SANE is a new schema-aware benchmark paradigm for text-to-SQL evaluation that demonstrates few-shot LLMs with structured prompting can generate accurate queries on constrained biological data schemas without fine-tuning.
CellProfiler: image analysis software for identifying and quantifying cell phenotypes
4 Pith papers cite this work, alongside 5,483 external citations. Polarity classification is still indexing.
4
Pith papers citing it
5,483
external citations · Crossref
citation-role summary
background 1
citation-polarity summary
roles
background 1polarities
background 1representative citing papers
DiffEx builds a classifier-aware latent space with a diffusion model, finds contrastive directions in it, and ranks them to produce visual explanations that reveal cellular phenotype changes.
A branched StarDist architecture with a within-boundary penalty segments nested biomedical objects such as nuclei in cells and plaques in wells in one shot, with a new joint true-positive metric.
citing papers explorer
-
SANE Schema-aware Natural-language Evaluation of Biological Data
SANE is a new schema-aware benchmark paradigm for text-to-SQL evaluation that demonstrates few-shot LLMs with structured prompting can generate accurate queries on constrained biological data schemas without fine-tuning.
-
DiffEx: Explaining a Classifier with Diffusion Models to Identify Microscopic Cellular Variations
DiffEx builds a classifier-aware latent space with a diffusion model, finds contrastive directions in it, and ranks them to produce visual explanations that reveal cellular phenotype changes.
-
Single-shot Star-convex Polygon-based Instance Segmentation for Spatially-correlated Biomedical Objects
A branched StarDist architecture with a within-boundary penalty segments nested biomedical objects such as nuclei in cells and plaques in wells in one shot, with a new joint true-positive metric.
- Using Deep Learning Models Pretrained by Self-Supervised Learning for Protein Localization