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ORCID20th MLCB 2025, New York, NY, USA
- David A. Knowles, Peter K. Koo:
Proceedings of the 20th Machine Learning in Computational Biology (MLCB), 10-11 September 2025, New York, NY, USA. Proceedings of Machine Learning Research 311, PMLR 2025 - Minsheng Hao, Nan Yan, Haiyang Bian, Yixin Chen, Jin Gu, Lei Wei, Xuegong Zhang:
GeST: Towards Building A Generative Pretrained Transformer for Learning Cellular Spatial Context. 1-11 - Tapanmitra Ravi, Irene M. Ong:
TCR-ECHO: Evolutionary Cross-attention with Physicochemical Bias for Hierarchical TCR-Peptide Binding Prediction. 12-27 - Mu Qiao:
Unsupervised Evolutionary Cell Type Matching via Entropy-Minimized Optimal Transport. 28-43 - Minsheng Hao, Yongju Lee, Hanchen Wang, Gabriele Scalia, Aviv Regev:
PerTurboAgent: An LLM-based Agent for Designing Iterative Perturb-Seq Experiments. 44-64 - Kevin Lam, William Daniels, J. Maxwell Douglas, Daniel Lai, Samuel Aparicio, Benjamin Bloem-Reddy, Yongjin Park:
CN-SBM: Categorical Block Modelling For Primary and Residual Copy Number Variation. 65-80 - Viktoria Schuster:
Can sparse autoencoders make sense of gene expression latent variable models? 81-94 - Courtney Shearer, Rose Orenbuch, Felix Teufel, Christian Steinmetz, Daniel Ritter, Erik Xie, Artem Gazizov, Aviv Spinner, Mafalda Dias, Jonathan Frazer, Pascal Notin, Debora S. Marks:
A Genomic Language Model for Zero-Shot Prediction of Promoter Indel Effects. 95-127 - Caterina Fuses, Georgia Zavou, Berta Ros, Josep M. Canals, Jordi Abante:
Context-Dependent Genetic Modifiers of Huntington’s Disease Revealed Through Multimodal Machine Learning. 128-147 - Thomas Walton, Darin Tsui, Amirali Aghazadeh, Raquel Lieberman, Lauren Fogel, Rafael Chagas, Dustin Huard:
GOLF: A Generative AI Framework for Pathogenicity Prediction of Myocilin OLF Variants. 148-161 - Arushi Gupta, Alan M. Moses, Alex Lu:
Representation Learning Methods for Single-Cell Microscopy are Confounded by Background Cells. 162-177 - Shreyan Ganguly, Zhanhong Jiang, Nyzil Massey, Nikhil Sanjay Rao, Thimmasettappa Thippeswamy, Soumik Sarkar:
Automated Seizure Detection in Animal EEG Signals. 178-188 - Maryam Haghani, Krishna Vamsi Dhulipalla, Song Li:
Harnessing DNA Foundation Models for Cross-Species Transcription Factor Binding Site Prediction in Plant Genomes. 189-198 - Shubham Chaudhary, Almut Voigts, Sergey Vilov, Matthias Heinig, Francesco Paolo Casale:
AI-based histopathology phenotyping reveals germline loci shaping breast cancer morphology. 199-212 - Neda Shokraneh Kenari, Maxwell W. Libbrecht:
Variational Graph Auto-encoder for Denoising Single-cell Hi-C Data. 213-229 - Antoine de Mathelin, Christopher Tosh, Wesley Tansey:
Addressing the Cold-Start Problem for Personalized Combination Drug Screening. 230-239 - Chiho Im, Artem Mikelov, Ryan Zhao, Anshul Kundaje, Scott D. Boyd:
Somatic Hypermutation Informed Vocabulary Encoder Representations. 240-250 - Pengfei Zhang, Sonal Prabhu, Gloria Grama, Seojin Bang, Heewook Lee:
Self-Contemplating In-Context Learning Enhances T Cell Receptor Generation for Novel Epitopes. 251-269 - Gizem Cicekli, Adrita Samanta, Hao Zhu, Donna Slonim:
BIRDccNEST: Interpretable single cell characterization with inferred directed cell networks. 270-279 - Jacob Silberg, Elana Simon, James Zou:
Towards functional annotation with latent protein language model features. 280-293 - Nimisha Papineni, Pratik Dutta, Max Chao, Orbin Acanto, Rekha Sathian, Pallavi Surana, Ramana V. Davuluri:
Augmenting DNABERT Embeddings with Multimodal DNA Features for Improved Regulatory Sequence Interpretation. 294-303 - Sergio E. Mares, Ariel Espinoza Weinberger, Nilah M. Ioannidis:
Continued domain-specific pre-training of protein language models for pMHC-I binding prediction. 304-325 - Ofir Yaish, Yaron Orenstein:
F-MoDA: Efficient Fourier-based motif discovery in attribution maps. 326-335 - João F. Rocha, Ke Xu, Xingzhi Sun, Ananya Krishna, Dhananjay Bhaskar, Blanche Mongeon, Morgan Craig, Mark Gerstein, Smita Krishnaswamy:
STAGED: A Multi-Agent Neural Network for Learning Cellular Interaction Dynamics. 336-346
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