deepbiop
Deep Learning Preprocessing Library for Biological Data
Decision gist · record as of 2026-08-14
Yes, if you work with biological data and need preprocessing tools for deep learning. The package is actively maintained, has no runtime dependencies (low friction), supports current Python versions, and carries a permissive license. However, verify that the specific preprocessing algorithms and model architectures you need are implemented in version 0.1.14, as the early version number suggests the feature set may still be evolving despite the 'Production/Stable' classifier.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.9 or later; compiled wheels available for macOS (x86_64, arm64), Linux (x86_64, aarch64, armv7l, i686), and Windows (32-bit, 64-bit).
- Medium install friction due to compiled wheels across multiple platforms (cp39-abi3 stable ABI).
- No runtime dependencies simplifies deployment.
License · maintenance · safety
permissive license (permissive) — Apache Software License (permissive) allows commercial and private use with minimal restrictions, making it suitable for research and production deployments.
last release 2025-01-17 (574 days) · last repo commit 2026-04-22 · 5 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 223,494 downloads/mo, #9,244 on PyPI
Alternatives
Verify before relying
pip install deepbiop
import deepbiop
# Library is ready for biological data preprocessing tasks- Specific preprocessing algorithms and model architectures available in the library—documentation link provided but content not verified.
- Whether visualization and integration features mentioned in the description are implemented in version 0.1.14.
- Performance characteristics and scalability limits for large genomic datasets.
- Maturity of the API surface given the early version number (0.1.14) despite 'Production/Stable' classifier.
What it is and what it does
DeepBioP is a Python library for preprocessing and analyzing biological data using deep learning. It targets researchers and bioinformaticians working with genomic sequences, proteomics, and imaging data, providing tools for data cleaning, normalization, and augmentation. The library is designed to integrate with popular deep learning frameworks and offers both Python and Rust APIs for flexibility across platforms.
The package has no runtime dependencies, reducing deployment complexity. It supports Python 3.9 through 3.12 and is distributed as compiled wheels across major platforms (macOS, Linux, Windows). The project is actively maintained with recent commits, and its permissive Apache license makes it suitable for both research and commercial use.
Use it for
- Preprocess genomic sequences for deep learning models by cleaning and normalizing raw sequencing data.
- Augment proteomics datasets to improve training data diversity for neural network models.
- Build end-to-end bioinformatics pipelines combining preprocessing, model training, and analysis.
- Integrate biological data preprocessing into existing deep learning workflows via Python or Rust APIs.
- Analyze imaging data from biological experiments using pre-built deep learning architectures.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you work with biological data and need preprocessing tools for deep learning.
The package is actively maintained, has no runtime dependencies (low friction), supports current Python versions, and carries a permissive license. However, verify that the specific preprocessing algorithms and model architectures you need are implemented in version 0.1.14, as the early version number suggests the feature set may still be evolving despite the 'Production/Stable' classifier.
Install
deepbiop on PyPI
Before you install
Medium install friction due to compiled wheels across multiple platforms (cp39-abi3 stable ABI). No runtime dependencies simplifies deployment. Repository is active with recent commits and a permissive license.
Requires Python 3.9 or later; compiled wheels available for macOS (x86_64, arm64), Linux (x86_64, aarch64, armv7l, i686), and Windows (32-bit, 64-bit).
License in practice
Apache Software License (permissive) allows commercial and private use with minimal restrictions, making it suitable for research and production deployments.
Quickstart
pip install deepbiop
import deepbiop
# Library is ready for biological data preprocessing tasksVerify before relying
- Specific preprocessing algorithms and model architectures available in the library—documentation link provided but content not verified.
- Whether visualization and integration features mentioned in the description are implemented in version 0.1.14.
- Performance characteristics and scalability limits for large genomic datasets.
- Maturity of the API surface given the early version number (0.1.14) despite 'Production/Stable' classifier.
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.9 |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | None |
| Maintenance | Actively maintained 574 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 223,494 / month, #9,244 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableEnvironment :: ConsoleIntended Audience :: Science/ResearchLicense :: OSI Approved :: Apache Software LicenseOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.9Programming Language :: RustTopic :: Scientific/Engineering |
Evidence: deepbiop-0.1.14-cp39-abi3-macosx_10_12_x86_64.whl; deepbiop-0.1.14-cp39-abi3-macosx_11_0_arm64.whl; deepbiop-0.1.14-cp39-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl; deepbiop-0.1.14-cp39-abi3-manylinux_2_17_armv7l.manylinux2014_armv7l.whl; deepbiop-0.1.14-cp39-abi3-manylinux_2_17_i686.manylinux2014_i686.whl; deepbiop-0.1.14-cp39-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl; deepbiop-0.1.14-cp39-abi3-musllinux_1_2_aarch64.whl; deepbiop-0.1.14-cp39-abi3-musllinux_1_2_armv7l.whl; deepbiop-0.1.14-cp39-abi3-musllinux_1_2_i686.whl; deepbiop-0.1.14-cp39-abi3-musllinux_1_2_x86_64.whl; deepbiop-0.1.14-cp39-abi3-win32.whl; deepbiop-0.1.14-cp39-abi3-win_amd64.whl
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See also biotite · biocommons.seqrepo · Keras-Preprocessing · scikit-bio · gseapy · RUST · pipebio · biom-format · pyranges · gtfparse