| Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution SG Rodriques, RR Stickels, A Goeva, CA Martin, E Murray, ... Science 363 (6434), 1463-1467, 2019 | 1585 | 2019 |
| Molecular diversity and specializations among the cells of the adult mouse brain A Saunders, EZ Macosko, A Wysoker, M Goldman, FM Krienen, ... Cell 174 (4), 1015-1030. e16, 2018 | 1287 | 2018 |
| Robust decomposition of cell type mixtures in spatial transcriptomics DM Cable, E Murray, LS Zou, A Goeva, EZ Macosko, F Chen, RA Irizarry Nature biotechnology 40 (4), 517-526, 2022 | 449 | 2022 |
| Loss landscapes of regularized linear autoencoders D Kunin, JM Bloom, A Goeva, C Seed ICML, arXiv:1901.08168 97 (PMLR), 3560-3569, 2019 | 93 | 2019 |
| Initial evaluation of the effects of an environmental‐focused problem‐solving intervention for transition‐age young people with developmental disabilities: Project TEAM JM Kramer, C Helfrich, M Levin, IT Hwang, PS Samuel, A Carrellas, ... Developmental Medicine & Child Neurology 60 (8), 801-809, 2018 | 40 | 2018 |
| A single-cell atlas of cell types, states, and other transcriptional patterns from nine regions of the adult mouse brain A Saunders, E Macosko, A Wysoker, M Goldman, F Krienen, H de Rivera, ... BioRxiv, 299081, 2018 | 31 | 2018 |
| Exposure of iPSC-derived human microglia to brain substrates enables the generation and manipulation of diverse transcriptional states in vitro MJ Dolan, M Therrien, S Jereb, T Kamath, V Gazestani, T Atkeson, ... Nature Immunology 24 (8), 1382-1390, 2023 | 21 | 2023 |
| Reconstructing input models via simulation optimization A Goeva, H Lam, B Zhang Proceedings of the Winter Simulation Conference 2014, 698-709, 2014 | 14 | 2014 |
| Optimization-based calibration of simulation input models A Goeva, H Lam, H Qian, B Zhang Operations research 67 (5), 1362-1382, 2019 | 13 | 2019 |
| A resource for generating and manipulating human microglial states in vitro MJ Dolan, M Therrien, S Jereb, T Kamath, T Atkeson, SE Marsh, A Goeva, ... BioRxiv, 2022.05. 02.490100, 2022 | 12 | 2022 |
| Emergence of division of labor in tissues through cell interactions and spatial cues M Adler, N Moriel, A Goeva, I Avraham-Davidi, S Mages, TS Adams, ... Cell Reports 42 (5), 2023 | 11 | 2023 |
| Toward reproducible and extensible research: from values to action A Goeva, S Stoudt, A Trisovic PubPub 2 (4), 2020 | 8 | 2020 |
| Outcomes of an environmental-focused, problem-solving intervention for transition-age youth: Project TEAM J Kramer, C Helfrich, A Schwartz, P Samuel, E Kolaczyk, A Goeva The American Journal of Occupational Therapy 73 (4_Supplement_1 …, 2019 | 3 | 2019 |
| Reconstructing input models in stochastic simulation A Goeva, H Lam, H Qian, B Zhang Proceedings of the 2014 Winter Simulation Conference, IEEE Press, 698-709, 2014 | 2 | 2014 |
| HiDDEN: A machine learning label refinement method for detection of disease-relevant populations in case-control single-cell transcriptomics A Goeva, MJ Dolan, J Luu, E Garcia, R Boiarsky, RM Gupta, E Macosko bioRxiv, 2023.01. 06.523013, 2023 | 1 | 2023 |
| Exploiting spatiotemporal regulation of FZD5 during neural patterning for efficient ventral midbrain specification A Yang, R Chidiac, E Russo, H Steenland, Q Pauli, R Bonin, LL Blazer, ... Development 151 (5), 2024 | | 2024 |
| Why Do We Plot Data? K Blumenthal, A Goeva, S Stoudt, A Trisovic, P Trisovic Harvard Data Science Review, 2021 | | 2021 |
| Recipes for Connector Courses From the Early-Career Board Kitchen A Goeva, P Jones, S Stoudt, A Trisovic Harvard Data Science Review, 2021 | | 2021 |
| Kaleidoscopic Perspectives on Practicum-Based Data Science Education S Frost, A Goeva, J Pombra, W Seaton, S Stoudt, A Trisovic, C Wang, ... Harvard Data Science Review 3 (1), 2021 | | 2021 |
| COVID-19 Case Fatality Rate Bias Visual Explainer A Goeva, S Stoudt PubPub, 2021 | | 2021 |
Evan MacoskoBroad Institute of MIT and HarvardVerified email at broadinstitute.org
