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Department of Applied Mathematics and Theoretical Physics

Professor Stephen John Eglen

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

CODECHECK: an Open Science initiative for the independent execution of computations underlying research articles during peer review to improve reproducibility.
D Nüst, SJ Eglen
– F1000Res
(2021)
10,
253
(doi: 10.12688/f1000research.51738.2)
CODECHECK: an Open Science initiative for the independent execution of computations underlying research articles during peer review to improve reproducibility
D Nüst, SJ Eglen
– F1000Research
(2021)
10,
253
(doi: 10.12688/f1000research.51738.1)
CODECHECK: an Open Science initiative for the independent execution of computations underlying research articles during peer review to improve reproducibility
D Nüst, S Eglen
(2021)
(doi: 10.12688/f1000research.51738.2)
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 Comput Biol
(2020)
16,
e1008316
(doi: 10.1371/journal.pcbi.1008316)
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)
(doi: 10.31219/osf.io/fsd7t)
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
(doi: 10.1002/cne.24880)
Open Code and Peer Review
S Eglen, E Lieungh
– Open Science Talk
(2020)
(doi: 10.7557/19.5311)
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
(doi: 10.1038/s41598-019-53647-8)
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)
(doi: 10.7557/5.4910)
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)
(doi: 10.1007/978-3-030-59436-7_45)
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Research Group

Computational Biology

Email

S.J.Eglen@damtp.cam.ac.uk

Room

G0.11

Personal homepage

http://www.damtp.cam.ac.uk/user/sje30/

Study at Cambridge

About the University

Research at Cambridge