Savitha Parur Venkitachalam
Western Michigan University, Department of Computer Science, Kalamazoo, MI 49008, USA
Savitha Parur Venkitachalam is a Graduate Student in Computer Science at Western Michigan University, Kalamazoo, Michigan. She completed her Bachelor’s Degree in Electronics & Communication Engineering from Avinashilingam Deemed University, India. Savitha’s professional experience includes 2.5 years as a Software Engineer and Project Lead at UST Global in India and Graduate internships at Whirlpool Corporation
Survey of cloud computing tools in Bioinformatics is a study of the different tools, algorithms and current projects in the field of Bioinformatics that leverage the power of cloud computing. This survey has used different cloud service providers like Amazon web services, Penguin On Demand, Microsoft Azure to study the different bioinformatics tools and datasets they host. This study also includes testing some of the bioinformatics programs on cloud and documenting the performance and benefits of running large datasets on cloud. The tools studied as part of this survey will benefit any firm in the field of Bioinformatics that aims to run its programs on cloud. Bio-informatics is a field that requires large amounts of computational power to conduct research and experiments can benefit significantly from the services provided by cloud computing. This survey documents the benefits of using a cloud service and analyzes bioinformatics tools like CloudBlast, CloudBurst, Cloud Aligner and many more. Many useful public data sets in Bioinformatics that are available in cloud include Ensembl, Annotated Human Genome Data, 1000 Genomes project, Model Organism Encyclopedia of DNA Elements, Denisova Genomes, Genbank etc. Database and storage capacity offered by each service provider vary greatly. Another interesting feature includes studying the use of frame works like Hadoop in Bioinformatics. Leveraging these tools and cloud providers, bioinformatics firms can gain access to latest technology and achieve significant cost benefits. This survey was done as a semester project for the Graduate course Bioinformatics and Data Mining research under the guidance of Dr. Elise de Doncker, Professor, Department of Computer Science, Western Michigan University.