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Department of Applied Mathematics and Theoretical Physics

Career

  • 1997-2000 Wellcome Trust Fellow in Mathematical Biology, Edinburgh
  • 2000-2001 Lecturer, School of Informatics, Edinburgh
  • 2001-2004 Wellcome Trust Travelling Fellowship, St Louis and Edinburgh
  • 2004-2006 Lecturer, DAMTP
  • 2006-2015 Senior Lecturer, DAMTP
  • 2015- Reader. DAMTP

Research

Stephen Eglen is a computational neuroscientist: he uses computational methods to study the development of the nervous system, using mostly the retina and other parts of the visual pathway as a model system. He is particularly interested in questions of structural and functional development:

Structural development: how do retinal neurons acquire their positional information within a circuit?

Functional development: what are the mechanisms by which neurons make contact with each other, to perform functioning circuits?

Selected Publications

Please see my publications page

Publications

Ten simple rules for writing Dockerfiles for reproducible data science
D Nüst, V Sochat, B Marwick, SJ Eglen, T Head, T Hirst, BD Evans
– PLOS Computational Biology
(2020)
16,
e1008316
Ten Simple Rules for Writing Dockerfiles for Reproducible Data Science
D Nüst, V Sochat, B Marwick, S Eglen, T Head, T Hirst, B Evans
(2020)
From random to regular: Variation in the patterning of retinal mosaics.
PW Keeley, SJ Eglen, BE Reese
– The Journal of comparative neurology
(2020)
528,
2135
Open Code and Peer Review
S Eglen, E Lieungh
– Open Science Talk
(2020)
Functional characterization of human pluripotent stem-derived cortical networks differentiated on laminin-521 substrate: comparison to rat cortical cultures
T Hyvärinen, A Hyysalo, FE Kapucu, L Aarnos, A Vinogradov, SJ Eglen, L Ylä-Outinen, S Narkilahti
– Scientific reports
(2019)
9,
17125
CODECHECK: An open-science initiative to facilitate sharing of computer programs and results presented in scientific publications
S Eglen, D Nüst
– Septentrio Conference Series
(2019)
DeepClean: Self-Supervised Artefact Rejection for Intensive Care Waveform Data Using Deep Generative Learning
T Edinburgh, P Smielewski, M Czosnyka, M Cabeleira, SJ Eglen, A Ercole
(2019)
Burst Detection Methods.
E Cotterill, SJ Eglen
(2019)
22,
185
Recent developments in scholarly publishing to improve research practices in the life sciences
SJ Eglen, R Mounce, L Gatto, AM Currie, Y Nobis
– Emerging topics in life sciences
(2018)
2,
775
Recent developments in scholarly publishing to improve research practices in the life sciences
S Eglen, R Mounce, L Gatto, A Currie, Y Nobis
(2018)
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Research Group

Computational Biology

Room

G0.11