular systems. Many studies have been done for analyzing and investigating interactions between protein residues and RNA bases. For interactions between protein residues, it is supported that residues at interacting sites have co-evolved with the corresponding residues in the partner protein to keep the interactions between the proteins. In our previous work, on the basis of this idea, we calculated mutual information (MI) between residues from multiple sequence alignments of homologous proteins for identifying interacting pairs of residues in interacting proteins, and combined it with the discriminative random field (DRF), which is useful to extract some characteristic regions from an image in the field of image processing, and is a special type of conditional random fields (CRFs). In a similar way, in this paper, we make use of mutual information for predicting interactions between protein residues and RNA bases. Furthermore, we introduce labels of amino acids and bases as features of a simple two-dimensional CRF instead of DRF. To evaluate our method, we perform computational experiments for several interactions between Pfam domains and Rfam entries. The results suggest that the CRF model with MI and labels is more useful than the CRF model with only MI. © 2012 ieee.

关键词： Proteins

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Towards Scalable Optimal Sequence Homology Detection

Towards Scalable Optimal Sequence Homology Detection

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19th International conference on High Performance Computing (HiPC)

作者： Daily, Jeff Krishnamoorthy, Sriram Kalyanaraman, Ananth Pacific NW Natl Lab Richland WA 99352 USA

ISBN: (纸本)9781467323703;9781467323727

The field of bioinformatics and computational biology is experiencing a data revolution - experimental techniques to procure data have increased in throughput, improved in accuracy and reduced in costs. This has spurred an array of high profile sequencing and data generation projects. While the data repositories represent untapped reservoirs of rich information critical for scientific breakthroughs, the analytical software tools that are needed to analyze large volumes of such sequence data have significantly lagged behind in their capacity to scale. In this paper, we address homology detection, which is a fundamental problem in large-scale sequence analysis with numerous applications. We present a scalable framework to conduct large-scale optimal homology detection on massively parallel super-computing platforms. Our approach employs distributed memory work stealing to effectively parallelize optimal pairwise alignment computation tasks. Results on 120,000 cores of the Hopper Cray XE6 supercomputer demonstrate strong scaling and up to 2.42 x 10(7) optimal pairwise sequence alignments computed per second (PSAPS), the highest reported in the literature.

关键词： Cray computers DNA bioinformatics distributed memory systems mainframes parallel machines pattern recognition

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