ersiliaos/eos9li5 repository overview

⁠Biosynfoni natural product fingerprint

BioSynFoni is a biosynthesis-informed count-based molecular fingerprint designed for natural product research. It decomposes molecules into 39 biosynthetic building block substructures derived from Dewicks classification of natural product biosynthetic pathways. The fingerprint is computed via SMARTS substructure matching using RDKit and returns an integer count vector. It was shown to outperform MACCS, Morgan, and Daylight-like fingerprints for biosynthetic distance estimation and performs comparably for natural product classification while being more compact and interpretable.

This model was incorporated on 2026-02-23.Last packaged on 2026-03-24.

⁠Information

⁠Identifiers

• Ersilia Identifier: eos9li5
• Slug: biosynfoni

⁠Domain

• Task: Representation
• Subtask: Featurization
• Biomedical Area: Any
• Target Organism: Any
• Tags: Fingerprint, Natural product

⁠Input

• Input: Compound
• Input Dimension: 1

⁠Output

• Output Dimension: 39
• Output Consistency: Fixed
• Interpretation: Vector representation of a molecule. Higher counts indicate a greater presence of predefined biosynthetic unit.

Below are the Output Columns of the model:

10 of 39 columns are shown

⁠Source and Deployment

• Source: Local
• Source Type: External
• DockerHub: https://hub.docker.com/r/ersiliaos/eos9li5⁠
• Docker Architecture: AMD64
• S3 Storage: https://ersilia-models-zipped.s3.eu-central-1.amazonaws.com/eos9li5.zip⁠

⁠Resource Consumption

• Model Size (Mb): 1
• Environment Size (Mb): 469
• Image Size (Mb): 445.46

Computational Performance (seconds):

• 10 inputs: 38.27
• 100 inputs: 25.05
• 10000 inputs: 43.42

⁠References

• Source Code: https://github.com/lucinamay/biosynfoni⁠
• Publication: https://doi.org/10.1186/s13321-025-01081-6⁠
• Publication Type: Peer reviewed
• Publication Year: 2025
• Ersilia Contributor: GemmaTuron⁠

⁠License

This package is licensed under a GPL-3.0⁠ license. The model contained within this package is licensed under a MIT⁠ license.

Notice: Ersilia grants access to models as is, directly from the original authors, please refer to the original code repository and/or publication if you use the model in your research.

⁠Use

To use this model locally, you need to have the Ersilia CLI⁠ installed. The model can be fetched using the following command:

# fetch model from the Ersilia Model Hub
ersilia fetch eos9li5

Then, you can serve, run and close the model as follows:

# serve the model
ersilia serve eos9li5
# generate an example file
ersilia example -n 3 -f my_input.csv
# run the model
ersilia run -i my_input.csv -o my_output.csv
# close the model
ersilia close

⁠About Ersilia

The Ersilia Open Source Initiative⁠ is a tech non-profit organization fueling sustainable research in the Global South. Please cite⁠ the Ersilia Model Hub if you've found this model to be useful. Always let us know⁠ if you experience any issues while trying to run it. If you want to contribute to our mission, consider donating⁠ to Ersilia!