Scikit-bio: a fundamental Python library for biological omic data analysis
2025-12-11·,,,,
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0 min read
Matthew Aton
Daniel McDonald
Jorge Cañardo Alastuey
Raeed Azom
Paarth Batra
Valentyn Bezshapkin
Evan Bolyen
Alexander Cagle
J Gregory Caporaso
Justine W Debelius
Kestrel Gorlick
Nirmitha Hamsanipally
Lars Hunger
Aryan Keluskar
Disen Liao
Yang Young Lu
Jose A Navas-Molina
Anders Pitman
Jai Ram Rideout
Anton Sazonov
Bharath Sathappan
Karen Schwarzberg Lipson
Igor Sfiligoi
Chris Tapo
Yoshiki Vázquez-Baeza
Zijun Wu
Zhenjiang Zech Xu
Mingsong Sam Ye
Jianshu Zhao
Rob Knight
James T Morton
Qiyun Zhu
Abstract
Scikit-bio is an open-source, BSD-licensed Python package providing data structures, algorithms, and educational resources for bioinformatics. It is a fundamental library for biological omic data analysis, supporting a wide range of tasks from sequence analysis to diversity calculations.
Publication
Nature Methods
Authors
Valentyn Bezshapkin
(he/him)
MD, PhD Researcher in Bioinformatics
MD and PhD student in Bioinformatics at ETH Zürich, applying deep learning
and computational methods to decode the human gut microbiome. Building tools
that bridge metagenomics, machine learning, and clinical insights.