Padraig Gleeson

University College London, London, United Kingdom 
Computational neuroscience
"Padraig Gleeson"
Mean distance: 15.3 (cluster 11)


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Angus Silver grad student UCL


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Ankur Sinha post-doc 2020- UCL
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Birgiolas J, Haynes V, Gleeson P, et al. (2023) NeuroML-DB: Sharing and characterizing data-driven neuroscience models described in NeuroML. Plos Computational Biology. 19: e1010941
Shaikh B, Smith LP, Vasilescu D, et al. (2022) BioSimulators: a central registry of simulation engines and services for recommending specific tools. Nucleic Acids Research
Waltemath D, Golebiewski M, Blinov ML, et al. (2020) The first 10 years of the international coordination network for standards in systems and synthetic biology (COMBINE). Journal of Integrative Bioinformatics
Dai K, Hernando J, Billeh YN, et al. (2020) The SONATA data format for efficient description of large-scale network models. Plos Computational Biology. 16: e1007696
Schreiber F, Sommer B, Bader GD, et al. (2019) Specifications of Standards in Systems and Synthetic Biology: Status and Developments in 2019. Journal of Integrative Bioinformatics
Gleeson P, Cantarelli M, Marin B, et al. (2019) Open Source Brain: A Collaborative Resource for Visualizing, Analyzing, Simulating, and Developing Standardized Models of Neurons and Circuits. Neuron
Dura-Bernal S, Suter BA, Gleeson P, et al. (2019) NetPyNE, a tool for data-driven multiscale modeling of brain circuits. Elife. 8
Dura-Bernal S, Suter BA, Gleeson P, et al. (2019) Author response: NetPyNE, a tool for data-driven multiscale modeling of brain circuits Elife
Neal ML, König M, Nickerson D, et al. (2018) Harmonizing semantic annotations for computational models in biology. Briefings in Bioinformatics
Blundell I, Brette R, Cleland TA, et al. (2018) Code Generation in Computational Neuroscience: A Review of Tools and Techniques. Frontiers in Neuroinformatics. 12: 68
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