DeepMind Blog

AlphaGenome: AI for better understanding the genome

Introducing a new, unifying DNA sequence model that advances regulatory variant-effect prediction and promises to shed new light on genome function — now available via API.

arXiv AI

Jul 29

DeepVRegulome: DNABERT-based deep-learning framework for predicting the functional impact of short genomic variants on the human regulome

arXiv:2511. 09026v2 Announce Type: replace-cross Abstract: Whole-genome sequencing (WGS) has revealed numerous non-coding short variants whose functional impacts remain poorly understood.

By Pratik Dutta, Matthew Obusan, Rekha Sathian, Max Chao, Pallavi Surana, Nimisha Papineni, Yanrong Ji, Zhihan Zhou, Han Liu, Alisa Yurovsky, Ramana V Davuluri

fine-tuning

arXiv Machine Learning

Jul 2

Explainable AI for Cancer Drug Response Prediction: Beyond Univariate Feature Attributions

arXiv:2607. 00931v1 Announce Type: new Abstract: Predicting cancer drug response from transcriptomic profiles is a cornerstone of precision oncology, yet the scientific value of machine learning models hinges not solely on predictive accuracy, but also on their capacity to generate reliable biological insights.

By Martino Ciaperoni, Margherita Lalli, Simone Piaggesi, Martina Varisco, Francesco Carli, Riccardo Guidotti, Dino Pedreschi, Francesco Raimondi, Fosca Giannotti

arXiv AI

Jun 16

BRIDGE: Biological Evidence Refinement and Heterogeneous Dynamic Gating for Gene Regulatory Networks

arXiv:2606. 14734v1 Announce Type: cross Abstract: Motivation: Gene regulatory network inference from single-cell RNA sequencing (scRNA-seq) data is important for uncovering cell-state-specific transcriptional programs.

By Ziyang Dong, Shanwen Tan, Hengchuang Yin, Wei Liu, Yifan Wang, Siyu Yi, Jiancheng Lv, Wei Ju

benchmarks

arXiv Machine Learning

Jun 17

Beyond Independent Genes: Learning Module-Inductive Representations for Single-Cell Gene Perturbation Prediction

arXiv:2602. 04901v2 Announce Type: replace-cross Abstract: Predicting transcriptional responses to genetic perturbations is a central problem in functional genomics.

By Jiafa Ruan, Ruijie Quan, Liyang Xu, Zongxin Yang, Yi Yang

diffusion benchmarks safety

arXiv AI

Aug 12

JEPA-DNA: Grounding Genomic Foundation Models through Joint-Embedding Predictive Architectures

arXiv:2602. 17162v3 Announce Type: replace Abstract: Genomic Foundation Models (GFMs) typically rely on Masked Language Modeling (MLM) or Next-Token Prediction (NTP) to learn the "Laws of Nature".

By Ariel Larey, Elay Dahan, Amit Bleiweiss, Raizy Kellerman, Guy Leib, Omri Nayshool, Dan Ofer, Tal Zinger, Dan Dominissini, Gideon Rechavi, Nicole Bussola, Simon Lee, Shane O'Connell, Dung Hoang, Marissa Wirth, Alexander W. Charney, Nati Daniel, Yoli Shavit

rag diffusion benchmarks safety

arXiv AI

2d ago

Program-space Diffusion for Morphology-to-Transcriptomics Prediction

arXiv:2608. 14330v1 Announce Type: new Abstract: Spatial transcriptomics (ST) enables genome-wide gene expression profiling while preserving tissue architecture, but its cost and limited scalability remain major bottlenecks.

By Ruyter Swann, Dorent Reuben, Racoceanu Daniel

diffusion

arXiv AI

Jun 3

TadA-Bench: A Million-Variant Benchmark for Future-Round Discovery Toward Agentic Protein Engineering

arXiv:2606. 02624v1 Announce Type: cross Abstract: AI for scientific discovery is entering an agentic era, where protein-engineering systems are expected to prioritize future wet-lab experiments rather than merely fit static measurements.

By Jin Gao, Juntu Zhao, Zirui Zeng, Jiaqi Shen, Junhao Shi, Dukun Zhao, Yuming Lu, Dequan Wang

agents benchmarks

arXiv AI

Jun 18

SciHorizon-GENE: Benchmarking LLM for Life Sciences Inference from Gene Knowledge to Functional Understanding

arXiv:2601. 12805v4 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown growing promise in biomedical research, particularly for knowledge-driven interpretation tasks.

By Xiaohan Huang, Meng Xiao, Chuan Qin, Qingqing Long, Jinmiao Chen, Yuanchun Zhou, Hengshu Zhu

llms benchmarks safety

arXiv AI

Jul 24

Generative Artificial Intelligence in Bioinformatics: A Systematic Review of Models, Applications, and Methodological Advances

arXiv:2511. 03354v2 Announce Type: replace-cross Abstract: Generative artificial intelligence (GenAI) is transforming bioinformatics by advancing genomics, proteomics, transcriptomics, structural biology, and drug discovery.

By Wasimul Karim, Riasad Alvi, Sayeem Been Zaman, Arefin Ittesafun Abian, Mohaimenul Azam Khan Raiaan, Saddam Mukta, Md Rafi Ur Rashid, Md Rafiqul Islam, Yakub Sebastian, Sami Azam

benchmarks safety

arXiv Machine Learning

Jun 9

Biological Reasoning-Informed Regression for Interpretable Regulatory DNA Activity Prediction

arXiv:2606. 08147v1 Announce Type: cross Abstract: DNA cis-regulatory elements (CREs) such as enhancers control gene expression levels.

By Yi Duan, Zhao Yang, Jiwei Zhu, Ying Ba, Chuan Cao, Bing Su

llms reinforcement-learning benchmarks safety

arXiv AI

Jul 7

Leveraging Natural Language Processing to Unravel the Mystery of Life: A Review of NLP Approaches in Genomics, Transcriptomics, and Proteomics

arXiv:2506. 02212v2 Announce Type: replace-cross Abstract: Natural Language Processing (NLP) has transformed various fields beyond linguistics by applying techniques originally developed for human language to the analysis of biological sequences.

By Ella Rannon, David Burstein

llms nlp

arXiv Machine Learning

Jun 25

Stable-Shift: Biologically Structured Prediction of Transcriptional Responses to Unseen Gene Perturbations

arXiv:2606. 24940v1 Announce Type: cross Abstract: Predicting transcriptional responses to genetic perturbations could reduce the experimental burden of functional genomics, but extrapolation to genes that were never perturbed during training remains difficult.

By Sajib Acharjee Dip, Liqing Zhang

benchmarks

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