{"categories":[{"label":"Libraries","url":"https://skillfed.io/packages/category/software-development-libraries/9"},{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/6"},{"label":"Bio-Informatics","url":"https://skillfed.io/packages/category/scientific-engineering-bio-informatics"}],"enrichment":{"capability":"scikit-bio provides data structures, algorithms, and educational resources for bioinformatics analysis, including sequence, phylogenetic, and diversity data manipulation.","skillfed_tags":["bioinformatics","sequence-analysis","microbiome"],"use_cases":["Analyze microbiome data using diversity metrics and phylogenetic tree operations with biom-format integration.","Work with phylogenetic trees and evolutionary relationships in biological datasets.","Integrate bioinformatics workflows with pandas DataFrames and numpy arrays for downstream analysis.","Store and retrieve large biological datasets using h5py-backed data structures.","Build educational bioinformatics applications using standardized data structures and algorithms."],"what_it_does":"scikit-bio is a Python library for bioinformatics that provides data structures and algorithms for working with biological data. It sits at the intersection of scientific computing\u2014built on numpy, scipy, pandas, and statsmodels\u2014and domain-specific bioinformatics, offering abstractions for biological sequences and diversity metrics. The package is actively maintained and widely adopted in projects like QIIME 2, Qiita, and Emperor, suggesting it has become a foundational layer for the bioinformatics Python ecosystem.\n\nThe library depends on a substantial stack of scientific packages: 11 runtime dependencies including h5py for data storage, biom-format for microbiome data interchange, and decorator for function wrapping. This makes installation moderately friction-heavy but also means it integrates well with existing scientific Python workflows. It supports Python 3.10 and above and is available as prebuilt wheels across major platforms and architectures, reducing build friction for most users.","worth_installing":"Yes, if you are doing bioinformatics work in Python. scikit-bio is actively maintained, widely adopted by established projects, has no known vulnerabilities, and provides a permissive BSD-3-Clause license. The medium install friction is justified by its comprehensive dependency stack and the maturity it brings. Not necessary for general scientific computing; install only if you need domain-specific bioinformatics data structures."},"id":"scikit-bio","links":{"html":"https://skillfed.io/packages/scikit-bio","md":"https://skillfed.io/packages/scikit-bio.md","pypi":"https://pypi.org/project/scikit-bio/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-06-01","license_spdx":"BSD-3-Clause","license_treatment":"permissive","name":"scikit-bio","python_support":"supports_current","summary":"Data structures, algorithms and educational resources for bioinformatics."},"popularity":{"monthly_downloads":143050,"position":11186,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.7.3"}