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AI for the immune system — antibodies, TCR/BCR, and immune interactions.
8 papers in this topic (ICML 2026).
Stephen Zhewen Lu, Aakarsh Vermani, Kohei Sanno, Jiarui Lu +3
Common deep learning approaches for antibody engineering focus on modeling the marginal distribution of sequences. By treating sequences as independent samples, however, these…
Paul Collart, Juergen Gall, Andrea Schnepf, Holger Pagel +1
Soil microorganisms control organic matter cycling and largely determine how soil systems can cope with and mitigate climate change and environmental threats. Representing…
Boqiao Lai, Melissa Englund, Ramit Bharanikumar, Isabel Nocedal +3
Modeling recognition between T-cell receptors (TCRs) and peptide-MHC (pMHC) complexes is a fundamental challenge in computational immunology, constrained by sparse paired…
Haoyang Luan, Gufeng Yu, Letian Chen, Zhenran Xiao +3
The *de novo* generation of high-affinity epitopes tailored to specific major histocompatibility complex (MHC) proteins is a pivotal challenge in computational immunotherapy.…
Jeonghyeon Kim, Nathaniel Blalock, Ameya Kulkarni, Kensuke Nakamura +1
Antibodies originate from germline templates and are diversified by somatic hypermutation, producing sequences in which conserved germline residues scaffold structure while rare…
Yang Song, Yixuan Zhang, Lingfa Meng, Tongyuan Hu +4
Parameter-efficient adaptation has made LLMs practical for domain prediction, but standard LoRA still relies on a static low-rank update and does not expose the latent…
Xiang Fang, Wanlong Fang, Wei Ji
Large Vision-Language Models have achieved unprecedented success in zero-shot recognition by aligning visual features with broad semantic concepts. However, this semantic…
Josh Qixuan Sun, Morteza Babaie, Wenyang hou, Mark Crowley +1
Antibody expression ranking is a critical task in antibody design, yet its modelling is severely hindered by the scarcity of labeled experimental data. To address this, we propose…
Metadata from BioTender-max/icml2026-ai-bio (CC0-1.0).