The Experts below are selected from a list of 60522 Experts worldwide ranked by ideXlab platform
Guangzhou Zeng - One of the best experts on this subject based on the ideXlab platform.
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goals description and application in migrating Workflow System
Expert Systems With Applications, 2010Co-Authors: Guangzhou ZengAbstract:Goals, which can be described as states that an agent would like to realize, is an important concept for intelligent agent Systems. The representation of goals and the ability to reason about them are the major problems in goal-oriented analysis and modeling techniques, especially in intelligent agent System, as goals are more stable than other abstractions (e.g. user stories). Description Logics (DLs) is a formal tool of knowledge representation and reasoning. In this paper, we construct a framework with explicit representation and formal semantics of goals-Goal Description Logics (GDLs), which integrates two aspects of goals: declarative (a description of the state of sought), and procedural (a set of plans for achieving the goal), into one concept based on Description Logics (DLs). In addition, goals reasoning, especially goal matchmaking in GDLs, is studied using its effective judgment to concept subsumption. We propose a conceptual model of goal-based migration Workflow System (GMWfS) based on GDLs, and illustrate an application. We also present preliminary experimental results on an implementation of these ideas. Compared to traditional Workflow methods, GOMWfS is more flexible and intelligent.
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study of initiative security mechanism for migrating instance in migrating Workflow System
International Workshop on Education Technology and Computer Science, 2010Co-Authors: Fangxi Han, Guangzhou Zeng, Qiuli SunAbstract:In migrating Workflow System, the migrating instance which behavior is similar to mobile agent is dispatched to execute task on the workplace, so the migrating instance faces the same security problem as the mobile agent. However, most of the present protecting mobile agent security methods are in passive ways. In this paper, we propose a model with the danger detection algorithm to protect migrating instance from attacks initiatively based on the security proxy agent. While the migrating instance is executing on a workplace, it creates and dispatches a security proxy agent to the next workplace in order to evaluate if the next workplace is safe or not, and the migrating instance could evade the unsafe zone with the help of the evaluation result. We also give an example to demonstrate that our method provides a practical solution.
Ranganatha Shoba - One of the best experts on this subject based on the ideXlab platform.
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A practical, bioinformatic Workflow System for large datasets generated by next-generation sequencing
'Oxford University Press (OUP)', 2010Co-Authors: Cantacessi Cinzia, Jex, Aaron R., Hall, Ross S., Young, Neil D., Campbell, Bronwyn E., Joachim Anja, Nolan, Matthew J., Abubucker Sahar, Sternberg, Paul W., Ranganatha ShobaAbstract:Transcriptomics (at the level of single cells, tissues and/or whole organisms) underpins many fields of biomedical science, from understanding the basic cellular function in model organisms, to the elucidation of the biological events that govern the development and progression of human diseases, and the exploration of the mechanisms of survival, drug-resistance and virulence of pathogens. Next-generation sequencing (NGS) technologies are contributing to a massive expansion of transcriptomics in all fields and are reducing the cost, time and performance barriers presented by conventional approaches. However, bioinformatic tools for the analysis of the sequence data sets produced by these technologies can be daunting to researchers with limited or no expertise in bioinformatics. Here, we constructed a semi-automated, bioinformatic Workflow System, and critically evaluated it for the analysis and annotation of large-scale sequence data sets generated by NGS. We demonstrated its utility for the exploration of differences in the transcriptomes among various stages and both sexes of an economically important parasitic worm (Oesophagostomum dentatum) as well as the prediction and prioritization of essential molecules (including GTPases, protein kinases and phosphatases) as novel drug target candidates. This Workflow System provides a practical tool for the assembly, annotation and analysis of NGS data sets, also to researchers with a limited bioinformatic expertise. The custom-written Perl, Python and Unix shell computer scripts used can be readily modified or adapted to suit many different applications. This System is now utilized routinely for the analysis of data sets from pathogens of major socio-economic importance and can, in principle, be applied to transcriptomics data sets from any organism
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A practical, bioinformatic Workflow System for large data sets generated by next-generation sequencing
Published online, 2010Co-Authors: Cantacessi Cinzia, Jex, Aaron R., Hall, Ross S., Young, Neil D., Campbell, Bronwyn E., Joachim Anja, Nolan, Matthew J., Abubucker Sahar, Sternberg, Paul W., Ranganatha ShobaAbstract:Transcriptomics (at the level of single cells, tissues and/or whole organisms) underpins many fields of biomedical science, from understanding the basic cellular function in model organisms, to the elucidation of the biological events that govern the development and progression of human diseases, and the exploration of the mechanisms of survival, drug-resistance and virulence of pathogens. Next-generation sequencing (NGS) technologies are contributing to a massive expansion of transcriptomics in all fields and are reducing the cost, time and performance barriers presented by con- ventional approaches. However, bioinformatic tools for the analysis of the sequence data sets produced by these technologies can be daunting to researchers with limited or no expertise in bio- informatics. Here, we constructed a semi- automated, bioinformatic Workflow System, and critically evaluated it for the analysis and annotation of large-scale sequence data sets generated by NGS. We demonstrated its utility for the exploration of differences in the transcriptomes among various stages and both sexes of an economically important parasitic worm (Oesophagostomum dentatum) as well as the prediction and prioritization of essential molecules (including GTPases, protein kinases and phosphatases) as novel drug target candidates. This Workflow System provides a practical tool for the assembly, annotation and analysis of NGS data expertise. The custom-written Perl, Python and Unix shell computer scripts used can be readily modified or adapted to suit many different applications. This System is now utilized routinely for the analysis of data sets from pathogens of major socio-economic importance and can, in principle, be applied to transcriptomics data sets from any organism
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A practical, bioinformatic Workflow System for large data sets generated by next-generation sequencing
'Oxford University Press (OUP)', 2010Co-Authors: Cantacessi Cinzia, Jex, Aaron R., Hall, Ross S., Young, Neil D., Campbell, Bronwyn E., Joachim Anja, Nolan, Matthew J., Abubucker Sahar, Sternberg, Paul W., Ranganatha ShobaAbstract:Transcriptomics (at the level of single cells, tissues and/or whole organisms) underpins many fields of biomedical science, from understanding the basic cellular function in model organisms, to the elucidation of the biological events that govern the development and progression of human diseases, and the exploration of the mechanisms of survival, drug-resistance and virulence of pathogens. Next-generation sequencing (NGS) technologies are contributing to a massive expansion of transcriptomics in all fields and are reducing the cost, time and performance barriers presented by conventional approaches. However, bioinformatic tools for the analysis of the sequence data sets produced by these technologies can be daunting to researchers with limited or no expertise in bioinformatics. Here, we constructed a semi-automated, bioinformatic Workflow System, and critically evaluated it for the analysis and annotation of large-scale sequence data sets generated by NGS. We demonstrated its utility for the exploration of differences in the transcriptomes among various stages and both sexes of an economically important parasitic worm (Oesophagostomum dentatum) as well as the prediction and prioritization of essential molecules (including GTPases, protein kinases and phosphatases) as novel drug target candidates. This Workflow System provides a practical tool for the assembly, annotation and analysis of NGS data sets, also to researchers with a limited bioinformatic expertise. The custom-written Perl, Python and Unix shell computer scripts used can be readily modified or adapted to suit many different applications. This System is now utilized routinely for the analysis of data sets from pathogens of major socio-economic importance and can, in principle, be applied to transcriptomics data sets from any organism
Cantacessi Cinzia - One of the best experts on this subject based on the ideXlab platform.
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A practical, bioinformatic Workflow System for large datasets generated by next-generation sequencing
'Oxford University Press (OUP)', 2010Co-Authors: Cantacessi Cinzia, Jex, Aaron R., Hall, Ross S., Young, Neil D., Campbell, Bronwyn E., Joachim Anja, Nolan, Matthew J., Abubucker Sahar, Sternberg, Paul W., Ranganatha ShobaAbstract:Transcriptomics (at the level of single cells, tissues and/or whole organisms) underpins many fields of biomedical science, from understanding the basic cellular function in model organisms, to the elucidation of the biological events that govern the development and progression of human diseases, and the exploration of the mechanisms of survival, drug-resistance and virulence of pathogens. Next-generation sequencing (NGS) technologies are contributing to a massive expansion of transcriptomics in all fields and are reducing the cost, time and performance barriers presented by conventional approaches. However, bioinformatic tools for the analysis of the sequence data sets produced by these technologies can be daunting to researchers with limited or no expertise in bioinformatics. Here, we constructed a semi-automated, bioinformatic Workflow System, and critically evaluated it for the analysis and annotation of large-scale sequence data sets generated by NGS. We demonstrated its utility for the exploration of differences in the transcriptomes among various stages and both sexes of an economically important parasitic worm (Oesophagostomum dentatum) as well as the prediction and prioritization of essential molecules (including GTPases, protein kinases and phosphatases) as novel drug target candidates. This Workflow System provides a practical tool for the assembly, annotation and analysis of NGS data sets, also to researchers with a limited bioinformatic expertise. The custom-written Perl, Python and Unix shell computer scripts used can be readily modified or adapted to suit many different applications. This System is now utilized routinely for the analysis of data sets from pathogens of major socio-economic importance and can, in principle, be applied to transcriptomics data sets from any organism
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A practical, bioinformatic Workflow System for large data sets generated by next-generation sequencing
Published online, 2010Co-Authors: Cantacessi Cinzia, Jex, Aaron R., Hall, Ross S., Young, Neil D., Campbell, Bronwyn E., Joachim Anja, Nolan, Matthew J., Abubucker Sahar, Sternberg, Paul W., Ranganatha ShobaAbstract:Transcriptomics (at the level of single cells, tissues and/or whole organisms) underpins many fields of biomedical science, from understanding the basic cellular function in model organisms, to the elucidation of the biological events that govern the development and progression of human diseases, and the exploration of the mechanisms of survival, drug-resistance and virulence of pathogens. Next-generation sequencing (NGS) technologies are contributing to a massive expansion of transcriptomics in all fields and are reducing the cost, time and performance barriers presented by con- ventional approaches. However, bioinformatic tools for the analysis of the sequence data sets produced by these technologies can be daunting to researchers with limited or no expertise in bio- informatics. Here, we constructed a semi- automated, bioinformatic Workflow System, and critically evaluated it for the analysis and annotation of large-scale sequence data sets generated by NGS. We demonstrated its utility for the exploration of differences in the transcriptomes among various stages and both sexes of an economically important parasitic worm (Oesophagostomum dentatum) as well as the prediction and prioritization of essential molecules (including GTPases, protein kinases and phosphatases) as novel drug target candidates. This Workflow System provides a practical tool for the assembly, annotation and analysis of NGS data expertise. The custom-written Perl, Python and Unix shell computer scripts used can be readily modified or adapted to suit many different applications. This System is now utilized routinely for the analysis of data sets from pathogens of major socio-economic importance and can, in principle, be applied to transcriptomics data sets from any organism
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A practical, bioinformatic Workflow System for large data sets generated by next-generation sequencing
'Oxford University Press (OUP)', 2010Co-Authors: Cantacessi Cinzia, Jex, Aaron R., Hall, Ross S., Young, Neil D., Campbell, Bronwyn E., Joachim Anja, Nolan, Matthew J., Abubucker Sahar, Sternberg, Paul W., Ranganatha ShobaAbstract:Transcriptomics (at the level of single cells, tissues and/or whole organisms) underpins many fields of biomedical science, from understanding the basic cellular function in model organisms, to the elucidation of the biological events that govern the development and progression of human diseases, and the exploration of the mechanisms of survival, drug-resistance and virulence of pathogens. Next-generation sequencing (NGS) technologies are contributing to a massive expansion of transcriptomics in all fields and are reducing the cost, time and performance barriers presented by conventional approaches. However, bioinformatic tools for the analysis of the sequence data sets produced by these technologies can be daunting to researchers with limited or no expertise in bioinformatics. Here, we constructed a semi-automated, bioinformatic Workflow System, and critically evaluated it for the analysis and annotation of large-scale sequence data sets generated by NGS. We demonstrated its utility for the exploration of differences in the transcriptomes among various stages and both sexes of an economically important parasitic worm (Oesophagostomum dentatum) as well as the prediction and prioritization of essential molecules (including GTPases, protein kinases and phosphatases) as novel drug target candidates. This Workflow System provides a practical tool for the assembly, annotation and analysis of NGS data sets, also to researchers with a limited bioinformatic expertise. The custom-written Perl, Python and Unix shell computer scripts used can be readily modified or adapted to suit many different applications. This System is now utilized routinely for the analysis of data sets from pathogens of major socio-economic importance and can, in principle, be applied to transcriptomics data sets from any organism
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A practical, bioinformatic Workflow System for large data sets generated by next-generation sequencing
'Oxford University Press (OUP)', 2010Co-Authors: Cantacessi Cinzia, Hall, Ross S., Young, Neil D., Campbell, Bronwyn E., Joachim Anja, Nolan, Matthew J., Jex Aaron, Mitreva Makedonka, Gasser, Robin B, Abubucker SaharAbstract:Transcriptomics (at the level of single cells, tissues and/or whole organisms) underpins many fields of biomedical science, from understanding the basic cellular function in model organisms, to the elucidation of the biological events that govern the development and progression of human diseases, and the exploration of the mechanisms of survival, drug-resistance and virulence of pathogens. Next-generation sequencing (NGS) technologies are contributing to a massive expansion of transcriptomics in all fields and are reducing the cost, time and performance barriers presented by conventional approaches. However, bioinformatic tools for the analysis of the sequence data sets produced by these technologies can be daunting to researchers with limited or no expertise in bioinformatics. Here, we constructed a semi-automated, bioinformatic Workflow System, and critically evaluated it for the analysis and annotation of large-scale sequence data sets generated by NGS. We demonstrated its utility for the exploration of differences in the transcriptomes among various stages and both sexes of an economically important parasitic worm (Oesophagostomum dentatum) as well as the prediction and prioritization of essential molecules (including GTPases, protein kinases and phosphatases) as novel drug target candidates. This Workflow System provides a practical tool for the assembly, annotation and analysis of NGS data sets, also to researchers with a limited bioinformatic expertise. The custom-written Perl, Python and Unix shell computer scripts used can be readily modified or adapted to suit many different applications. This System is now utilized routinely for the analysis of data sets from pathogens of major socio-economic importance and can, in principle, be applied to transcriptomics data sets from any organism.12 page(s
Abubucker Sahar - One of the best experts on this subject based on the ideXlab platform.
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A practical, bioinformatic Workflow System for large datasets generated by next-generation sequencing
'Oxford University Press (OUP)', 2010Co-Authors: Cantacessi Cinzia, Jex, Aaron R., Hall, Ross S., Young, Neil D., Campbell, Bronwyn E., Joachim Anja, Nolan, Matthew J., Abubucker Sahar, Sternberg, Paul W., Ranganatha ShobaAbstract:Transcriptomics (at the level of single cells, tissues and/or whole organisms) underpins many fields of biomedical science, from understanding the basic cellular function in model organisms, to the elucidation of the biological events that govern the development and progression of human diseases, and the exploration of the mechanisms of survival, drug-resistance and virulence of pathogens. Next-generation sequencing (NGS) technologies are contributing to a massive expansion of transcriptomics in all fields and are reducing the cost, time and performance barriers presented by conventional approaches. However, bioinformatic tools for the analysis of the sequence data sets produced by these technologies can be daunting to researchers with limited or no expertise in bioinformatics. Here, we constructed a semi-automated, bioinformatic Workflow System, and critically evaluated it for the analysis and annotation of large-scale sequence data sets generated by NGS. We demonstrated its utility for the exploration of differences in the transcriptomes among various stages and both sexes of an economically important parasitic worm (Oesophagostomum dentatum) as well as the prediction and prioritization of essential molecules (including GTPases, protein kinases and phosphatases) as novel drug target candidates. This Workflow System provides a practical tool for the assembly, annotation and analysis of NGS data sets, also to researchers with a limited bioinformatic expertise. The custom-written Perl, Python and Unix shell computer scripts used can be readily modified or adapted to suit many different applications. This System is now utilized routinely for the analysis of data sets from pathogens of major socio-economic importance and can, in principle, be applied to transcriptomics data sets from any organism
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A practical, bioinformatic Workflow System for large data sets generated by next-generation sequencing
Published online, 2010Co-Authors: Cantacessi Cinzia, Jex, Aaron R., Hall, Ross S., Young, Neil D., Campbell, Bronwyn E., Joachim Anja, Nolan, Matthew J., Abubucker Sahar, Sternberg, Paul W., Ranganatha ShobaAbstract:Transcriptomics (at the level of single cells, tissues and/or whole organisms) underpins many fields of biomedical science, from understanding the basic cellular function in model organisms, to the elucidation of the biological events that govern the development and progression of human diseases, and the exploration of the mechanisms of survival, drug-resistance and virulence of pathogens. Next-generation sequencing (NGS) technologies are contributing to a massive expansion of transcriptomics in all fields and are reducing the cost, time and performance barriers presented by con- ventional approaches. However, bioinformatic tools for the analysis of the sequence data sets produced by these technologies can be daunting to researchers with limited or no expertise in bio- informatics. Here, we constructed a semi- automated, bioinformatic Workflow System, and critically evaluated it for the analysis and annotation of large-scale sequence data sets generated by NGS. We demonstrated its utility for the exploration of differences in the transcriptomes among various stages and both sexes of an economically important parasitic worm (Oesophagostomum dentatum) as well as the prediction and prioritization of essential molecules (including GTPases, protein kinases and phosphatases) as novel drug target candidates. This Workflow System provides a practical tool for the assembly, annotation and analysis of NGS data expertise. The custom-written Perl, Python and Unix shell computer scripts used can be readily modified or adapted to suit many different applications. This System is now utilized routinely for the analysis of data sets from pathogens of major socio-economic importance and can, in principle, be applied to transcriptomics data sets from any organism
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A practical, bioinformatic Workflow System for large data sets generated by next-generation sequencing
'Oxford University Press (OUP)', 2010Co-Authors: Cantacessi Cinzia, Jex, Aaron R., Hall, Ross S., Young, Neil D., Campbell, Bronwyn E., Joachim Anja, Nolan, Matthew J., Abubucker Sahar, Sternberg, Paul W., Ranganatha ShobaAbstract:Transcriptomics (at the level of single cells, tissues and/or whole organisms) underpins many fields of biomedical science, from understanding the basic cellular function in model organisms, to the elucidation of the biological events that govern the development and progression of human diseases, and the exploration of the mechanisms of survival, drug-resistance and virulence of pathogens. Next-generation sequencing (NGS) technologies are contributing to a massive expansion of transcriptomics in all fields and are reducing the cost, time and performance barriers presented by conventional approaches. However, bioinformatic tools for the analysis of the sequence data sets produced by these technologies can be daunting to researchers with limited or no expertise in bioinformatics. Here, we constructed a semi-automated, bioinformatic Workflow System, and critically evaluated it for the analysis and annotation of large-scale sequence data sets generated by NGS. We demonstrated its utility for the exploration of differences in the transcriptomes among various stages and both sexes of an economically important parasitic worm (Oesophagostomum dentatum) as well as the prediction and prioritization of essential molecules (including GTPases, protein kinases and phosphatases) as novel drug target candidates. This Workflow System provides a practical tool for the assembly, annotation and analysis of NGS data sets, also to researchers with a limited bioinformatic expertise. The custom-written Perl, Python and Unix shell computer scripts used can be readily modified or adapted to suit many different applications. This System is now utilized routinely for the analysis of data sets from pathogens of major socio-economic importance and can, in principle, be applied to transcriptomics data sets from any organism
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A practical, bioinformatic Workflow System for large data sets generated by next-generation sequencing
'Oxford University Press (OUP)', 2010Co-Authors: Cantacessi Cinzia, Hall, Ross S., Young, Neil D., Campbell, Bronwyn E., Joachim Anja, Nolan, Matthew J., Jex Aaron, Mitreva Makedonka, Gasser, Robin B, Abubucker SaharAbstract:Transcriptomics (at the level of single cells, tissues and/or whole organisms) underpins many fields of biomedical science, from understanding the basic cellular function in model organisms, to the elucidation of the biological events that govern the development and progression of human diseases, and the exploration of the mechanisms of survival, drug-resistance and virulence of pathogens. Next-generation sequencing (NGS) technologies are contributing to a massive expansion of transcriptomics in all fields and are reducing the cost, time and performance barriers presented by conventional approaches. However, bioinformatic tools for the analysis of the sequence data sets produced by these technologies can be daunting to researchers with limited or no expertise in bioinformatics. Here, we constructed a semi-automated, bioinformatic Workflow System, and critically evaluated it for the analysis and annotation of large-scale sequence data sets generated by NGS. We demonstrated its utility for the exploration of differences in the transcriptomes among various stages and both sexes of an economically important parasitic worm (Oesophagostomum dentatum) as well as the prediction and prioritization of essential molecules (including GTPases, protein kinases and phosphatases) as novel drug target candidates. This Workflow System provides a practical tool for the assembly, annotation and analysis of NGS data sets, also to researchers with a limited bioinformatic expertise. The custom-written Perl, Python and Unix shell computer scripts used can be readily modified or adapted to suit many different applications. This System is now utilized routinely for the analysis of data sets from pathogens of major socio-economic importance and can, in principle, be applied to transcriptomics data sets from any organism.12 page(s
Lican Huang - One of the best experts on this subject based on the ideXlab platform.
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enhancement of Workflow flexibility by composing activities at run time
ACM Symposium on Applied Computing, 2004Co-Authors: Shuiguang Deng, Lican HuangAbstract:Flexibility has recently grown to be one of the major research topics in the area of Workflow management. A Workflow System that supports flexible processes will benefit organizations more. In this paper, we present a Workflow model offering flexibility by enabling activities to be composed automatically or manually at run-time. Our model uses selection constraints and composition constraints to guide end users to build valid Workflow specifications. As an application of this model, we outline the architecture of our multi-agent based Workflow management System, of which model agents play the role to complete Workflow specifications according to run-time information of instances. We put forward an important algorithm related to the model agent, which is to compose activities into a valid subprocess with the shortest critical path.
