Melchizedek Mashiku
ABSTRACT
In this paper we discuss the development of a science gateway; identifying Ca2+ binding sites in proteins using a java application developed by Dr. Jenny Yang at the Chemistry department, Georgia State University. Starting with a Protein Data Bank (PDB) X-ray or NMR structure file, MUGC application predicts calcium binding sites using a graph theory-based algorithm [1]. The project creates a science gateway to provide access to the MUGC algorithm using tools provided by Amazon Web Services. The full-stack solution uses S3 storage, AWS Lambda functions, and API gateway to relay the PDB files to the back-end computing in EC2. Architecture for a full stack serverless processing pipeline is implemented which allows users to access the application. The design is optimized for scalability, reliability, security, performance, and cost.
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Index Terms
- Serverless Science Gateway Development for Ca2+ binding site prediction on Amazon Web Services: Case Study
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