🧬 Computational Biology

📹 ICCV2025 · 4 paper notes

📌 Same area in other venues: 📷 CVPR2026 (21) · 🔬 ICLR2026 (156) · 💬 ACL2026 (5) · 🧪 ICML2026 (52) · 🤖 AAAI2026 (20) · 🧠 NeurIPS2025 (76)

CryoFastAR: Fast Cryo-EM Ab initio Reconstruction Made Easy

The first work to introduce the DUSt3R-style geometric foundation model paradigm into cryo-EM, achieving feedforward pose prediction from large sets of noisy particle images via a ViT encoder with cross-view attention decoder—without iterative optimization—enabling ab initio protein 3D reconstruction 10–33× faster than traditional methods.

G2PDiffusion: Cross-Species Genotype-to-Phenotype Prediction via Evolutionary Diffusion

This paper proposes G2PDiffusion, the first diffusion model-based cross-species genotype-to-phenotype prediction framework, which generates morphological images conditioned on evolutionary signals (multiple sequence alignments, MSA, and environmental context) to predict species appearance from DNA sequences.

Integrating Biological Knowledge for Robust Microscopy Image Profiling on De Novo Cell Lines

This paper proposes integrating external biological knowledge — protein–protein interaction graphs and transcriptomic features from single-cell foundation models — into microscopy image pretraining, explicitly decoupling perturbation-specific and cell-line-specific representations to improve generalization of perturbation screening on unseen (de novo) cell lines.

MolParser: End-to-end Visual Recognition of Molecule Structures in the Wild

This paper proposes MolParser, an end-to-end Optical Chemical Structure Recognition (OCSR) method that handles Markush structures via an extended SMILES representation (E-SMILES), constructs a large-scale training set MolParser-7M with 7 million samples, and incorporates real-world literature data through active learning. MolParser achieves 76.9% accuracy on the WildMol benchmark, significantly outperforming existing methods.