dogear

enter for all results · esc to close

Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences

pnas.orgsite

Proceedings of the National Academy of Sciences, 2021. [All Versions].

from
AGI & CoCoSci
added
2026-10-10
likes
0

similar

  1. Protein LM github.com

    Implements BERT and autoregressive models for proteins, as described in Biological Structure and Function Emerge from Scaling Unsupervised Learning to 250 Million Protein Sequences and ProGen: Language Modeling for Protein Generation.

  2. Unsupervised learning by competing hidden units pnas.org

    Proceedings of the National Academy of Sciences, 2019. [All Versions].

  3. Highly accurate protein structure prediction with AlphaFold nature.com

    Nature, 2021. [All Versions]. This paper provides the first computational method that can regularly predict protein structures with atomic accuracy even in cases in which no similar structure is known. This approach is a canonical application of observation- and explanation…

  4. Scaling up psychology via Scientific Regret Minimization pnas.org

    Proceedings of the National Academy of Sciences, 2020. [All Versions]. The statistical and ecological basis for scaling up behavioral studies.

  5. Computational evidence for hierarchically structured reinforcement learning in humans pnas.org

    Proceedings of the National Academy of Sciences, 2020. [All Versions]. A piece of evidence on hierarchical human planning.

  6. scFoundation github.com

    Large-scale foundation model for single-cell gene expression, enabling multiple downstream tasks.

AGI & CoCoSci › Papers > Science Logology > AI Assisted Research: “Proceedings of the National Academy of Sciences, 2021. [All Versions].”