Simon Andrews

Simon Andrews did his first degree in Microbiology at the University of Warwick.  After a breif period working for Sandoz pharmaceuticals he went on  to do a PhD in protein engineering a the University of Newcastle with Harry Gilbert.  During his PhD his interests moved from bench work toward the emerging field of bioinformatics, and he decided to follow this direction in his future career.

After completing his PhD Simon worked with the BBSRC IT Services where he developed and then presented a series of bioinformatics training courses in protein structure analysis to the BBSRC institutes.  At one of these courses at Babraham he met John Coadwell who establised the Babraham bioinformatics group and was then employed as the second member of the bioinformatics team.  Since joining Babraham Simon has seen the group grow from two people to nine as the field has become far more prominent in the biological research community.  He took over the running of the group in 2010.

Latest Publications

LipidFinder 2.0: advanced informatics pipeline for lipidomics discovery applications.
Alvarez-Jarreta J, Rodrigues PRS, Fahy E, O'Connor A, Price A, Gaud C, Andrews S, Benton P, Siuzdak G, Hawksworth JI, Valdivia-Garcia M, Allen SM, O'Donnell VB

We present LipidFinder 2.0, incorporating four new modules that apply artefact filters, remove lipid and contaminant stacks, in-source fragments and salt clusters, and a new isotope deletion method which is significantly more sensitive than available open-access alternatives. We also incorporate a novel false discovery rate (FDR) method, utilizing a target-decoy strategy, which allows users to assess data quality. A renewed lipid profiling method is introduced which searches three different databases from LIPID MAPS and returns bulk lipid structures only, and a lipid category scatter plot with color blind friendly pallet. An API interface with XCMS Online is made available on LipidFinder's online version. We show using real data that LipidFinder 2.0 provides a significant improvement over non-lipid metabolite filtering and lipid profiling, compared to available tools.

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Bioinformatics (Oxford, England), 1, 1, 07 Oct 2020

PMID: 33027502

Correction to: DNA methylation changes during preimplantation development reveal interspecies differences and reprogramming events at imprinted genes.
Ivanova E, Canovas S, Garcia-Martínez S, Romar R, Lopes JS, Rizos D, Sanchez-Calabuig MJ, Krueger F, Andrews S, Perez-Sanz F, Kelsey G, Coy P

An amendment to this paper has been published and can be accessed via the original article.

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Clinical epigenetics, 12, 1, 29 Jun 2020

PMID: 32600441

High-Throughput Quantitative RT-PCR in Single and Bulk C. elegans Samples Using Nanofluidic Technology.
Chauve L, Le Pen J, Hodge F, Todtenhaupt P, Biggins L, Miska EA, Andrews S, Casanueva O

This paper presents a high-throughput reverse transcription quantitative PCR (RT-qPCR) assay for Caenorhabditis elegans that is fast, robust, and highly sensitive. This protocol obtains precise measurements of gene expression from single worms or from bulk samples. The protocol presented here provides a novel adaptation of existing methods for complementary DNA (cDNA) preparation coupled to a nanofluidic RT-qPCR platform. The first part of this protocol, named 'Worm-to-CT', allows cDNA production directly from nematodes without the need for prior mRNA isolation. It increases experimental throughput by allowing the preparation of cDNA from 96 worms in 3.5 h. The second part of the protocol uses existing nanofluidic technology to run high-throughput RT-qPCR on the cDNA. This paper evaluates two different nanofluidic chips: the first runs 96 samples and 96 targets, resulting in 9,216 reactions in approximately 1.5 days of benchwork. The second chip type consists of six 12 x 12 arrays, resulting in 864 reactions. Here, the Worm-to-CT method is demonstrated by quantifying mRNA levels of genes encoding heat shock proteins from single worms and from bulk samples. Provided is an extensive list of primers designed to amplify processed RNA for the majority of coding genes within the C. elegans genome.

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Journal of visualized experiments : JoVE, 1, 159, 28 May 2020

PMID: 32538915

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