Abstract
Cloud computing services have found applications as low cost, effective to analyze, store data and have been applied to health, biomedical, and life sciences domain. Both Microsoft Azure and Amazon Web Services (AWS) have been instrumental in facilitating research in the domain of life sciences. We discuss in this chapter the application of AZURE and AWS in research in the domain of Life sciences.
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Abbreviations
- AI:
-
Artificial intelligence
- AML:
-
Azure Machine Learning
- ASSS:
-
Amazon Simple Storage Service
- DA:
-
Data analytics
- DDI:
-
AWS Diagnostic Development Initiative
- DL:
-
Deep learning
- DRMAA:
-
Distributed Resource Management Application API
- EC2:
-
Elastic Compute Cloud
- EHR:
-
Electronic health records
- FINRA:
-
Financial Industry Regulatory Authority
- HPC:
-
High performance computing
- JIST:
-
Java Image Science Toolkit
- MIPAV:
-
Medical-image processing, analysis, and visualization
- ML:
-
Machine learning
- NGS:
-
Next-generation sequencing
- NL:
-
Natural language
- NLP:
-
Natural language processing
- OS:
-
Operating system
- PDB:
-
Protein Data Bank
- VMs:
-
Virtual machines
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© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Ghosh, S., Dasgupta, R. (2022). Artificial Intelligence Industry and the Domain of Life Sciences. In: Machine Learning in Biological Sciences. Springer, Singapore. https://doi.org/10.1007/978-981-16-8881-2_19
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DOI: https://doi.org/10.1007/978-981-16-8881-2_19
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Online ISBN: 978-981-16-8881-2
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