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increase in data volume, it is necessary to adopt parallelism techniques to achieve reasonable query response time. The main focus will be on parallel query processing, which is the main driver for Big Data
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increase in data volume, it is necessary to adopt parallelism techniques to achieve reasonable query response time. The main focus will be on parallel query processing, which is the main driver for Big Data
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-cell RNA-seq datasets; (2) cross-validating the pattern in independent datasets and (3) associating observed spatial patterns with known literature in congenital heart disease. References https
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) and data engineering for reproducible research. Familiarity with cloud/HPC workflows, containerisation (Docker), and basic bioinformatics pipelines will be preferred. Cross-disciplinary training and
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) and data engineering for reproducible research. Familiarity with cloud/HPC workflows, containerisation (Docker), and basic bioinformatics pipelines will be preferred. Cross-disciplinary training and
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., Allen J., et.al. Predicting tumor cell line response to drug pairs with deep learning. BMC Bioinformatics. 2018; 19(Suppl 18): 486. doi: 10.1186/s12859-018-2509-3 Chiu Y., Chen H., Zhang T., Zhang S
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., Allen J., et.al. Predicting tumor cell line response to drug pairs with deep learning. BMC Bioinformatics. 2018; 19(Suppl 18): 486. doi: 10.1186/s12859-018-2509-3 Chiu Y., Chen H., Zhang T., Zhang S
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). Available at SSRN: https://ssrn.com/abstract=3461418 or http://dx.doi.org/10.2139/ssrn.3461418 Fitzgibbon, L.J., D. L. Dowe and F. Vahid (2004). Minimum Message Length Autoregressive Model Order
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). Available at SSRN: https://ssrn.com/abstract=3461418 or http://dx.doi.org/10.2139/ssrn.3461418 Fitzgibbon, L.J., D. L. Dowe and F. Vahid (2004). Minimum Message Length Autoregressive Model Order
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(mobile-edge-cloud continuum) federated learning architecture and develop context-aware models and schemes for optimising distribution, storage and processing of tasks and data in each layer. Required