Genomic language models: opportunities and challenges

G Benegas, C Ye, C Albors, JC Li, YS Song - Trends in Genetics, 2025 - cell.com
Large language models (LLMs) are having transformative impacts across a wide range of
scientific fields, particularly in the biomedical sciences. Just as the goal of natural language …

regLM: Designing realistic regulatory DNA with autoregressive language models

A Lal, D Garfield, T Biancalani, G Eraslan - International Conference on …, 2024 - Springer
We present regLM, a framework to design synthetic CREs with desired properties, such as
high, low or cell type-specific activity, using autoregressive language models in conjunction …

gReLU: A comprehensive framework for DNA sequence modeling and design

A Lal, L Gunsalus, S Nair, T Biancalani, G Eraslan - bioRxiv, 2024 - biorxiv.org
Deep learning models are increasingly being used to perform a variety of tasks on DNA
sequences, such as predicting tissue-and cell type-specific sequence activity, deriving cis …

[CS582Reading Assignment 1-1] Genomic Language Models: Opportunities and Challenges

G Liu - CS582 ML for bioinformatics workshop, 2024 - openreview.net
arXiv:2407.11435v1 [q-bio.GN] 16 Jul 2024 Page 1 Genomic Language Models: Opportunities
and Challenges Gonzalo Benegas1,∗, Chengzhong Ye2,∗, Carlos Albors1,∗, Jianan Canal …