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Research

Biological systems - including the simplest cells - exhibit a broad range of functions to thrive in their environment. Research in the Imperial College Centre for Synthetic Biology is focused on the possibility of engineering the underlying biochemical processes to solve many of the challenges facing society, from healthcare to sustainable energy. In particular, we model, analyse, design and build biological and biochemical systems in living cells and/or in cell extracts, both exploring and enhancing the engineering potential of biology.

As part of our research we develop novel methods to accelerate the celebrated Design-Build-Test-Learn synthetic biology cycle. As such research in the Centre for Synthetic Biology highly multi- and interdisciplinary covering computational modelling and machine learning approaches; automated platform development and genetic circuit engineering ; multi-cellular and multi-organismal interactions, including gene drive and genome engineering; metabolic engineering; in vitro/cell-free synthetic biology; engineered phages and directed evolution; and biomimetics, biomaterials and biological engineering.

Publications

Citation

BibTex format

@inproceedings{Appuswamy:2019,
author = {Appuswamy, R and Lebrigand, K and Barbry, P and Antonini, M and Madderson, O and Freemont, P and MacDonald, J and Heinis, T},
title = {Oligoarchive: Using DNA in the DBMS storage hierarchy},
year = {2019}
}

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RIS format (EndNote, RefMan)

TY - CPAPER
AB - © 2019 Conference on Innovative Data Systems Research (CIDR). All rights reserved. The demand for data-driven decision making coupled with need to retain data to meet regulatory compliance requirements has resulted in a rapid increase in the amount of archival data stored by enterprises. As data generation rate far outpaces the rate of improvement in storage density of media like HDD and tape, researchers have started investigating new architectures and media types that can store such “cold”, infrequently accessed data at very low cost. Synthetic DNA is one such storage media that has received some attention recently due to its high density and durability. In this paper, we investigate the problem of integrating DNA in the database storage hierarchy. More specifically, we ask the following two questions: (i) how can database knowledge help optimize DNA encoding and decoding? and (ii) how can biochemical mechanisms used for DNA manipulation be used to perform in-vitro, near-data SQL query processing? In answering these questions, we present OligoArchive, an architecture for using DNA-based storage system as the archival tier of a relational database. We demonstrate that OligoArchive can be realized in practice by building archiving and recovery tools (pg_oligo_dump and pg_oligo_restore) for PostgreSQL that perform schema-aware encoding and decoding of relational data on DNA, and using these tools to archive a 12KB TPC-H database to DNA, perform in-vitro computation, and restore it back again.
AU - Appuswamy,R
AU - Lebrigand,K
AU - Barbry,P
AU - Antonini,M
AU - Madderson,O
AU - Freemont,P
AU - MacDonald,J
AU - Heinis,T
PY - 2019///
TI - Oligoarchive: Using DNA in the DBMS storage hierarchy
ER -

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