Gene Expression Data Analysis in Cloud Computing


A gene is the basic physical and functional unit of heredity. Genes, which are made up of DNA, act as instructions to make molecules, such as proteins. In humans, genes vary in size from a few hundred DNA bases to more than 2 million bases.

Gene expression:
Gene expression is the process by which information from a gene is used in the synthesis of a functional gene product, such as proteins.

Some of the tools for gene expression analysis are-
  • AltAnalyze
  • Dchip
  • geWorkbench 2.5.1 from NCI.
  • Babelomics suit
  • Myrna

Cloud-CoXCS, is a machine learning classification system for gene expression datasets on the Cloud infrastructure.

It is composed of three components: CoXCS, Aneka, and Cloud computing infrastructure.

Gene expression technology, allows for the monitoring of the expression levels of thousands of genes at once.

As a direct result of recent advances technology, it is now feasible to obtain gene expression profiles of tissue samples at relatively low costs.

The gene expression software’s, such as as Myrna, uses cloud computing, an Internet-based method of sharing computer resources.

Cloud computing bundles together the processing power of the individual computers using the Internet.

A number of firms with large computing centers like Amazon, Microsoft etc, rent unused computers over the Internet for a fee.

Cloud computing makes economic sense because cloud vendors are very efficient at running and maintaining huge collections of computers.

Researchers struggling to keep pace with their sequencing instruments can use the cloud to scale up their analyses while avoiding the headaches associated with building and running their own computer center.

More topics from Cloud Computing to read
Cloud Computing: covered following topics in these notes.
  1. Introduction to Cloud Computing
  2. Historical development of Cloud Computing 
  3. Vision of Cloud Computing
  4. Characteristics of cloud computing as per NIST
  5. Cloud computing reference model
  6. Cloud computing environments
  7. Cloud services requirements
  8. Cloud and dynamic infrastructure
  9. Cloud Adoption and rudiments
  10. Cloud application: ECG Analysis in the cloud
  11. Cloud application: Protein structure prediction
  12. Cloud application: Gene Expression Data Analysis
  13. Cloud Computing Architecture
  14. IaaS
  15. PaaS
  16. SaaS
  17. Types of Clouds
  18. Cloud Interoperability & Standards
  19. Scalability and Fault Tolerance
  20. Cloud Ecosystem
  21. Cloud Business Process Management
  22. Cloud Service Management
  23. Cloud Analytics
  24. Testing Under Control
  25. Virtual Desktop Infrastructure
  26. Cloud Resiliency
  27. Cloud Provisioning
  28. Asset management
  29. Concepts of Map reduce
  30. Cloud Governance
  31. High Availability and Disaster Recovery
  32. Virtualization in cloud computing
  33. Server virtualization
  34. Hypervisor management software
  35. Third Party Cloud Services
  36. Case Study: Google App Engine
  37. Case Study: Microsoft Azure
  38. Case Study: Hadoop
  39. Case Study: Amazon
  40. Case Study: Aneka
A list of Video lectures
  1. Buyya, Selvi ,” Mastering Cloud Computing “,TMH Pub
  2. Krutz , Vines, “Cloud Security “ , Wiley Pub
  3. Velte, “Cloud Computing- A Practical Approach” ,TMH Pub
  4. Sosinsky, “ Cloud Computing” , Wiley Pub