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Investigating the determinants of performance in machine learning for protein fitness prediction

Year: 2025

Type: article

Abstract: Code for evaluating ML architectures on NK fitness landscapes, benchmarking interpolation, extrapolation, ablation, and positional extrapolation performance.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.15589853

Authors: Sandhu, Mahakaran, Mater, Adam C., Matthews, Dana S., Spence, Matthew A., Lensky, Artem A., Jackson, Colin J.

Institutions: Australian National University, ARC Centre of Excellence for Innovations in Peptide and Protein Science, UNSW Sydney, ARC Centre of Excellence in Synthetic Biology

Language: English

Topic: Evolution and Genetic Dynamics

Subfield: Genetics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: green

OpenAlex ID: W6912185267

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