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  • Proteína: Scaling Flow-based Protein Structure Generative Models
    Proteina is a novel flow-based protein backbone generative model It is trained with flow matching, leverages a scalable and efficient transformer architecture, and offers hierarchical fold class conditioning for enhanced controllability
  • NVIDIA-Digital-Bio proteina - GitHub
    Proteina achieves state-of-the-art performance on de novo protein backbone design and produces diverse and designable proteins at unprecedented length, up to 800 residues
  • Proteina: Scaling Flow-based Protein Structure Generative Models
    Here, we develop Proteina, a new large-scale flow-based protein backbone generator that utilizes hierarchical fold class labels for conditioning and relies on a tailored scalable transformer architecture with up to 5x as many parameters as previous models
  • La-Proteina: Atomistic Protein Generation via Partially Latent Flow . . .
    La-Proteina is a novel partially-latent fully atomistic protein design model Protein backbone structure is modeled explicitly, while sequence and atomistic details are captured via per-residue latent variables
  • Protein - Wikipedia
    A representation of the 3D structure of the protein myoglobin showing turquoise α-helices This protein was the first to have its structure solved by X-ray crystallography Toward the right-center among the coils, a prosthetic group called a heme group (shown in gray) with a bound oxygen molecule (red) Proteins are large biomolecules and macromolecules that comprise one or more long chains
  • New NVIDIA AI achieves over 75% ‘co-designability’ in atom-level . . .
    NVIDIA researchers have unveiled La-Proteina, an AI model that generates full-atom protein structures and can scale to chains of up to 800 residues, the basic amino acid units that form a protein
  • La-Proteina: Atomistic Protein Modeling
    La-Proteina is a generative framework that disentangles explicit backbone representations from latent side-chain details for efficient protein design It uses a partially latent model and flow matching to jointly generate coarse-grained backbones and fine atomistic features
  • P : S FLOW BASED PROTEIN S G MODELS - arXiv. org
    For model and code release, please see Prote ́ına’s GitHub repository https: github com NVIDIA-Digital-Bio proteina as well as our project page https: research nvidia com labs genair proteina




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