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Machine Learning for Protein Science and Engineering.

Publication ,  Journal Article
Koo, PK; Dallago, C; Nambiar, A; Yang, KK
Published in: Cold Spring Harb Perspect Biol
January 5, 2026

Recent years have seen significant breakthroughs at the intersection of machine learning and protein science. Tools such as AlphaFold have revolutionized protein structure prediction. They are also enabling variant effect prediction and functional annotation of proteins, as well as opening up new possibilities for protein design. However, these technological advances must be balanced with sustainable computing practices.

Duke Scholars

Published In

Cold Spring Harb Perspect Biol

DOI

EISSN

1943-0264

Publication Date

January 5, 2026

Volume

18

Issue

1

Location

United States

Related Subject Headings

  • Proteins
  • Protein Engineering
  • Protein Conformation
  • Machine Learning
  • Computational Biology
  • 3105 Genetics
  • 3101 Biochemistry and cell biology
 

Citation

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Koo, P. K., Dallago, C., Nambiar, A., & Yang, K. K. (2026). Machine Learning for Protein Science and Engineering. Cold Spring Harb Perspect Biol, 18(1). https://doi.org/10.1101/cshperspect.a041877
Koo, Peter K., Christian Dallago, Ananthan Nambiar, and Kevin K. Yang. “Machine Learning for Protein Science and Engineering.Cold Spring Harb Perspect Biol 18, no. 1 (January 5, 2026). https://doi.org/10.1101/cshperspect.a041877.
Koo PK, Dallago C, Nambiar A, Yang KK. Machine Learning for Protein Science and Engineering. Cold Spring Harb Perspect Biol. 2026 Jan 5;18(1).
Koo, Peter K., et al. “Machine Learning for Protein Science and Engineering.Cold Spring Harb Perspect Biol, vol. 18, no. 1, Jan. 2026. Pubmed, doi:10.1101/cshperspect.a041877.
Koo PK, Dallago C, Nambiar A, Yang KK. Machine Learning for Protein Science and Engineering. Cold Spring Harb Perspect Biol. 2026 Jan 5;18(1).

Published In

Cold Spring Harb Perspect Biol

DOI

EISSN

1943-0264

Publication Date

January 5, 2026

Volume

18

Issue

1

Location

United States

Related Subject Headings

  • Proteins
  • Protein Engineering
  • Protein Conformation
  • Machine Learning
  • Computational Biology
  • 3105 Genetics
  • 3101 Biochemistry and cell biology