3 papers
q-bio.GN2026
Parameter-free representations outperform single-cell foundation models on downstream benchmarks
Huan Souza, Pankaj Mehta
Single-cell RNA sequencing (scRNA-seq) data exhibit strong and reproducible statistical structure. This has motivated the development of large-scale foundation models, such as Tran…
q-bio.GN2025
Inferring genotype-phenotype maps using attention models
Krishna Rijal, Caroline M. Holmes, Samantha Petti +3
Predicting phenotype from genotype is a central challenge in genetics. Traditional approaches in quantitative genetics typically analyze this problem using methods based on linear…
physics.bio-ph2025
A differentiable Gillespie algorithm for simulating chemical kinetics, parameter estimation, and designing synthetic biological circuits
Krishna Rijal, Pankaj Mehta
The Gillespie algorithm is commonly used to simulate and analyze complex chemical reaction networks. Here, we leverage recent breakthroughs in deep learning to develop a fully diff…