| Saturated reconstruction of a volume of neocortex N Kasthuri, KJ Hayworth, DR Berger, RL Schalek, JA Conchello, ... Cell 162 (3), 648-661, 2015 | 1079 | 2015 |
| Functional connectomics spanning multiple areas of mouse visual cortex MICrONS Consortium, JA Bae, M Baptiste, CA Bishop, AL Bodor, ... BioRxiv, 2021.07. 28.454025, 2021 | 152 | 2021 |
| Quantifying mesoscale neuroanatomy using X-ray microtomography EL Dyer, WG Roncal, JA Prasad, HL Fernandes, D Gürsoy, V De Andrade, ... eneuro 4 (5), 2017 | 88 | 2017 |
| Graph classification using signal-subgraphs: Applications in statistical connectomics JT Vogelstein, WG Roncal, RJ Vogelstein, CE Priebe IEEE transactions on pattern analysis and machine intelligence 35 (7), 1539-1551, 2012 | 85 | 2012 |
| A community-developed open-source computational ecosystem for big neuro data JT Vogelstein, E Perlman, B Falk, A Baden, W Gray Roncal, ... Nature methods 15 (11), 846-847, 2018 | 67 | 2018 |
| The Open Connectome Project Data Cluster: Scalable Analysis and Vision for High-Throughput Neuroscience R Burns, W Gray Roncal, D Kleissas, K Lillaney, P Manavalan, E Perlman, ... arXiv preprint arXiv:1306.3543, 2013 | 66 | 2013 |
| MIGRAINE: MRI graph reliability analysis and inference for connectomics WG Roncal, ZH Koterba, D Mhembere, DM Kleissas, JT Vogelstein, ... 2013 IEEE Global Conference on Signal and Information Processing, 313-316, 2013 | 56 | 2013 |
| Magnetic resonance connectome automated pipeline: an overview WR Gray, JA Bogovic, JT Vogelstein, BA Landman, JL Prince, ... IEEE pulse 3 (2), 42-48, 2012 | 55 | 2012 |
| Mine your own view: Self-supervised learning through across-sample prediction M Azabou, MG Azar, R Liu, CH Lin, EC Johnson, K Bhaskaran-Nair, ... arXiv preprint arXiv:2102.10106, 2021 | 52 | 2021 |
| A high-throughput pipeline identifies robust connectomes but troublesome variability G Kiar, EW Bridgeford, WRG Roncai, ... Biorxiv, 188706, 2017 | 48* | 2017 |
| Eliminating accidental deviations to minimize generalization error and maximize replicability: Applications in connectomics and genomics EW Bridgeford, S Wang, Z Wang, T Xu, C Craddock, J Dey, G Kiar, ... PLoS computational biology 17 (9), e1009279, 2021 | 44 | 2021 |
| VESICLE: volumetric evaluation of synaptic interfaces using computer vision at large scale WG Roncal, M Pekala, V Kaynig-Fittkau, DM Kleissas, JT Vogelstein, ... arXiv preprint arXiv:1403.3724, 2014 | 40* | 2014 |
| Science in the cloud (SIC): A use case in MRI connectomics G Kiar, KJ Gorgolewski, D Kleissas, WG Roncal, B Litt, B Wandell, ... Giga Science 6 (5), gix013, 2017 | 39 | 2017 |
| An automated images-to-graphs framework for high resolution connectomics WR Gray Roncal, DM Kleissas, JT Vogelstein, P Manavalan, K Lillaney, ... Frontiers in neuroinformatics 9, 149964, 2015 | 34 | 2015 |
| DotMotif: an open-source tool for connectome subgraph isomorphism search and graph queries JK Matelsky, EP Reilly, EC Johnson, J Stiso, DS Bassett, BA Wester, ... Scientific Reports 11 (1), 13045, 2021 | 30 | 2021 |
| A framework for rigorous evaluation of human performance in human and machine learning comparison studies HP Cowley, M Natter, K Gray-Roncal, RE Rhodes, EC Johnson, ... Scientific reports 12 (1), 5444, 2022 | 27 | 2022 |
| The Brain Observatory Storage Service and Database (BossDB): A Cloud-Native Approach for Petascale Neuroscience Discovery R Hider Jr, D Kleissas, T Gion, D Xenes, J Matelsky, D Pryor, L Rodriguez, ... Frontiers in Neuroinformatics 16, 828787, 2022 | 24 | 2022 |
| Computing Scalable Multivariate Glocal Invariants of Large (Brain-) Graphs D Mhembere, W Gray Roncal, D Sussman, CE Priebe, R Jung, S Ryman, ... IEEE GlobalSIP, 2013 | 23 | 2013 |
| Container-based clinical solutions for portable and reproducible image analysis J Matelsky, G Kiar, E Johnson, C Rivera, M Toma, W Gray-Roncal Journal of digital imaging 31, 315-320, 2018 | 20 | 2018 |
| ndmg: Neurodata’s mri graphs pipeline G Kiar, WG Roncal, D Mhembere, E Bridgeford, R Burns, J Vogelstein Zenodo, 2016 | 20 | 2016 |
