Parallel and Cloud-Based Bioinformatics and Biomedicine
A special issue of BioTech (ISSN 2673-6284).
Deadline for manuscript submissions: closed (30 September 2018) | Viewed by 295
Special Issue Information
Dear Colleagues,
The availability of high-throughput platforms (e.g. next generation sequencing, microarray and mass spectrometry) and clinical diagnostic tools (e.g. medical imaging) is producing an overwhelming volume of experimental and clinical data. Thus, considering the complex analysis pipeline of the biomedical research, the bottleneck is more and more moving toward the storage, integration, and analysis of experimental data, as well as their correlation and integration with publicly available data banks. High Performance Computing offers the computational power and the storage to face this overwhelming availability of data, while Cloud Computing hides the complexity of computing infrastructures reducing the cost of the data analysis, and most importantly is changing the overall model of biomedical research and health provision.
Novel parallel architectures (e.g. CELL processors, GPUs, FPGA, hybrid CPU/FPGA) coupled with emerging programming models may overcome the limits posed by conventional computers to the mining and exploration of large amounts of data. Cloud Computing is able to offer scalable costs and increased reachability, availability and easiness of application use, and also the possibility to enforce collaboration among scientists. However, many problems remain to be solved, such as availability and safety of the data, privacy-related issues, availability of software platforms for rapid deployment, execution and billing of biomedical applications.
This Special Issue invites submissions on efficient algorithms, software tools and comprehensive data analysis pipelines for the preprocessing, integration and mining of molecular and clinical data; as well as submissions on applications of high performance computing and cloud computing in biology, medicine and clinical practice.
Prof. Dr. Mario Cannataro
Guest Editor
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Keywords
- Parallel bioinformatics algorithms
- Parallel preprocessing of omics and clinical data
- Parallel visualization and exploration of omics and clinical data
- High-throughput comprehensive bioinformatics pipelines
- Computing environments for large scale collaboration
- Scientific workflows in bioinformatics and biomedicine
- Parallel processing of bio-signals and bio-images
- Cloud computing for bioinformatics and biomedicine
- Cloud computing for health systems
- Privacy issues for cloud-based biomedical applications
- Services for bioinformatics and biomedicine
- Large scale biological and biomedical databases
- Integration and analysis of molecular and clinical data
- Ontologies in biology and medicine
- P4 (predictive, preventive, personalized and participatory) medicine
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