---
pretty_name: OpenPhase
license: other
viewer: false
tags:
  - protein
  - peptide
  - liquid-liquid-phase-separation
  - disordered-protein-regions
  - tabular
---

# OpenPhase

![PhaseFlow: sequence data to phase-behaviour learning](figures/PhaseFlow.png)

This repository groups three PhaseFlow research-data packages:

| Package | Task | Primary data |
| --- | --- | --- |
| [`llps/`](llps/README.md) | Protein-level LLPS learning | Canonical proteins, training units, fixed training plans, and evaluation inputs. |
| [`dpr/`](dpr/README.md) | Driving phase-separation region supervision | Protein records, region supervision, training schedules, and evaluation inputs. |
| [`peptide/`](peptide/README.md) | Short-peptide 4×4 PSSI phase-diagram modelling | The verified PhaseFlow input table and its preprocessing script. |

## Related resources

| Resource | Link | Role |
| --- | --- | --- |
| PhaseFlow code | [github.com/GENTEL-lab/PhaseFlow](https://github.com/GENTEL-lab/PhaseFlow) | Installation, inference scripts, configurations, and documentation |
| Unified checkpoint | [GENTEL-Lab/PhaseFlow](https://huggingface.co/GENTEL-Lab/PhaseFlow) | Combined peptide, full-protein, and DPR runtime weights |
| Online demo | [phaseflow.bio](http://phaseflow.bio/) | Interactive PhaseFlow usage |

## Open access

All data and accompanying preprocessing materials in this repository are
fully open source and freely available to the community. We warmly welcome
their use in research, benchmarking, method development, and reproducible
studies. Please cite the relevant PhaseFlow work and retain appropriate source
attribution when using or redistributing the data.

Benchmark inputs remain physically separated and must not be used for
training, feature selection, threshold tuning, or checkpoint selection.

## Integrity

Each package contains `metadata/file_inventory.csv`. Verify all listed files
before use; the inventory intentionally excludes itself to avoid a
self-referential checksum.

```python
import csv
import hashlib
from pathlib import Path

package = Path("llps")
with (package / "metadata/file_inventory.csv").open(newline="") as handle:
    for item in csv.DictReader(handle):
        digest = hashlib.sha256((package / item["path"]).read_bytes()).hexdigest()
        assert digest == item["sha256"], item["path"]
```

## Responsible use

These data are research resources, not clinical or diagnostic tools. Sequence
labels and benchmark annotations require independent validation and must be
interpreted under the documented evidence and coordinate conventions.