35 research outputs found
Proceedings of the 1998 annual ACM SIGAda international conference on Ada [electronic resource].
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Proceedings of the third ACM international conference on Multimedia [electronic resource].
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Proceedings of the second ACM international conference on Multimedia [electronic resource].
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Accurate Compton Profiles For H2 And D2 Including The Effects Of Electron Correlation And Molecular Vibration And Rotation
No full textAccurate isotropic Compton profiles J(q,R) for H2(X 1∑g +) are calculated for 22 internuclear separations from the 126 configuration wavefunctions of Liu. These profiles, supplemented by the united atom and separated atom profiles, are then rigorously averaged over vibration-rotation wavefunctions computed by direct numerical solution of the radial Schrödinger equation using nearly exact potential energy curves including adiabatic and relativistic corrections. These averages are performed for a large number of vibration-rotation states of H2 and the ground vibration-rotation state of D2. It is shown that the effects of averaging Compton profiles over vibration-rotation states are significant and cannot be neglected. The isotope effect is shown to be smaller than the vibration-rotation effect. The peak of the calculated H2 Compton profile for the ground vibration-rotation state is found to be in excellent agreement with the very recent high energy electron impact measurements of Lee. A number of expansion techniques for vibration-rotation averaging, including a new, very simple, and reasonably accurate delta approximation, are presented. Copyright © 1977 American Institute of Physics.67836763682 ACM Special Interest Group on Biomedical Computing (SIGBIO) ACM Special Interest Group on Biomedical Computing (SIGBIO
Approximation Algorithms For Sorting By Signed Short Reversals
No full textDuring evolution, global mutations may modify the gene order in a genome. Such mutations are commonly referred to as rearrangement events. One of the most frequent rearrangement events observed in genomes are reversals, which are responsible for reversing the order and orientation of a sequence of genes. The problem of sorting by reversals, that is, the problem of computing the most parsimonious reversal scenario to transform one genome into another, is a well-studied problem that finds application in comparative genomics. There is a number of works concerning this problem in the literature, but these works generally do not take into account the length of the reversals. Since it has been observed that short reversals are prevalent in the evolution of some species, recent efforts have been made to address this issue algorithmically. In this paper, we add to these efforts by introducing the problem of sorting by signed short reversals and by presenting three approximation algorithms for solving it. Although the worst-case approximation ratios of these algorithms are high, we show that their expected approximation ratios for sorting a random equiprobable signed permutation are much lower. Moreover, we present experimental results on small signed permutations which indicate that the worst-case approximation ratios of these algorithms may be better than those we have been able to prove.360369 ACM Special Interest Group on Biomedical Computing (SIGBIO)Arruda, T.S., Dias, U., Dias, Z., Heuristics for the sorting by length-weighted inversion problem (2013) Proceedings of the International Conference on Bioinformatics, Computational Biology and Biomedical Informatics (BCB'2013), pp. 498-507. , Washington DC, USA, ACMArruda, T.S., Dias, U., Dias, Z., Heuristics for the sorting by length-weighted inversions problem on signed permutations (2014) Proceedings of the First International Conference on Algorithms for Computational Biology (AlCoB'2014), , Lecture Notes in Computer Science, Tarragona, Spain, Springer-Verlag. To appearBader, D., Moret, B., Yan, M., A linear-time algorithm for computing inversion distance between signed permutations with an experimental study (2001) Journal of Computational Biology, 8 (5), pp. 483-491Bafna, V., Pevzner, P.A., Genome rearrangements and sorting by reversals (1996) SIAM Journal on Computing, 25 (2), pp. 272-289Bender, M.A., Ge, D., He, S., Hu, H., Pinter, R.Y., Skiena, S., Swidan, F., Improved bounds on sorting by length-weighted reversals (2008) Journal of Computer and System Sciences, 74 (5), pp. 744-774Berman, P., Hannenhalli, S., Karpinski, M., 1.375-Approximation algorithm for sorting by reversals (2002) Proceedings of the 10th Annual European Symposium on Algorithms (ESA'2002), pp. 200-210. , volume 2461 of Lecture Notes in Computer Science, Rome, Italy, Springer-VerlagCaprara, A., Sorting permutations by reversals and eulerian cycle decompositions (1999) SIAM Journal on Discrete Mathematics, 12 (1), pp. 91-110Dalevi, D., Eriksen, N., Eriksson, K., Andersson, S., Genome comparison: The number of evolutionary events separating C. Pneumoniae and C. Trachomatis (2000) Technical Report, University of UppsalaEgri-Nagy, A., Gebhardt, V., Tanaka, M.M., Francis, A.R., Group-theoretic models of the inversion process in bacterial genomes (2013) Journal of Mathematical Biology, pp. 1-23Galvao, G.R., Dias, Z., GRAAu: Genome rearrangement algorithm auditor (2012) Proceedings of the 4th International Conference on Bioinformatics and Computational Biology (BICoB'2012), pp. 97-101. , Las Vegas, Nevada, USA, Curran Associates, IncHannenhalli, S., Pevzner, P.A., Transforming cabbage into turnip: Polynomial algorithm for sorting signed permutations by reversals (1999) Journal of the ACM, 46 (1), pp. 1-27Heath, L.S., Vergara, J.P.C., Sorting by short swaps (2003) Journal of Computational Biology, 10 (5), pp. 775-789Jerrum, M., The complexity of finding minimum-length generator sequences (1985) Theoretical Computer Science, 36, pp. 265-289Kececioglu, J.D., Sankofi, D., Exact and approximation algorithms for sorting by reversals, with application to genome rearrangement (1995) Algorithmica, 13 (1-2), pp. 80-110Lefebvre, J.F., El-Mabrouk, N., Tillier, E., Sankofi, D., Detection and validation of single gene inversions (2003) Bioinformatics, 19, pp. i190-i196McLysaght, A., Seoighe, C., Wolfe, K.H., High frequency of inversions during eukaryote gene order evolution (2000) Comparative Genomics, Computational Biology, 1, pp. 47-58. , D. Sankofi and J. Nadeau, editors, of, Springer NetherlandsNguyen, T.C., Ngo, H.T., Nguyen, N.B., Sorting by restricted-length-weighted reversals (2005) Genomics Proteomics Bioinformatics, 3 (2), pp. 120-127Pinter, R.Y., Skiena, S., Genomic sorting with length-weighted reversals (2002) Genome Informatics, 13, pp. 103-111Sankofi, D., Short inversions and conserved gene cluster (2002) Bioinformatics, 18 (10), p. 1305Seoighe, C., Federspiel, N., Jones, T., Hansen, N., Bivolarovic, V., Surzycki, R., Tamse, R., Wolfe, K.H., Prevalence of small inversions in yeast gene order evolution (2000) Proceedings of the National Academy of Sciences USA, 97 (26), pp. 14433-14437Swidan, F., Bender, M.A., Ge, D., He, S., Hu, H., Pinter, R.Y., Sorting by length-weighted reversals: Dealing with signs and circularity (2004) Combinatorial Pattern Matching, pp. 32-46. , S. Sahinalp, S. Muthukrishnan, and U. Dogrusoz, editors, volume 3109 of Lecture Notes in Computer Science, Springer Berlin HeidelbergTannier, E., Bergeron, A., Sagot, M.F., Advances on sorting by reversals (2007) Discrete Applied Mathematics, 155 (6-7), pp. 881-888Watterson, G.A., Ewens, W.J., Hall, T.E., Morgan, A., The chromosome inversion problem (1982) Journal of Theoretical Biology, 99 (1), pp. 1-
Predictions of drug metabolism pathways through CYP 3A4 enzyme by analysing drug-target interactions network graph
No full textThe available data of drugs and their targets has increased widely in recent years. Far from the traditional way of studying the drug-target interactions, we propose a network-based computational method to identify new targets for known drugs. In this study, the Stanford Biomedical Network Dataset Collection (BIOSNAP Datasets) is used. A network graph is constructed and analyzed to study the relationship between the drugs and their targets. Different centrality and similarity measures analyses are applied and predict new potential metabolism pathways for five drugs, namely (Wortmannin, Voacamine, Vancomycin, Dactinomycin and Arundic acid) through Cytochrome P450 3A4 enzyme in the liver. The application of network theory to the analysis of this dataset reveals a new significant approach. Finally the molecular docking is performed to confirm the results. Also, the importance of the presented method in drug discovery is highlighted/pointed out.ACM Special Interest Group on Knowledge Discovery in Data (SIGKDD) ; Elsevier ; IEEE Computer Society ; IEEE TCDE ; Springe
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Literature Review on Patient-Friendly Documentation Systems
No full textÅhlfeldt H, Borin L, Grabar N, et al. Literature Review on Patient-Friendly Documentation Systems. Milton Keynes, UK: Centre for Research in Computing, The Open University; 2006.This literature review forms a deliverable in the European Network of Excellence on Semantic Interoperability and Data Mining in Biomedicine. More specifically, it is part of a work package (WP27) which aims to develop and evaluate generic methods and tools for assisting patients to understand their health and healthcare by generating patient-friendly readable texts that paraphrase the content of their electronic health records. We have reviewed the literature in topics that we consider to be relevant to this work package. When appropriate, we cover variations in conditions in the four countries of the collaborating research groups (France, Germany, Sweden and the UK) and we cover corpora, tools and language technologies for the European languages of interest to these groups
The building and application of a semantic platform for an e-research society
No full textThis thesis reviews the area of e-Research (the use of electronic infrastructure to support research) and considers how the insight gained from the development of social networking sites in the early 21st century might assist researchers in using this infrastructure. In particular it examines the myExperiment project, a website for e-Research that allows users to upload, share and annotate work flows and associated files, using a social networking framework. This Virtual Organisation (VO) supports many of the attributes required to allow a community of users to come together to build an e-Research society. The main focus of the thesis is how the emerging society that is developing out of my-Experiment could use Semantic Web technologies to provide users with a significantly richer representation of their research and research processes to better support reproducible research. One of the initial major contributions was building an ontology for myExperiment. Through this it became possible to build an API for generating and delivering this richer representation and an interface for querying it. Having this richer representation it has been possible to follow Linked Data principles to link up with other projects that have this type of representation. Doing this has allowed additional data to be provided to the user and has begun to set in context the data produced by myExperiment. The way that the myExperiment project has gone about this task and consideration of how changes may affect existing users, is another major contribution of this thesis. Adding a semantic representation to an emergent e-Research society like myExperiment,has given it the potential to provide additional applications. In particular the capability to support Research Objects, an encapsulation of a scientist's research or research process to support reproducibility. The insight gained by adding a semantic representation to myExperiment, has allowed this thesis to contribute towards the design of the architecture for these Research Objects that use similar Semantic Web technologies. The myExperiment ontology has been designed such that it can be aligned with other ontologies. Scientific Discourse, the collaborative argumentation of different claims and hypotheses, with the support of evidence from experiments, to construct, confirm or disprove theories requires the capability to represent experiments carried out in silico. This thesis discusses how, as part of the HCLS Scientific Discourse subtask group, the myExperiment ontology has begun to be aligned with other scientific discourse ontologies to provide this capability. It also compares this alignment of ontologies with the architecture for Research Objects. This thesis has also examines how myExperiment's Linked Data and that of other projects can be used in the design of novel interfaces. As a theoretical exercise, it considers how this Linked Data might be used to support a Question-Answering system, that would allow users to query myExperiment's data in a more efficient and user-friendly way. It concludes by reviewing all the steps undertaken to provide a semantic platform for an emergent e-Research society to facilitate the sharing of research and its processes to support reproducible research. It assesses their contribution to enhancing the features provided by myExperiment, as well as e-Research as a whole. It considers how the contributions provided by this thesis could be extended to produce additional tools that will allow researchers to make greater use of the rich data that is now available, in a way that enhances their research process rather than significantly changing it or adding extra workload
Energy- and information-managed wireless sensor networks: modelling and simulation
No full textWireless Sensor Networks (WSNs) allow the remote and distributed monitoring of parameters in their deployed environment. WSNs are receiving increasing research interest, due to their ability to enable a wide range of applications, and their potential to have a major impact on ubiquitous computing. Many research challenges are encountered in retaining a useful network lifetime under constraints imposed by the limited energy reserves that are inherent in the small, locally-powered sensor nodes. This research addresses some of these challenges through the development and evaluation of energy- and information-managed algorithms leading to increased network lifetime.The first contribution of this research is the development of an Information manageD Energy-aware ALgorithm for Sensor networks with Rule Managed Reporting (IDEALS/RMR). IDEALS/RMR is an application-independent, localised system to control and manage the degradation of a network through the positive discrimination of packets. This is achieved by the novel combination of energy management (through IDEALS) and information management (through RMR) which increases the network lifetime at the possible expense of often trivial data. IDEALS/RMR is particularly suited to applications where sensor nodes are small, energy constrained, embedded devices particularly those that feature energy harvesting) that are required to report data in an unassisted fashion.The second contribution of this research is the analysis of various environmental and physical aspects of WSNs, and the effect that they have on the operation of nodes and networks. These aspects include energy components (stores, sources and consumers), sensing devices, wireless communication, and timing; these aspects are independently modelled and, through simulation, their effect on the operation of the network is quantified.The third contribution of this research is the evaluation of IDEALS/RMR using a simulator that has been specifically developed to integrate both the proposed environmental and physical models, and a novel node architecture that facilitates structured software design. A scenario depicting the use of a WSN to monitor pump temperature in a water pumping station is simulated, and highlights the benefits of the developed algorithms
Partitioning and Local Matching Learning of Large Biomedical Ontologies
No full textInternational audienceConventional ontology matching systems are not well-tailored to ensure sufficient quality alignments for large ontology matching tasks. In this paper, we propose a local matching learning strategy to align large and complex biomedical ontologies. We define a novel partitioning approach that breakups large ontology alignment task into a set of local sub-matching tasks. We perform a machine learning approach for each local sub-matching task. We build a local machine learning model for each sub-matching task without any user involvement. Each local matching learning model automatically provides adequate matching settings for each local sub-matching task. Our results show that: (i) partitioning approach outperforms existing techniques, (ii) local matching while using a specific machine learning model for each sub-matching task yields to promising results and (iii) the combination between partitioning and machine learning increases the overall result
