Chirag Lakhani

Functional Genomics

Chromatin Accessibility

1. A meta-analysis of chromatin-associated loci provides insights into mechanistic interpretations of trait heritability

   Max F. Dudek, Brandon M. Wenz, Benjamin F. Voight, Laura Almasy, Struan F.A. Grant

   bioRxiv, 2026

   Link


2. Distinguishing causal from tagging enhancers using single-cell multiome data

   Elizabeth Dorans, Alkes L. Price

   medRxiv, 2026

   Link

Genomic Deep Learning

Model Interpretation

1. Uncovering the Mechanistic Landscape of Regulatory DNA with Deep Learning

   Evan E. Seitz, David M. McCandlish, Justin B. Kinney, Peter K Koo

   bioRxiv, 2025

   Link


2. When Less Is Enough: Low-Rank Structure in DNA Sequence-to-Function Models

   Elizabeth Gilfeather, Maria Chikina, Dennis Kostka

   bioRxiv, 2026

   Link

Self-Supervised Learning

1. Predicting functional constraints across evolutionary timescales with phylogeny-informed genomic language models

   Chengzhong Ye, Gonzalo Benegas, Carlos Albors, Jianan Canal Li, Sebastian Prillo, Peter D. Fields, Brian Clarke, Yun S. Song

   bioRxiv, 2025

   Link

Sequence to Function Modeling

1. Sequence-based modeling of low-affinity transcription factor–DNA binding through deep learning

   Yingfei Wang, Jinsen Li, Tsu-Pei Chiu, Beibei Xin, Remo Rohs

   NAR Genomics and Bioinformatics, 2026

   Link

Statistical Genetics

Fine-Mapping

1. Genome-wide fine-mapping improves identification of causal variants

   Yang Wu, Zhili Zheng, Loic Thibaut, Tian Lin, Qian Feng, Hao Cheng, Loic Yengo, Michael E. Goddard, Naomi R. Wray, Peter M. Visscher, Jian Zeng

   Nature Genetics, 2026

   Link

Variant Modeling

1. Training Flexible Models of Genetic Variant Effects from Functional Annotations using Accelerated Linear Algebra

   Alan N. Amin, Andres Potapczynski, Andrew Gordon Wilson

   2025

   Link