Darya Yu. Orlova

This study evaluates ML and biophysical models for predicting TCR-pMHC specificity, showing ML struggles with novel peptides while biophysical methods excel but underperform on known ones, leading to a hybrid model with improved performance.

This paper develops a method to quantify immunohistochemistry antigen concentrations and reaction-diffusion parameters, enabling more rigorous interpretation of IHC results.

The paper introduces Incytr, a method for discovering cell signaling pathways from multi-omics data, demonstrating its application in disease contexts and showing its utility for drug discovery and understanding cell communication.

SPEX provides a web-based platform for spatial omics analysis, enabling modular and user-friendly processing of spatial transcriptomics and proteomics data.

The paper introduces APP, a clustering method that reduces high-dimensional biological data to lower dimensions to improve clustering performance across multiple data types.

This paper evaluates machine learning approaches for predicting T-cell receptor specificity, highlighting limitations in current data and methods, and proposes a new framework integrating biophysical measurements.