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Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.
8 papers
Recent·Most cited
A. Brookhouse, Y. Ji, J. Knoblauch, P. Gaburak, B. M. Wager, Z. Lin, H.-H. Kunz, A. M. Gebremedhin, H. Pfister, W. S. Peters, D. Wei, M. Knoblauch
The paper develops an AI tool for quantifying ultrastructural traits from 3D microscopic datasets and improves fixation protocols for plants.
bioRxiv · May 6, 2024 · PreprintCell Biology
S. Warchol, J. Troidl, J. L. Muhlich, R. Krueger, J. Hoffer, T. Lin, J. Beyer, E. Glassman, P. K. Sorger, H. Pfister
psudo is an interactive system that optimizes pseudocolor palettes for multichannel biomedical images to enhance perceptual distinction and reduce color confusion in overlapping channels.
bioRxiv · Apr 11, 2024Cell Biology
G. Gaglia, M. Burger, C. C. Ritch, D. Rammos, Y. Dai, G. E. Crossland, S. Z. Tavana, S. Warchol, A. M. Jaeger, S. Naranjo, S. Coy, A. Johnson, R. Krueger, J.-R. Lin, H. Pfister, , S. Santagata
The paper maps lymphocyte interactions in lung adenocarcinoma using spatial analysis and machine learning, revealing dynamic lymphocyte networks that support anti-tumor immune responses.
bioRxiv · Aug 11, 2022Cancer Biology
S. Warchol, R. Krueger, A. J. Nirmal, G. Gaglia, J. Jessup, C. C. Ritch, J. Hoffer, J. L. Muhlich, M. Burger, T. L. Jacks, S. Santagata, P. K. Sorger, H. Pfister
Visinity analyzes spatial cell interactions in multiplexed tissue images to identify biological processes and immune-tumor interactions.
bioRxiv · May 9, 2022Cell Biology
T. Rademacher, B. Seyednasrollah, D. Basler, J. Cheng, T. Mandra, E. Miller, Z. Lin, D. A. Orwig, N. Pederson, H. Pfister, D. Wei, L. Yao, A. D. Richardson
The paper introduces WIAD, an open-source tool for visual analysis of wood images to improve transparency and reproducibility in ecological studies.
bioRxiv · Dec 16, 2020Plant Biology
R. Rashid, Y.-A. Chen, J. Hoffer, J. L. Muhlich, J.-R. Lin, R. Krueger, H. Pfister, R. Mitchell, S. Santagata, P. Sorger
The paper discusses the need for interactive guides to help interpret complex tissue atlas data and digital pathology images, using Minerva software as an example.
bioRxiv · Mar 27, 2020 · PreprintScientific Communication & Education
S. A. Magid, W.-D. Jang, D. Schapiro, D. Wei, J. Tompkin, P. K. Sorger, H. Pfister
This paper introduces a channel embedding method for interpreting highly multiplexed biomedical images, demonstrating its effectiveness on synthetic data and breast cancer cell images.
bioRxiv · Mar 24, 2020 · PreprintPathology
A. Gilson, N. Durfee, R. Razban, H. Strobelt, K. Dinkla, J.-M. Choi, H. Pfister, E. Shakhnovich
ProteomeVis explores protein evolution across S. cerevisiae and E. coli proteomes by analyzing structure, sequence, and organismal properties.
bioRxiv · Dec 28, 2017Evolutionary Biology