GSoC Gupta Lab
DNACloud
The term Big Data is usually used to describe huge amount of data that is generated by humans from digital media such as cameras, internet, phones, sensors etc. By building advanced analytics on the top of big data, one can predict many things about the user such as behavior, interest etc. However before one can use the data, one has to address many issues for big data storage. Two main issues are the need of large storage devices and the cost associated with it. Synthetic DNA storage seems to be an appropriate solution to address these issues of the big data. Recently in 2013, Goldman [1] and his collegues from European Bioinformatics Institute demonstrated the use of the DNA as storage medium with capacity of storing 2.2 peta bytes of information on one gram of DNA and retrived the data successfully with low error rate. This significant step shows a promise for synthetic DNA storage as a useful technology for the future data storage. Motivated by this, we have developed a software called DNACloud which makes it easy to store the data on the DNA. For better archival [2] and rewritable DNA [3] based data storage are developed [4].
Software Homepage 
(Click the logo)
Prerequisites: Basic molecular biology, coding theory.
(Student without prerequisites can seek the knowledge in project understanding phase.)
Programming Skills: Python.
Road Map:
References:
1. Goldman, N., Bertone, P., Chen, S., Dessimoz, C., LeProust, E. M., Sipos, B., & Birney, E. (2013). Towards practical, high-capacity, low-maintenance information storage in synthesized DNA. Nature, 494(7435), 77-80.
2. D. Limbachiya, V. Dhameliya, M. Khakhar, and M. K. Gupta, On optimal family of codes for archival DNA storage,in Signal Design and its Applications in Communications (IWSDA), 2015 Seventh International
Workshop on, Sept 2015.
3. Yazdi, S. H. T., Yuan, Y., Ma, J., Zhao, H., & Milenkovic, O. (2015). A rewritable, random-access DNA-based storage system. Scientific reports, 5.
4. Yazdi, S. M., Kiah, H. M., Garcia, E. R., Ma, J., Zhao, H., & Milenkovic, O. (2015). DNA-Based Storage: Trends and Methods. arXiv preprint arXiv:1507.01611.
5. Shalin Shah, Dixita Limbachiya and Manish K. Gupta, DNACloud: A Potential Tool for storing Big Data on DNA, In Proceeding of Foundations of Nanoscience Self-Assembled Architectures and Devices(FNANO14), SnowBird, Utah, USA. pp. 204–205, 2014 (poster) arXiv:1310.6992 [cs.ET]
Graduate Mentor
Dixita Limbachiya
Key Developers
1. Shalin Shah (PhD student at Dept of ECE Duke university, USA)
2. Madhav Kahkhhar (Intern at Endurance International Group)
3. Vijay Dhameliya
2. D. Limbachiya, V. Dhameliya, M. Khakhar, and M. K. Gupta, On optimal family of codes for archival DNA storage,in Signal Design and its Applications in Communications (IWSDA), 2015 Seventh International Workshop on, Sept 2015.
3. Yazdi, S. H. T., Yuan, Y., Ma, J., Zhao, H., & Milenkovic, O. (2015). A rewritable, random-access DNA-based storage system. Scientific reports, 5.
4. Yazdi, S. M., Kiah, H. M., Garcia, E. R., Ma, J., Zhao, H., & Milenkovic, O. (2015). DNA-Based Storage: Trends and Methods. arXiv preprint arXiv:1507.01611.
5. Shalin Shah, Dixita Limbachiya and Manish K. Gupta, DNACloud: A Potential Tool for storing Big Data on DNA, In Proceeding of Foundations of Nanoscience Self-Assembled Architectures and Devices(FNANO14), SnowBird, Utah, USA. pp. 204–205, 2014 (poster) arXiv:1310.6992 [cs.ET]
2. Madhav Kahkhhar (Intern at Endurance International Group)
3. Vijay Dhameliya