A low-code platform for evaluating and building protein property prediction workflows.

Protify

Protify is a low-code platform for evaluating protein language models and building protein property prediction workflows.

What It Does

Protify helps researchers compare protein language models across tasks, train lightweight predictors on protein embeddings, evaluate zero-shot and supervised workflows, and reproduce benchmark results with consistent data handling.

Why It Matters

Protein model selection should be empirical. The best model for one task may not be the best model for another, and benchmark claims are difficult to compare when every study uses different datasets, splits, pooling choices, probes, and reporting conventions.

Protify gives teams a common evaluation surface so model choice becomes less speculative.

Intended Use

Use Protify to prototype protein property prediction tasks, compare representations, evaluate transfer-learning strategies, and build reproducible benchmarks before committing to a model in production or experimental planning.

Limitations

Protify makes evaluation easier, but it does not make a dataset unbiased or a model universally reliable. Results still depend on label quality, split design, homology control, task definition, and experimental relevance.