Martin Culka

Predicting specificity of TCR-pMHC interactions using machine learning and biophysical models

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.

Lifting the curse from high dimensional data: Automated projection pursuit clustering for the variety of biological data modalities

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

Tricked by Edge Cases: Can Current Approaches Lead to Accurate Prediction of T-Cell Specificity with Machine Learning?

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.

Dinucleoside polyphosphates act as 5'-RNA caps in Escherichia coli

This study shows that dinucleoside polyphosphates function as RNA caps in E. coli, influencing RNA stability and metabolism through incorporation into RNA.