DNA Data Storage Research @ Imperial College

Making DNA Data Storage a Reality

Our ultimate goal to make it a staple of modern data centres to store archival data in the very long term.

DNA Data Storage Introduction

DNA, the blueprint of life, is not only responsible for encoding genetic information but also holds incredible potential as a data storage medium  to store archival data in the long term. Find out more about DNA data storage and the research we do at Imperial below and read our DNA storage FAQ!

Read our DNA Storage FAQ

DNA Data Storage

DNA Data Storage, the process of storing arbitrary binary data in DNA sequences is actively researched by us and the community. Its properties, primarily durability and compact form factor, make it an ideal storage media for archiving data for decades. Watch the video here to see what makes DNA an ideal storage media and how it all works.

Processing Data in DNA

Once data is stored in DNA, biomolecular processes can be used to process it on an unprecedented scale. More precisely, combinatorial problems (e.g., databases joins, travelling salesperson problems and others) can be solved in DNA very fast thanks to the unprecedented level of parallelism and also very energy efficient comapred to traditional computing. Watch the video here to learn more.

Modelling DNA Storage as a Constrained Channel

Key to storing binary data in synthetic in DNA is the translation between the binary representation of digital data to the quaternary domain of DNA. This translation must adhere to constraints imposed by the synthesis and sequencing processes used to write and read respectively. A technological advance in either process changes the constraints and renders current encoding schemes obsolete. In this line of work we present a recipe for taking constraints and producing an appropriate encoding scheme. Such a mechanism allows moving the encoding in lockstep with the technological advances in the underlying processes. We further show a method to understand trade-offs in constraints for a given overhead of bits needed to meet such constraints


Selected publications resulting from our research

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Meet the Team

Thomas Heinis

Lab Director

Omer Sella

Omer S. Sella


Roman Sokolovskii

Research Associate

William Hunter

William Hunter

Doctorate Research

Zijian (James) Zhou

Doctorate Research

Samira Brunmayr

MEng Student

Jamie J. Alnasir

Research Associate

Samantha Kwok

M.Sc. Student

Jasmine Quah

M.Sc. Student

Chandler Low

M.Sc. Student

Join us! We have the following student, PhD and PostDoc opportunities available…

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