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

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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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ieee International conference on computational Science and Engineering, CSE

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

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.

关键词： Portfolios Linear programming Prototypes Upper bound Manuals Decision support systems Optimization

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BioFactory: Semantic Integration of Biomedical Data and Applications

BioFactory: Semantic Integration of Biomedical Data and Appl...

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ieee International conference on Internet Operating systems (ICIOS)

作者： Charles C.N. Wang David A. Hecht Phillip Sheu Hiroshi Yamaguchi Jeffrey J.P. Tsai Department of Biomedical Informatics Asia University Taiwan Department of Chemistry Southwestern College USA Department of EECS University of California Irvine USA Research and Development Initiative Chuo University Japan

Web services have become increasingly important in biomedical research as tools that allow databases and algorithms to be accessed programmatically as computational components in programs. Various biomedical web services differ in their definitions and invocation protocols, as well as their communication and data formats and this presents a barrier to biomedical web service interoperability and integration. In this study, we present Biofactory, a web portal that collects and integrates biomedical web services. Users are able to register/search by semantic computation. The semantic computing and Semantic Description language (SDL) seems ideally suited to help streamline the collection of different biomedical services by providing a common language and a generic format for problem formalization.

关键词： Web services Semantics Databases Biological system modeling Mathematical model bioinformatics Data models

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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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ieee International conference on systems Biology

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

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.

关键词： RNA Amino acids Mutual information Protein sequence Random variables computational modeling

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Invited: Identifying mutations from TILLING experiments

Invited: Identifying mutations from TILLING experiments

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ieee International conference on computational Advances in Bio and Medical Sciences (ICCABS)

作者： Vladimir Filkov Department of Computer Science University of California Davis Davis CA USA

TILLING (Targeting Induced Local Lesions IN Genomes) is a reverse genetics approach to detect effects of globally induced mutations in a population and identify the individuals that have mutations in genes of interest. As long as the DNA sequence of the target gene is known and the organism of interest can be mutagenized, TILLING provides mutations in species where tools applicable to other model systems are unavailable. Importantly, organisms amenable to TILLING include both commercially valuable species such as rice, wheat, soybean, brassica, oat, and melon, and species important for research such as medaka, zebra fish, fruit flies, arabidopsis and nematodes. TILLING -by -Sequencing leverages next-generation sequencing and an overlapping pooled experimental design. It follows up the mutagenesis with deep sequencing of pools of individuals or populations of interest. Because of the high throughput of current sequencing technologies, deep sequencing to hundred and thousand fold coverage is possible [1]. Here I present on our method, Coverage Aware Mutation calling using Bayesian analysis, CAMBa, (read like the dance), which directly considers the pooled setup and sequencing coverage levels when calculating mutation and noise probabilities. Using data from two TILLING experiments, one with lower sequencing coverage variablility and data quality and the other with higher, we validate CAMBa's efficacy in identifying mutations, and demonstrate that it outperforms significantly other methods on sequence data of lower quality and higher variance in coverage across pools. We show that our method effectively discovers mutations in large populations with sensitivity of 92.5% and specificity of 99.8% [2].

关键词： bioinformatics Organisms Bayesian methods DNA Genomics

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Common motifs in scientific workflows: An empirical analysis

Common motifs in scientific workflows: An empirical analysis

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ieee International conference on e-Science and Grid Computing

作者： Daniel Garijo Pinar Alper Khalid Belhajjame Oscar Corcho Yolanda Gil Carole Goble Ontology Engineering Group Universidad Politécnica de Madrid The University of Manchester Manchester Manchester GB School of Computer Science University of Manchester Department of Computer Science University of Southern California

While workflow technology has gained momentum in the last decade as a means for specifying and enacting computational experiments in modern science, reusing and repurposing existing workflows to build new scientific experiments is still a daunting task. This is partly due to the difficulty that scientists experience when attempting to understand existing workflows, which contain several data preparation and adaptation steps in addition to the scientifically significant analysis steps. One way to tackle the understandability problem is through providing abstractions that give a high-level view of activities undertaken within workflows. As a first step towards abstractions, we report in this paper on the results of a manual analysis performed over a set of real-world scientific workflows from Taverna and Wings systems. Our analysis has resulted in a set of scientific workflow motifs that outline i) the kinds of data intensive activities that are observed in workflows (data oriented motifs), and ii) the different manners in which activities are implemented within workflows (workflow oriented motifs). These motifs can be useful to inform workflow designers on the good and bad practices for workflow development, to inform the design of automated tools for the generation of workflow abstractions, etc.

关键词： Data visualization Cleaning Genomics bioinformatics Drugs Servers Humans

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A Multibody Atomic Statistical Potential for the Prediction of Enzyme-Inhibitor Binding Energy

A Multibody Atomic Statistical Potential for the Prediction ...

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Annual International conference of the ieee Engineering in Medicine and Biology Society

作者： Majid Masso the Laboratory for Structural Bioinformatics School of Systems Biology George Mason University Manassas VA 20110 USA

ISBN: (纸本)9781424441198

Accurate prediction of enzyme-inhibitor binding energy has the capacity to speed drug design and chemical genomics efforts by helping to narrow the focus of experiments. Here a non-redundant set of three hundred high-resolution crystallographic enzyme-inhibitor structures was compiled for analysis, complexes with known binding energies (ΔG) based on the availability of experimentally determined inhibition constants (ki). Additionally, a separate set of over 1400 diverse high-resolution macromolecular crystal structures was collected for the purpose of creating an all-atom knowledgebased statistical potential, via application of the Delaunay tessellation computational geometry technique. Next, two hundred of the enzyme-inhibitor complexes were randomly selected to develop a model for predicting binding energy, first by tessellating structures of the complexes as well as the enzymes without their bound inhibitors, then by using the statistical potential to calculate a topological score for each structure tessellation. We derived as a predictor of binding energy an empirical linear function of the difference between topological scores for a complex and its isolated enzyme. A correlation coefficient (r) of 0.79 was obtained for the experimental and calculated ΔG values, with a standard error of 2.34 kcal/mol. Lastly, the model was evaluated with the heldout set of one hundred complexes, for which structure tessellations were performed in order to calculate topological score differences, and binding energy predictions were generated from the derived linear function. Calculated binding energies for the test data also compared well with their experimental counterparts, displaying a correlation coefficient of r = 0.77 with a standard error of 2.50 kcal/mol.

关键词： A Multibody Atomic Enzyme-Inhibitor the heldout set

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A Scalable Architecture for Intrusion-Detection systems Based on a Broadband Network of Embedded Set-Top Boxes

A Scalable Architecture for Intrusion-Detection Systems Base...

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54th ieee International Midwest Symposium on Circuits and systems (MWSCAS)

作者： Neill, Richard Carloni, Luca P. Columbia Univ Dept Comp Sci New York NY 10027 USA

ISBN: (纸本)9781612848570

As the processing power of set-top box (STB) devices continnes to grow with each new product generation and multiple service operators directly manage millions of these devices through a dedicated broadband network, we propose to harness this massive aggregate computational power to execute large-scale parallel applications. We present a prototype implementation of a heterogeneous distributed embedded system that combines a complete head-end cable system with a DOCSIS broadband network of STBs and an interoperable embedded implementation of Open MPI running on the STB operating system. We demonstrate the operations and performance of this system by reporting the experimental results that we obtained for the execution of various instances of Multiple Sequence Alignment, a parallel bioinformatics application. Based on these results we propose a new distributed embedded system architecture for highly-scalable intrusion-detection systems.

关键词： Broadband communication DOCSIS broadband network Frequency modulation Linux Radio frequency Servers Transform coding bioinformatics bioinformatics application computer networks dedicated broadband network embedded set-top boxes embedded systems head end cable system heterogeneous distributed embedded system intrusion detection systems large scale parallel applications massive aggregate computational power multiple sequence alignment scalable architecture security of data set-top boxes

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Unifying the Integration, Analysis and Interpretation of multi-omic datasets: Exploration of the disease networks of Obstructive Nephropathy in children

Unifying the Integration, Analysis and Interpretation of mul...

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33rd Annual International conference of the ieee Engineering-in-Medicine-and-Biology-Society (EMBS)

作者： Moulos, Panagiotis Valavanis, Ioannis Klein, Julie Maglogiannis, Ilias Schanstra, Joost Chatziioannou, Aristotelis Natl Hellen Res Fdn Inst Biol Res & Biotechnol Athens Greece

ISBN: (纸本)9781424441228

The wealth of data amassed by the utilization of various high-throughput techniques, in various layers of molecular dissection, stresses the critical role of the unification of the computational methodologies applied in biological data handling, storage, analysis and visualization. In this article, a generic workflow is showcased in a multi-omic dataset that is used to study Obstructive Nephropathy (ON) in children, integrating microarray data from several biological layers (transcriptomic, post-transcriptomic, proteomic). The workflow exploits raw measurements and through several analytical stages (preprocessing, statistical and functional), which entail various parsing steps, reaches the visualization stage of the heterogeneous, broader, molecular interacting network derived. This network, where the interconnected entities are exploiting the knowledge stored in public repositories, represents a systems level interpretation of the pathological state probed.

关键词： bioinformatics Data visualization Genomics Mice Proteins Proteomics bioinformatics biological data analysis biological data handling biological data storage biological data visualization biological techniques biomedical engineering complex networks comput

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Evolutionary sequence divergence predicts protein sub-cellular localization signals

Evolutionary sequence divergence predicts protein sub-cellul...

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5th ieee International conference on systems Biology, ISB 2011

作者： Fukasawa, Yoshinori Leung, Ross K.K. Tsui, Stephen K.W. Horton, Paul Department of Computational Biology Graduate School of Frontier Sciences University of Tokyo Kashiwa Japan Hong Kong Bioinformatics Centre School of Biomedical Sciences Chinese University of Hong Kong Shatin Hong Kong Computational Biology Research Center Advanced Industrial Science and Technology Tokyo Japan

ISBN: (纸本)9781457716669

Protein sub-cellular localization is a central problem in understanding cell biology and has been the focus of intense research. In order to predict localization from amino acid sequence a myriad of features have been tried: including amino acid composition, sequence similarity, the presence of certain motifs or domains, and many others. Surprisingly, sequence conservation of sorting motifs has not yet been employed, despite its extensive use for tasks such as the prediction of transcription factor binding sites. Here, we flip the problem around, and present a proof of concept for the idea that the lack of sequence conservation can be a useful feature for localization prediction. © 2011 ieee.

关键词： Proteins

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Uncover cooperative gene regulations by microRNAs and transcription factors in glioblastoma using a nonnegative hybrid factor model

Uncover cooperative gene regulations by microRNAs and transc...

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ieee International conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Meng, Jia Chen, Hung-, I Zhang, Jianqiu Chen, Yidong Huang, Yufei Univ Texas San Antonio Dept Elect & Comp Engn San Antonio TX 78249 USA

ISBN: (纸本)9781457705397

Transcriptional regulation by transcription factors (TFs) and microRNAs controls when and how much RNA is created. Due to technical limitations, the protein level expressions of TFs are usually unknown, making computational reconstruction of transcriptional network a difficult task. We proposed here a novel Bayesian nonnegative hybrid factor model for transcriptional network modeling, which is capable to estimate both the non-negative abundances of the transcription factors, the regulatory effects of TFs and microRNAs, and the sample clustering information by integrating microarray data and existing knowledge regarding TFs and microRNAs regulated target genes. The results demonstrated its validity and effectiveness to reconstructing transcriptional networks through simulated systems and real data.

关键词： bioinformatics Biological system modeling Data models Genomics Load modeling Loading Sparse matrices

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