Andrew Favor

De novo design of RNA pseudoknots with deep learning

This paper demonstrates that deep learning can accurately design RNA pseudoknots, achieving results comparable to human experts in a competition.

Fast remote nucleotide sequence alignment with Riboseek

Riboseek is a fast and sensitive sequence alignment tool for RNA and DNA that uses di-mers for alignment, outperforming BLASTN and nhmmer in speed and sensitivity.

Template-based RNA structure prediction advanced through a blind code competition

The paper describes a Kaggle competition for RNA 3D structure prediction, showing that template-based methods can outperform deep learning approaches.

Geometric Tuning of Cytokine Receptor Association Modulates Synthetic Agonist Signaling

This paper designs synthetic cytokine agonists with controlled receptor geometry to modulate signaling outcomes and functional effects.

RNA sequence design and protein-DNA specificity prediction with NA-MPNN

This paper introduces NA-MPNN, a unified deep learning model for nucleic acid inverse folding, which outperforms existing methods in RNA sequence design and protein-DNA specificity prediction.

De novo design of RNA and nucleoprotein complexes

This paper introduces a generative diffusion model for de novo design of RNA and nucleoprotein complexes, validated experimentally with SHAPE-seq and electron microscopy.

Accelerating Biomolecular Modeling with AtomWorks andRF3

AtomWorks, a modular atom-level data framework, trains structure prediction and design models; the resulting RF3 improves chirality handling and performs between AF3 and Boltz.

Bond-centric modular design of protein assemblies

The paper introduces a modular bond-centric design approach for protein assemblies, demonstrating the successful creation of multiple polyhedral cages, 2D arrays, and 3D lattices with high success rates.

Designed NGF mimetics with reduced nociceptive signatures in neurons

The paper designs TrkA agonists that activate neuronal differentiation and neurite outgrowth without triggering pain-related gene expression.

Accurate Computational Design of 3D Protein Crystals

This paper designs 3D protein crystals with specified lattice architectures using computational methods, achieving atomic accuracy and demonstrating successful experimental validation.