Andrew P. Davison

Orcid: 0000-0002-4793-7541

According to our database1, Andrew P. Davison authored at least 28 papers between 1999 and 2023.

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Bibliography

2023
EBRAINS Live Papers - Interactive Resource Sheets for Computational Studies in Neuroscience.
Neuroinformatics, January, 2023

2022
The EBRAINS Hodgkin-Huxley Neuron Builder: An online resource for building data-driven neuron models.
Frontiers Neuroinformatics, August, 2022

2021
HippoUnit: A software tool for the automated testing and systematic comparison of detailed models of hippocampal neurons based on electrophysiological data.
PLoS Comput. Biol., 2021

2020
The SONATA data format for efficient description of large-scale network models.
PLoS Comput. Biol., 2020

Editorial: Reproducibility and Rigour in Computational Neuroscience.
Frontiers Neuroinformatics, 2020

2018
Code Generation in Computational Neuroscience: A Review of Tools and Techniques.
Frontiers Neuroinformatics, 2018

Arkheia: Data Management and Communication for Open Computational Neuroscience.
Frontiers Neuroinformatics, 2018

2017
Sustainable computational science: the ReScience initiative.
PeerJ Comput. Sci., 2017

2016
Requirements for storing electrophysiology data.
CoRR, 2016

A Collaborative Simulation-Analysis Workflow for Computational Neuroscience Using HPC.
Proceedings of the High-Performance Scientific Computing, 2016

2015
Python in neuroscience.
Frontiers Neuroinformatics, 2015

2014
PyNN: A Python API for Neural Network Modeling.
Proceedings of the Encyclopedia of Computational Neuroscience, 2014

libNeuroML and PyLEMS: using Python to combine procedural and declarative modeling approaches in computational neuroscience.
Frontiers Neuroinformatics, 2014

Neo: an object model for handling electrophysiology data in multiple formats.
Frontiers Neuroinformatics, 2014

Efficient generation of connectivity in neuronal networks from simulator-independent descriptions.
Frontiers Neuroinformatics, 2014

2013
Integrated workflows for spiking neuronal network simulations.
Frontiers Neuroinformatics, 2013

2012
Automated Capture of Experiment Context for Easier Reproducibility in Computational Research.
Comput. Sci. Eng., 2012

2011
A comprehensive workflow for general-purpose neural modeling with highly configurable neuromorphic hardware systems.
Biol. Cybern., 2011

2010
NeuroML: A Language for Describing Data Driven Models of Neurons and Networks with a High Degree of Biological Detail.
PLoS Comput. Biol., 2010

2009
NEURON and Python.
Frontiers Neuroinformatics, 2009

Establishing a novel modeling tool: a python-based interface for a neuromorphic hardware system.
Frontiers Neuroinformatics, 2009

2008
PyNN: a common interface for neuronal network simulators.
Frontiers Neuroinformatics, 2008

2007
Simulation of networks of spiking neurons: A review of tools and strategies.
J. Comput. Neurosci., 2007

2006
Biophysical and Phenomenological Models of Multiple Spike Interactions in Spike-timing Dependent Plasticity.
Int. J. Neural Syst., 2006

2004
Semi-automated population of an online database of neuronal models (ModelDB) with citation information, using PubMed for validation.
Neuroinformatics, 2004

2003
ModelDB - Making models publicly accessible to support computational neuroscience.
Neuroinformatics, 2003

2001
Spike synchronization in a biophysically-detailed model of the olfactory bulb.
Neurocomputing, 2001

1999
Structure of Lateral Inhibition in an Olfactory Bulb Model.
Proceedings of the Foundations and Tools for Neural Modeling, 1999


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