The Experts below are selected from a list of 159 Experts worldwide ranked by ideXlab platform
Min Chen - One of the best experts on this subject based on the ideXlab platform.
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Anytime QoS-aware service composition over the GraphPlan
Service Oriented Computing and Applications, 2015Co-Authors: Yuhong Yan, Min ChenAbstract:Automatic service composition is the generation of a business process to fulfill business goals that cannot be fulfilled by individual services. Planning Algorithms are frequently used to solve this problem. In addition to satisfying functional goals, recent reSearch is geared toward selecting the best services to optimize the QoS of the result business process. Without considering QoS, the planning Algorithm normally Searches for the shortest plan, which actually implies the unit execution time for each service. With QoS, a longer plan may have better QoS values and thus is preferred over a shorter one. In this paper, we are motivated to combine a Systematic Search Algorithm like Dijkstra’s Algorithm with a planning Algorithm, GraphPlan, to achieve both functional goals and QoS optimization at the same time. The planning graph generated by GraphPlan is a compact representation of all execution paths, which makes it feasible to apply Dijkstra’s principle. In our new QoSGraphPlan Algorithm, we extend Dijkstra’s Algorithm from working on a single-source graph to working on the planning graph whose nodes have multiple sources. Using our method, we can get the best QoS value for throughput and response time in polynomial time when they are the single criteria. For the other QoS criteria, such as execution time, reputation, successful execution rate, and availability, our Algorithm is exponential for both single criterion problem and multiple criteria problem. In this case, we extend QoSGraphPlan with beam Search to solve the combination explosion problem. As our Algorithms Search for an optimal solution during the process of constructing the planning graph, they belong to the category of anytime Algorithms that return better solutions if they keep running for a longer time.
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QoS-aware Service Composition and Redundant Service Removal
2015Co-Authors: Min ChenAbstract:Automatic Service Composition (ASC) is the generation of a business process to fulfill business goals that cannot be fulfilled by individual services. Planning Algorithms are frequently used to solve this problem. In addition to satisfying functional goals, recent reSearch is geared towards selecting the best services to optimize the QoS of the business process results. It is a challenge to fulfill functional goals and achieve QoS optimization at the same time. In this thesis, we propose to combine a planning Algorithm called GraphPlan, with a Systematic Search Algorithm like Dijkstra's Algorithm to achieve functional goals and QoS optimization at the same time. The GraphPlan Algorithm has the advantages of easily modeling business logic, reusing the actions in one plan, and planning parallel actions in a plan. The planning graph generated by the GraphPlan Algorithm is a compact representation of all execution paths, which makes it feasible to apply Dijkstra's principle. Two methods have been proposed to combine the Graphplan with Dijkstra's Algorithm. In the first method, we extend Dijkstra's Algorithm from working on a single source graph to working on the extended planning graph whose nodes have multiple sources. The advantage of this method is that it gets an optimal plan with the best QoS value for the single criteria of throughput or response time in polynomial time. However, this method does not provide a uniform graph structure (\ie an extended planning graph with single or multiple tag, to generate an optimal plan for all kinds of quality criteria). In the second method, we improve the idea of combining the Graphplan with Dijkstra's Algorithm by providing a uniform graph structure to generate a QoS optimal solution for all kinds of quality criteria. A Layered Weighted Graph (LWG) is generated and provides a uniform structure for the easy use of Dijkstra's Algorithm to find an optimal plan for all kinds of quality criteria. By using multi-objective shortest path Algorithms, this method can be easily extended to solve QoS optimization on multiple QoS criterion for service composition problem. In this thesis, we also study redundant service removal to further optimize QoS optimal solutions. The removal of redundant services does not worsen the QoS value of the optimal solution. Fewer numbers of services indicates less execution costs to invoke these services. A redundant service removal problem is modeled as an optimization problem such that the optimal solution without redundancy is found.
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SAC - Anytime QoS optimization over the PlanGraph for web service composition
Proceedings of the 27th Annual ACM Symposium on Applied Computing - SAC '12, 2012Co-Authors: Yuhong Yan, Min Chen, Yu-bin YangAbstract:Automatic service composition is the generation of a business process to fulfill business goals that cannot be fulfilled by individual services. Planning Algorithms are frequently used to solve this problem. In addition to satisfying functional goals, recent reSearch is geared towards selecting the best services to optimize the QoS of the result business process. In this paper, we combine a Systematic Search Algorithm like Dijkstra's Algorithm with a planning Algorithm, GraphPlan, to achieve both functional goals and QoS optimization at the same time. In addition, we make our Algorithm an anytime Algorithm that has the advantage of getting better solutions if it keeps running for a longer time.
Mark C. Hersam - One of the best experts on this subject based on the ideXlab platform.
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Nanotubes sorted using DNA
Nature, 2009Co-Authors: Mark C. HersamAbstract:A vast number of DNA sequences are possible, and so finding the few that bind to a particular non-DNA entity is a daunting task. A Systematic Search Algorithm has found sequences that target specific carbon nanotubes. The methods so far developed for the production of carbon nanotubes generate mixtures of metallic and semiconducting tubes, with differing diameters and chiralities. For nanotubes to be of practical use, in electronics for example, it is important to be able to purify single species so that their properties can be properly determined. It is proving very difficult to disentangle these mixtures but a team working at DuPont's Wilmington reSearch labs and at Lehigh University in Bethlehem, Pennsylvania, has recruited DNA to the cause with promising results. They find that specially tailored DNA sequences, consisting of repeats of one purine plus one or more subsequent pyrimidines, can purify every single species in a nanotube mixture. Through theory they also show that these DNA sequences form particularly stable three-dimensional barrel structures when wrapped around a nanotube, which could be responsible for the selectivity.
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Materials science: Nanotubes sorted using DNA
Nature, 2009Co-Authors: Mark C. HersamAbstract:A vast number of DNA sequences are possible, and so finding the few that bind to a particular non-DNA entity is a daunting task. A Systematic Search Algorithm has found sequences that target specific carbon nanotubes.
Yuhong Yan - One of the best experts on this subject based on the ideXlab platform.
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Anytime QoS-aware service composition over the GraphPlan
Service Oriented Computing and Applications, 2015Co-Authors: Yuhong Yan, Min ChenAbstract:Automatic service composition is the generation of a business process to fulfill business goals that cannot be fulfilled by individual services. Planning Algorithms are frequently used to solve this problem. In addition to satisfying functional goals, recent reSearch is geared toward selecting the best services to optimize the QoS of the result business process. Without considering QoS, the planning Algorithm normally Searches for the shortest plan, which actually implies the unit execution time for each service. With QoS, a longer plan may have better QoS values and thus is preferred over a shorter one. In this paper, we are motivated to combine a Systematic Search Algorithm like Dijkstra’s Algorithm with a planning Algorithm, GraphPlan, to achieve both functional goals and QoS optimization at the same time. The planning graph generated by GraphPlan is a compact representation of all execution paths, which makes it feasible to apply Dijkstra’s principle. In our new QoSGraphPlan Algorithm, we extend Dijkstra’s Algorithm from working on a single-source graph to working on the planning graph whose nodes have multiple sources. Using our method, we can get the best QoS value for throughput and response time in polynomial time when they are the single criteria. For the other QoS criteria, such as execution time, reputation, successful execution rate, and availability, our Algorithm is exponential for both single criterion problem and multiple criteria problem. In this case, we extend QoSGraphPlan with beam Search to solve the combination explosion problem. As our Algorithms Search for an optimal solution during the process of constructing the planning graph, they belong to the category of anytime Algorithms that return better solutions if they keep running for a longer time.
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SAC - Anytime QoS optimization over the PlanGraph for web service composition
Proceedings of the 27th Annual ACM Symposium on Applied Computing - SAC '12, 2012Co-Authors: Yuhong Yan, Min Chen, Yu-bin YangAbstract:Automatic service composition is the generation of a business process to fulfill business goals that cannot be fulfilled by individual services. Planning Algorithms are frequently used to solve this problem. In addition to satisfying functional goals, recent reSearch is geared towards selecting the best services to optimize the QoS of the result business process. In this paper, we combine a Systematic Search Algorithm like Dijkstra's Algorithm with a planning Algorithm, GraphPlan, to achieve both functional goals and QoS optimization at the same time. In addition, we make our Algorithm an anytime Algorithm that has the advantage of getting better solutions if it keeps running for a longer time.
Lincong Wang - One of the best experts on this subject based on the ideXlab platform.
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A data-driven, Systematic Search Algorithm for structure determination of denatured or disordered proteins.
Computational systems bioinformatics. Computational Systems Bioinformatics Conference, 2006Co-Authors: Lincong Wang, Bruce R. DonaldAbstract:Traditional Algorithms for the structure determination of native proteins by solution nuclear magnetic resonance (NMR) spectroscopy require a large number of experimental restraints. These Algorithms formulate the structure determination problem as the computation of a structure or a set of similar structures that best fit the restraints. However, for both laboratory-denatured and natively-disordered proteins, the number of restraints measured by the current NMR techniques is well below that required by traditional Algorithms. Furthermore, there presumably exists a heterogeneous set of structures in either the denatured or disordered state. We present a data-driven Algorithm capable of computing a set of structures (ensemble) directly from sparse experimental restraints. For both denatured and disordered proteins, we formulate the structure determination problem as the computation of an ensemble of structures from the restraints. In this formulation, each experimental restraint is a distribution. Compared with previous Algorithms, our Algorithm can extract more structural information from the experimental data. In our Algorithm, all the backbone conformations consistent with the data are computed by solving a series of low-degree monomials (yielding exact solutions in closed form) and Systematic Search with pruning. The Algorithm has been successfully applied to determine the structural ensembles of two denatured proteins, acyl-coenzyme A binding protein (ACBP) and eglin C, using real experimental NMR data.
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Exact Solutions for Internuclear Vectors and Backbone Dihedral Angles from NH Residual Dipolar Couplings in Two Media, and their Application in a Systematic Search Algorithm for Determining Protein Backbone Structure
Journal of Biomolecular NMR, 2004Co-Authors: Lincong Wang, Bruce Randall DonaldAbstract:We have derived a quartic equation for computing the direction of an internuclear vector from residual dipolar couplings (RDCs) measured in two aligning media, and two simple trigonometric equations for computing the backbone (φ,ψ) angles from two backbone vectors in consecutive peptide planes. These equations make it possible to compute, exactly and in constant time , the backbone (φ,ψ) angles for a residue from RDCs in two media on any single backbone vector type. Building upon these exact solutions we have designed a novel Algorithm for determining a protein backbone substructure consisting of α-helices and β-sheets. Our Algorithm employs a Systematic Search technique to refine the conformation of both α-helices and β-sheets and to determine their orientations using exclusively the angular restraints from RDCs. The Algorithm computes the backbone substructure employing very sparse distance restraints between pairs of α-helices and β-sheets refined by the Systematic Search. The Algorithm has been demonstrated on the protein human ubiquitin using only backbone NH RDCs, plus twelve hydrogen bonds and four NOE distance restraints. Further, our results show that both the global orientations and the conformations of α-helices and β-strands can be determined with high accuracy using only two RDCs per residue. The Algorithm requires, as its input, backbone resonance assignments, the identification of α-helices and β-sheets as well as sparse NOE distance and hydrogen bond restraints. Abbreviations: NMR – nuclear magnetic resonance; RDC – residual dipolar coupling; NOE – nuclear Overhauser effect; SVD – singular value decomposition; DFS – depth-first Search; RMSD – root mean square deviation; POF – principal order frame; PDB – protein data bank; SA – simulated annealing; MD – molecular dynamics.
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Exact solutions for internuclear vectors and backbone dihedral angles from NH residual dipolar couplings in two media, and their application in a Systematic Search Algorithm for determining protein backbone structure.
Journal of biomolecular NMR, 2004Co-Authors: Lincong Wang, Bruce R. DonaldAbstract:We have derived a quartic equation for computing the direction of an internuclear vector from residual dipolar couplings (RDCs) measured in two aligning media, and two simple trigonometric equations for computing the backbone (φ,ψ) angles from two backbone vectors in consecutive peptide planes. These equations make it possible to compute, exactly and in constant time, the backbone (φ,ψ) angles for a residue from RDCs in two media on any single backbone vector type. Building upon these exact solutions we have designed a novel Algorithm for determining a protein backbone substructure consisting of α-helices and β-sheets. Our Algorithm employs a Systematic Search technique to refine the conformation of both α-helices and β-sheets and to determine their orientations using exclusively the angular restraints from RDCs. The Algorithm computes the backbone substructure employing very sparse distance restraints between pairs of α-helices and β-sheets refined by the Systematic Search. The Algorithm has been demonstrated on the protein human ubiquitin using only backbone NH RDCs, plus twelve hydrogen bonds and four NOE distance restraints. Further, our results show that both the global orientations and the conformations of α-helices and β-strands can be determined with high accuracy using only two RDCs per residue. The Algorithm requires, as its input, backbone resonance assignments, the identification of α-helices and β-sheets as well as sparse NOE distance and hydrogen bond restraints.
Bruce R. Donald - One of the best experts on this subject based on the ideXlab platform.
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A data-driven, Systematic Search Algorithm for structure determination of denatured or disordered proteins.
Computational systems bioinformatics. Computational Systems Bioinformatics Conference, 2006Co-Authors: Lincong Wang, Bruce R. DonaldAbstract:Traditional Algorithms for the structure determination of native proteins by solution nuclear magnetic resonance (NMR) spectroscopy require a large number of experimental restraints. These Algorithms formulate the structure determination problem as the computation of a structure or a set of similar structures that best fit the restraints. However, for both laboratory-denatured and natively-disordered proteins, the number of restraints measured by the current NMR techniques is well below that required by traditional Algorithms. Furthermore, there presumably exists a heterogeneous set of structures in either the denatured or disordered state. We present a data-driven Algorithm capable of computing a set of structures (ensemble) directly from sparse experimental restraints. For both denatured and disordered proteins, we formulate the structure determination problem as the computation of an ensemble of structures from the restraints. In this formulation, each experimental restraint is a distribution. Compared with previous Algorithms, our Algorithm can extract more structural information from the experimental data. In our Algorithm, all the backbone conformations consistent with the data are computed by solving a series of low-degree monomials (yielding exact solutions in closed form) and Systematic Search with pruning. The Algorithm has been successfully applied to determine the structural ensembles of two denatured proteins, acyl-coenzyme A binding protein (ACBP) and eglin C, using real experimental NMR data.
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Exact solutions for internuclear vectors and backbone dihedral angles from NH residual dipolar couplings in two media, and their application in a Systematic Search Algorithm for determining protein backbone structure.
Journal of biomolecular NMR, 2004Co-Authors: Lincong Wang, Bruce R. DonaldAbstract:We have derived a quartic equation for computing the direction of an internuclear vector from residual dipolar couplings (RDCs) measured in two aligning media, and two simple trigonometric equations for computing the backbone (φ,ψ) angles from two backbone vectors in consecutive peptide planes. These equations make it possible to compute, exactly and in constant time, the backbone (φ,ψ) angles for a residue from RDCs in two media on any single backbone vector type. Building upon these exact solutions we have designed a novel Algorithm for determining a protein backbone substructure consisting of α-helices and β-sheets. Our Algorithm employs a Systematic Search technique to refine the conformation of both α-helices and β-sheets and to determine their orientations using exclusively the angular restraints from RDCs. The Algorithm computes the backbone substructure employing very sparse distance restraints between pairs of α-helices and β-sheets refined by the Systematic Search. The Algorithm has been demonstrated on the protein human ubiquitin using only backbone NH RDCs, plus twelve hydrogen bonds and four NOE distance restraints. Further, our results show that both the global orientations and the conformations of α-helices and β-strands can be determined with high accuracy using only two RDCs per residue. The Algorithm requires, as its input, backbone resonance assignments, the identification of α-helices and β-sheets as well as sparse NOE distance and hydrogen bond restraints.
