David Van Valen, Ph.D.
Affiliations: | 2011 | Applied Physics | California Institute of Technology, Pasadena, CA |
Area:
General Physics, General BiophysicsGoogle:
"David Van Valen"Mean distance: (not calculated yet)
Parents
Sign in to add mentor| Robert B. Phillips | grad student | 2011 | Caltech | |
| (Case studies in quantitative biology: Biochemistry on a leash and a single-molecule Hershey-Chase experiment.) | ||||
| Markus Willard Covert | post-doc | UCSD (Computational Biology Tree) | ||
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Publications
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| Ma J, Xie R, Ayyadhury S, et al. (2024) The multimodality cell segmentation challenge: toward universal solutions. Nature Methods |
| Israel U, Marks M, Dilip R, et al. (2023) A Foundation Model for Cell Segmentation. Biorxiv : the Preprint Server For Biology |
| Laubscher E, Wang XJ, Razin N, et al. (2023) Accurate single-molecule spot detection for image-based spatial transcriptomics with weakly supervised deep learning. Biorxiv : the Preprint Server For Biology |
| Schwartz M, Israel U, Wang XJ, et al. (2023) Scaling biological discovery at the interface of deep learning and cellular imaging. Nature Methods. 20: 956-957 |
| Andrews B, Chang JB, Collinson L, et al. (2022) Imaging cell biology. Nature Cell Biology |
| Greenwald NF, Miller G, Moen E, et al. (2021) Whole-cell segmentation of tissue images with human-level performance using large-scale data annotation and deep learning. Nature Biotechnology |
| Bannon D, Moen E, Schwartz M, et al. (2021) Publisher Correction: DeepCell Kiosk: scaling deep learning-enabled cellular image analysis with Kubernetes. Nature Methods |
| Bannon D, Moen E, Schwartz M, et al. (2021) DeepCell Kiosk: scaling deep learning-enabled cellular image analysis with Kubernetes. Nature Methods |
| Moen E, Bannon D, Kudo T, et al. (2019) Deep learning for cellular image analysis. Nature Methods |
| Lane K, Van Valen D, DeFelice MM, et al. (2017) Measuring Signaling and RNA-Seq in the Same Cell Links Gene Expression to Dynamic Patterns of NF-κB Activation. Cell Systems |