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Benchmark

DeepProtein benchmark

Benchmark of sequence-based, graph-based and pretrained protein models, plus two chemistry LLMs, over protein function, localization, interaction, epitope and paratope, developability, CRISPR repair and structure prediction tasks, with datasets taken from TAPE, PEER and TDC.

Results are recorded on the linked protocols, tasks or configurations listed below. Their settings and evaluations are kept separate.

40 protocols with results

Overview

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Results on linked records

This benchmark has no results of its own in this release. 40 linked records have results. They are not assigned to the underlying benchmark: each record keeps its own settings and evaluations, and its scores are on its own page.

20 further linked records are listed under Related records.

Methods and evaluation design

Procedure, tasks and evaluated configurations

Baseline coverage

Reference methods help show what a model adds beyond simple controls. We track a null control and a conventional method for each protocol.

0 of 120 active baseline roles have published Rewire measurements in this release. Measurements on a selected protocol do not establish coverage of an entire suite.

Baseline status by linked protocol

Protocol coverage CSV (gzip) · Model evaluation matrix (gzip) · Source table (gzip) · Release and checksums (gzip)

Coverage is derived from release 2026-10-22-1b7cf027e4f6. Source citations describe the original records; they do not validate an unreviewed baseline proposal. No results have been generated by this audit.

Run instructions

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Strengths, limitations and unresolved questions

Evidence

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Evidence table

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Claims, original sources and review scope · Release 2026-10-22-1b7cf027e4f6
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How to read the evidence

Sources and history

Release 2026-10-22-1b7cf027e4f6 · Record review: source checked

1 source record and release historyDownload this release (gzip)
Technical metadata and extraction receipts

Stable ID: lit-protein-20261011-deepprotein-benchmark-deepprotein

areas
protein-function
contexts
research
entity level
suite
version
As published 2025 (DeepProtein library)
task
Protein sequence learning across nine task groups
scope note
Each task keeps the split of its original benchmark; every method is trained with five random seeds and the mean and standard deviation are reported.
source locator
Results, 'Each individual split is reported from Tables 2-7'; Tables 2 to 8
limitations
Author-reported: the DeepProtein authors both run the baselines and introduce DeepProt-T5.; Residue-level and secondary structure tasks were not run for structure-based and language models (Table 7 footnote).
Related records

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