M. Pavlovic

BrainLine: An Open Pipeline for Connectivity Analysis of Heterogeneous Whole-Brain Fluorescence Volumes

BrainLine processes whole-brain fluorescence images through registration, segmentation, and analysis using a feedback-based training approach.

In silico proof of principle of machine learning-based antibody design at unconstrained scale

This paper demonstrates that deep generative models can design high-affinity, developable antibodies at scale using synthetic data and transfer learning.

Unconstrained generation of synthetic antibody-antigen structures to guide machine learning methodology for real-world antibody specificity prediction

The paper introduces Absolut!, a software suite generating synthetic antibody-antigen structures to benchmark machine learning methods for antibody specificity prediction.

Integrative genomic and epigenomic analyses identified IRAK1 as a novel target for chronic inflammation-driven prostate tumorigenesis

Individualized VDJ recombination predisposes the available Ig sequence space

The paper shows that VDJ recombination rules vary between individuals, leading to individual-specific Ig sequence spaces.

A compact vocabulary of paratope-epitope interactions enables predictability of antibody-antigen binding

The paper identifies a compact vocabulary of paratope-epitope interaction motifs that enables machine learning prediction of antibody-antigen binding.