Alexandr A. Kalinin

The paper presents a comprehensive genetic perturbation dataset using Cell Painting to analyze gene expression effects in human cells, revealing novel gene clusters and functional relationships.

The paper introduces a statistical framework using mean average precision (mAP) to evaluate phenotypic activity and consistency in high-dimensional profiling data across various modalities and perturbation types.

The paper introduces a dataset of cell morphology images treated with matched chemical and genetic perturbations and evaluates methods for identifying perturbation similarities.

This study quantifies 4D nuclear morphology changes in human astrocytes treated with valproic acid, showing significant size and shape differences by day 7.

The paper develops a 3D morphometric analysis pipeline for cell nuclei and nucleoli, achieving high classification accuracy in prostate cancer and fibroblast cells.

The paper compares nuclear structure classification methods using 2D microscopy data from a 3D dataset, evaluating classification algorithms on raw intensity images and binary masks.

This paper presents a deep learning approach for automatic segmentation of robotic instruments in surgery videos, achieving state-of-the-art results for both binary and multi-class segmentation tasks.

This paper develops a deep learning approach for automated pediatric bone age assessment using radiological hand images and shows it outperforms existing methods.

The paper introduces a 3D cell nuclear morphology dataset and evaluates classification algorithms using voxel-based morphometric measures.

This paper develops deep convolutional neural networks for detecting and localizing angiodysplasia lesions in gastrointestinal images, achieving state-of-the-art results.

This paper develops a deep convolutional neural network approach for breast cancer histology image classification, achieving high accuracy in both 4-class and 2-class tasks.

Deep learning rivals or beats baselines across imaging, health records, genomics and drug discovery but is not yet transformative; scarce labels, privacy and opacity remain hurdles.

The paper observes rotational 3D mechanogenomic Turing patterns in Caco-2 cells during differentiation, suggesting a link between actomyosin dynamics and gene morphogen-driven morphogenesis.