FLIP

Fitness landscape inference benchmarks with realistic train/test splits (AAV, GB1, Meltome, SCL, Bind).

Composite
80.8
Experimental validation
Retrospective
Stages
Target IDDevelopmental Candidate
Modalities
protein-general
Task types
fitness-prediction
Size
landscapes: 5
splits: 15
License
CC-BY 4.0
First release
2021-12
Last updated
2024-05
Official site
→ project page
Leaderboard
→ leaderboard
Dataset
→ dataset
Code / GitHub
→ repository
HuggingFace
→ HF
Paper
FLIP: Benchmark tasks in fitness landscape inference for proteins · Dallago C, Mou J, Johnston KE, et al. · 2021 · paper · doi:10.48550/arXiv.2112.06661 · 120 citations
Flags
none
Experts
Burkhard Rost, Mohammed AlQuraishi, Christian Dallago
Groups
Rostlab (TU München), AlQuraishi Lab (Columbia)
Hosted by
FLIP
Related benchmarks
ProteinGym

Rubric (7-criterion)

rigor
5
coverage
3
maintenance
3
adoption
4
quality
5
accessibility
5
industry_relevance
3

Notes

Complements ProteinGym (smaller but carefully designed splits).

← Back to all benchmarks

Compare:
Open comparison →