Learning Diffusion Models with Flexible Representation Guidance (Contributed Talk) Chenyu Wang, Cai Zhou, Sharut Gupta, Zongyu Lin, Stefanie Jegelka, Stephen Bates, Tommi Jaakkola

NextGenPLM: A Novel Structure-Infused Foundational Protein Language Model for Antibody Discovery and Optimization (Contributed Talk) Abhinav Gupta, Ruijiang Li, Camila Leal, Madhumati Sevvana, Brian C Mackness, Ryan G Casner, Joseph D Batchelor, Anna Park, Michael Bailey, Lorenzo Kogler Anele, Sven Jager, Maria Wendt, Yves Fomekong Nanfack, Norbert Furtmann, Yu Qiu

Towards functional annotation with latent protein language model features (Contributed Talk) Jake Silberg, Elana Simon, James Zou

3D-SBDD meets LLM: Towards FDA-Level Drug Design Bowen Gao, Yanwen Huang, Yiqiao Liu, Wenxuan Xie, Bowei He, Haichuan Tan, Wei-Ying Ma, Ya-Qin Zhang, Yanyan Lan

A Foundation Model for Mass Spectrometry Proteomics Justin Sanders, Melih Yilmaz, Jacob H. Russell, William E Fondrie, Wout Bittremieux, Nicholas M. Riley, Sewoong Oh, William Noble

A Genomic Language Model for Zero-Shot Prediction of Promoter Indel Effects Courtney A. Shearer, Felix Teufel, Rose Orenbuch, Christian J. Steinmetz, Daniel Ritter, Erik Xie, Artem Gazizov, Aviv Spinner, Jonathan Frazer, Mafalda Dias, Pascal Notin, Debora Susan Marks

A Look at the Isotropy of Pretrained Protein Language Models Sheikh Azizul Hakim, Kowshic Roy, M Saifur Rahman

A Multi-Modal Large Language Model for Free-Form, Open-Ended, and Interactive Prediction of Properties and Mechanisms of Candidate Drug Molecules Youwei Liang, Ruiyi Zhang, Zinnia Ma, Digvijay Singh, Yongce Li, Mingjia Huo, Chengzhan Gao, Hamidreza Rahmani, Satvik Bandi, Li Zhang, Robert Weinreb, Atul Malhotra, Danielle A. Grotjahn, Linda Awdishu, Trey Ideker, Michael K Gilson, Pengtao Xie

AIDO.Tissue: Spatial Cell-Guided Pretraining for Scalable Spatial Transcriptomics Foundation Model Jing Gong, Yixuan Wang, Nicholas Ho, Xingyi Cheng, Le Song, Eric P. Xing

Advancing Knotted Protein Design with ESM3: Guided Generation and Topological Insights Petr Simecek, Eva Klimentová

AnnoDPO: Protein Functional Annotation Learning with Direct Preference Optimization Zixuan Jiang, Renjing Xu

ATOMICA: Learning Universal Representations of Intermolecular Interactions Ada Fang, Zaixi Zhang, Andrew Zhou, Marinka Zitnik

Benchmarking Vision-Language Contrastive Methods for Medical Representation Learning Shuvendu Roy, Yasaman Parhizkar, Franklin Ogidi, Vahid Reza Khazaie, Michael Colacci, Ali Etemad, Elham Dolatabadi, Arash Afkanpour

BioLangFusion: Multimodal Fusion of DNA, mRNA, and Protein Language Models Amina Mollaysa, Artem Moskalev, Pushpak Pati, Tommaso Mansi, Mangal Prakash, Rui Liao

Cell-Type-Aware Pooling for Robust Sample Classification in Single-Cell RNA-seq Data Soorin Yim, Kyungwook Lee, Dongyun Kim, Sungjoon Park, Doyeong Hwang, Soonyoung Lee, Amy Dunn, Daniel Gatti, Elissa Chesler, Kristen O’Connell, Kiyoung Kim

Challenges and Guidelines in Deep Generative Protein Design: Four Case Studies Tianyuan Zheng, Alessandro Rondina, Gos Micklem, Pietro Lio

Closing the gap between the biology and the clinic with a foundation model of immunology and inflammation Aziz Fouché, Apolline Bruley, Matthew Corney, Pierre Marschall, Vincent Bouget, Julien Duquesne

Conditional Normalizing Flows for the Design of T Cell Therapies Samarth Kadaba, Alexander K Eapen, Kristin C. Y. Tsui, Kuan Pang, Theodore L Roth, Zinaida Good

DeepSeq: High-Throughput Single-Cell RNA Sequencing Data Labeling via Web Search-Augmented Agentic Generative AI Foundation Models Saleem Abdul Fattah Ahmed Al Dajani, Abel Sanchez, John R Williams

Describe Anything in Medical Images Xi Xiao, Yunbei Zhang, Thanh-Huy Nguyen, Ba-Thinh Lam, Janet Wang, Lin Zhao, Jihun Hamm, Tianyang Wang, Xingjian Li, Xiao Wang, Hao Xu, Tianming Liu, Min Xu

DisProtEdit: Exploring Disentangled Representations for Multi-Attribute Protein Editing Max Ku, Sun Sun, Hongyu Guo, Wenhu Chen

Enriched Instruction-Following Graph Alignment for Efficient Medical Vision-Language Models Duy Minh Ho Nguyen, Nghiem Tuong Diep, Trung Quoc Nguyen, Hoang-Bao Le, Tai Nguyen, Anh-Tien Nguyen, TrungTin Nguyen, Nhat Ho, Pengtao Xie, Roger Wattenhofer, Daniel Sonntag, James Zou, Mathias Niepert

Evaluating Multi-Modal Models for Enzyme-Reaction Retrieval Annika Viswesh, Jason Yang, Frances H. Arnold, Yisong Yue

From Vision to Graph Self-Supervised Learning in Digital Pathology Sevda Öğüt, Carlos Hurtado, Cédric Vincent-Cuaz, Natalia Dubljevic, Vaishnavi Subramanian, Dorina Thanou, Pascal Frossard

GeneChat: A Multi-Modal Large Language Model for Gene Function Prediction Shashi Dhanasekar, Pengtao Xie, Akash Saranathan

H&Enium, Applying Foundation Models to Computational Pathology and Spatial Transcriptomics to Learn an Aligned Latent Space Marc Glettig, Tim Ehrensperger, Josephine Yates, Valentina Boeva

HPP-Voice: A Large-Scale Evaluation of Speech Embeddings for Multi-Phenotypic Classification David Krongauz, Hido Pinto, Sarah Kohn, Yanir Marmor, Eran Segal

Ibex: Pan-immunoglobulin structure prediction Frederic A Dreyer, Karolis Martinkus, Jan Ludwiczak, Brennan Abanades, Robert G Alberstein, Pranav Rao, Jae Hyeon Lee, Richard Bonneau, Andrew Martin Watkins, Franziska Seeger

Integrating Pathology Foundation Models and Spatial Transcriptomics for Cellular Decomposition from Histology Images Yutong Sun, Sichen Zhu, Peng Qiu

Joint Diffusion Sampling via Positive-Unlabeled Guidance for Multi-Modal Data Matt Raymond, Yilun Zhu, Jianxin Zhang, Angela Violi, Clayton Scott

KD-CPT: A Knowledge-Driven Cellular Phenotypic Transdifferentiation Model Lei Xin, Zhenglun Kong, Xiaoshuo Yan, Sijia Yan, Zeheng Wang, Wuzhe Fan, Hao Tang

Knowledge Graph-Augmented DNA Representation Learning Fengyu Cai, Erik Kubaczka, Shaobo Cui, Heinz Koeppl

Leveraging the Structure of Medical Data for Improved Representation Learning Andrea Agostini, Sonia Laguna, Alain Ryser, Samuel Ruiperez-Campillo, Moritz Vandenhirtz, Nicolas Deperrois, Farhad Nooralahzadeh, Michael Krauthammer, Thomas M. Sutter, Julia E Vogt

Ligand Iterative Sampling for Affinity Refinement and Drug Discovery (LISARDD) Valentin BADEA, Shyam Chandra, John Lin

MiST: Understanding the Role of Mid-Stage Scientific Training in Developing Chemical Reasoning Models Andres M Bran, Tong Xie, Shai Pranesh, Jeremy Goumaz, Xuan Vu Nguyen, David Ming Segura, Ruizhi Xu, Jeffrey Meng, Dongzhan Zhou, Wenjie Zhang, Philippe Schwaller

Molecularly informed analysis of histopathology images using natural language Moritz Schaefer, Kalin Nonchev, Animesh Awasthi, Jake Burton, Viktor Koelzer, Gunnar Ratsch, Christoph Bock

Multi-Modal Interpretable Graph for Competing Risk Prediction with Electronic Health Records Munib Mesinovic, Peter Watkinson, Tingting Zhu

Multi-Modal Large Language Model Enables Protein Function Prediction Han Guo, Mingjia Huo, Xingyi Cheng, Digvijay Singh, Hamidreza Rahmani, Shen Li, Philipp Gerlof, Trey Ideker, Danielle Grotjahn, Elizabeth Villa, Le Song, Pengtao Xie

Multi-Modal Medical Image Augmentation for Controlled Heterogeneity and Fair Outcomes Soo Yong Kim, Seunghyeok Hong

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Tong Chen, Yinuo Zhang, Sophia Tang, Pranam Chatterjee

Multi-Objective-Guided Generative Design of mRNA with Therapeutic Properties Sawan Patel, Sophia Tang, Yinuo Zhang, Pranam Chatterjee, Sherwood Yao

Multimillion cell self-supervised representation learning enables organ-scale tissue niche discovery Alex Jihun Lee, Alma Dubuc, Michael Kunst, Shenqin Yao, Nicholas Lusk, Lydia Ng, Hongkui Zeng, Bosiljka Tasic, Reza Abbasi-Asl

Multimodal Benchmarking of Foundation Model Representations for Cellular Perturbation Response Prediction Euxhen Hasanaj, Elijah Cole, Shahin Mohammadi, Sohan Addagudi, Xingyi Zhang, Le Song, Eric P. Xing

Multimodal Modeling of CRISPR-Cas12 Activity Using Foundation Models and Chromatin Accessibility Data Azim Dehghani Amirabad, Yanfei Zhang, Artem Moskalev, Sowmya Rajesh, Tommaso Mansi, Shuwei Li, Mangal Prakash, Rui Liao

Multimodal Protein Language Models for Flexibility Prediction and Loop Design Tyler Verhaar, Samuel W. K. Wong

PM1: A Foundation Model Fusing Genotype, Phenotype, and Image for Precision Medicine Margarita Geleta, Christophe Thomassin, Marçal Comajoan Cara, David Bonet, Aina Luis Vidal, Benet Oriol Sabat, Daniel Mas Montserrat, Alexander G. Ioannidis

Promoter Sequence Generation using Homology Prompting Erik Xie, Courtney A. Shearer, Ruben Weitzman, Pascal Notin, Debora Susan Marks

ProteinAligner: A Tri-Modal Contrastive Learning Framework for Protein Representation Learning Li Zhang, Han Guo, Leah Schaffer, Young Su Ko, Digvijay Singh, Danielle Grotjahn, Elizabeth Villa, Michael K Gilson, Wei Wang, Trey Ideker, Eric P. Xing, Pengtao Xie

ProteinGPT: Multimodal LLM for Protein Property Prediction and Structure Understanding Yijia Xiao, Edward Sun, Yiqiao Jin, Qifan Wang, Wei Wang

Rapid and Reproducible Multimodal Biological Foundation Model Development with AIDO.ModelGenerator Caleb Ellington, Dian Li, Shuxian Zou, Elijah Cole, Ning Sun, Sohan Addagudi, Le Song, Eric P. Xing

RepoLLM: A Multi-modal Foundation Model for Drug Repurposing via Alignment of Molecules, EHRs, and Knowledge Graphs Zichao Li, Zong Ke

Retrieval Augmented Protein Language Models for Protein Structure Prediction Pan Li, Xingyi Cheng, Le Song, Eric P. Xing

Robust Multi-Omics Integration from Incomplete Modalities Significantly Improves Prediction of Alzheimer’s Disease Sungjoon Park, Kyungwook Lee, Soorin Yim, Doyeong Hwang, Dongyun Kim, Soonyoung Lee, Amy Dunn, Daniel Gatti, Elissa Chesler, Kristen O'Connell, Kiyoung Kim

Scaling up measurement noise scaling laws Igor Sadalski, Dan Raviv, Jonathan S Rosenfeld, Allon M Klein, Gokul Gowri

Segmentation Helps Understanding: Mask-Infused Vision-Language Pre-training for 3D Medical Images Yuqi Hu, Xufang Luo, Zilong Wang, Dongsheng Li, Lili Qiu

Self-Supervised Representation Learning for Microbiome Improves Downstream Prediction in Data-Limited Settings and Cross-Cohort Generalizability Liron Zahavi, Zachary Levine, Eran Segal

SHIVER: Somatic Hypermutation Informed Vocabulary Encoder Representations Chiho Im, Artem Mikelov, Ryan Zhao, Anshul Kundaje, Scott D. Boyd

SOAPIA: Siamese-Guided Generation of Off Target-Avoiding Protein Interactions with High Target Affinity Sophia Vincoff, Oscar Davis, Ismail Ilkan Ceylan, Alexander Tong, Joey Bose, Pranam Chatterjee

Stabilizing protein fitness predictors via the PCS framework Omer Ronen, Alex Y. Zhao, Ron Boger, Chengzhong Ye, Bin Yu

SYNAPSE: A Multi-Modal Framework for Interpretable Neural Decoding Using Vision-Language Foundation Models Edward Ju, Adarsh Kumarappan, Shrujana S Kunnam, Raaghav Malik, Dhruv Sheth

TICA-Based Free Energy Matching for Machine-Learned Molecular Dynamics Alexander Aghili, Andy Bruce, Daniel Sabo, Razvan Marinescu

Temporal Representation Learning for Ultrasound Analysis using Masked Modeling Yves Dominic Stebler, Thomas M. Sutter, Ece Ozkan, Julia E Vogt

Towards foundation models that learn across biological scales Jeremie Kalfon, Laura Cantini, Gabriel Peyré

Towards Molecular Conformer Generation with Language Models Menua Bedrosian, Hrant Khachatrian

Transfer Learning of Condition-Specific Perturbation in Gene Interactions: Towards Multi-modal Foundational Modeling of Drug Response Dongmin Bang, Bonil Koo, Sun Kim

Transferring Cell-level Drug Response to Patient via Tumor Heterogeneity-Aware Alignment and Gene-level Foundational Models Inyoung Sung, Dongmin Bang, Sun Kim, Sangseon Lee

TRIDENT: Tri-Modal Molecular Representation Learning with Taxonomic Annotations and Local Correspondence Feng Jiang, Mangal Prakash, Hehuan Ma, Jianyuan Deng, Yuzhi Guo, Amina Mollaysa, Tommaso Mansi, Rui Liao, Junzhou Huang

Unified Representation of Genomic and Biomedical Concepts through Multi-Task, Multi-Source Contrastive Learning Hongyi Yuan, Suqi Liu, Zongxin Yang, Kelly Cho, Katherine P. Liao, Alexandre Pereira, Tianxi Cai

Uncertainty-Aware Discrete Diffusion Improves Protein Design Sazan Mahbub, Christoph Feinauer, Caleb Ellington, Le Song, Eric P. Xing