Labs & Groups (1)
Models (8)
A hybrid simulation and machine-learning framework that predicts ribosome location profiles from mRNA sequence alone, combining a structure-aware TASEP with a Mamba polisher.
A 730M-parameter protein foundation model that co-designs enzyme sequence and 3D structure under small-molecule ligand guidance for de novo enzyme design.
EEG foundation model pretrained by spectrogram reconstruction that improves online directional motor-imagery brain-computer interface control.
A tokenizer-free, hierarchical autoregressive genomic foundation model that adaptively chunks raw nucleotides, enabling efficient long-context learning and zero-shot variant and gene predictions.
A multimodal LLM fine-tuned to interpret electrocardiogram images, trained on the >1M-sample ECGInstruct dataset and evaluated on the ECGBench benchmark.
Training-free cryo-ET tomogram segmentation that adapts SAM and DINOv2 for 3D volumetric data, enabling full tomogram segmentation from a single user prompt.
A transformer-based single particle tracker for fluorescence microscopy that uses multi-hypothesis attention and position-based relinking to handle low SNR and high particle density.
Multi-modal self-supervised model pre-trained on regulatory genome sequences and transcription factor binding matrices for cell-type-specific regulatory prediction.