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AI for Biology

  • Protein structure prediction: AlphaFold 1/2/3, ESMFold, co-evolutionary analysis, MSA transformers
  • Protein design: inverse folding (ProteinMPNN), diffusion for protein generation (RFDiffusion), hallucination
  • Drug discovery: molecular representations (SMILES, graphs), molecular property prediction, virtual screening, docking
  • Generative chemistry: molecular generation (VAE, GAN, diffusion), retrosynthesis prediction
  • Genomics: DNA sequence modelling (Enformer, Hyena DNA), variant effect prediction, CRISPR guide design
  • Single-cell analysis: scRNA-seq, cell type clustering, trajectory inference
  • Medical imaging: radiology (CheXNet), pathology (whole-slide images), segmentation (nnU-Net)
  • Clinical NLP: medical entity extraction, clinical trial matching, electronic health records