https://github.com/scikit-bio/scikit-bio
scikit-bio: a community-driven Python library for bioinformatics, providing versatile data structures, algorithms and educational resources.
https://github.com/scikit-bio/scikit-bio
bioinformatics computational-biology
Last synced: 4 months ago
JSON representation
scikit-bio: a community-driven Python library for bioinformatics, providing versatile data structures, algorithms and educational resources.
- Host: GitHub
- URL: https://github.com/scikit-bio/scikit-bio
- Owner: scikit-bio
- License: bsd-3-clause
- Created: 2013-12-13T16:24:41.000Z (about 12 years ago)
- Default Branch: main
- Last Pushed: 2024-05-16T21:03:41.000Z (over 1 year ago)
- Last Synced: 2024-05-17T20:58:49.155Z (over 1 year ago)
- Topics: bioinformatics, computational-biology
- Language: Python
- Homepage: https://scikit.bio
- Size: 24.2 MB
- Stars: 845
- Watchers: 53
- Forks: 266
- Open Issues: 235
-
Metadata Files:
- Readme: README.rst
- Changelog: CHANGELOG.md
- License: LICENSE.txt
Awesome Lists containing this project
- awesome-python-fa - scikit-bio - ابزارهایی برای آنالیز زیستی، از جمله توالییابی، فیلوژنی و آماری. (زیست شناسی و بیوتکنولوژی / کار با زمان و تقویم)
- StarryDivineSky - scikit-bio/scikit-bio - bio 是一个由社区驱动的 Python 生物信息学工具库,专注于为研究人员和开发者提供高效的数据结构、算法和教育资源。该项目的核心目标是通过模块化设计和易用性,帮助用户处理生物数据(如DNA序列、蛋白质结构、微生物群落等),并支持从基础分析到复杂建模的多种应用场景。其特色包括针对生物数据设计的专用数据结构(如序列对象、距离矩阵),以及与主流科学计算库(如NumPy、SciPy)的无缝集成,使用户能够快速实现数据预处理、统计分析和可视化。工作原理上,scikit-bio 采用面向对象设计,将生物数据抽象为可操作的对象,并通过算法库提供序列比对、系统发育树构建、微生物多样性分析等功能,同时支持通过教育资源(如教程、示例代码)降低学习门槛。该库被广泛应用于基因组学、宏基因组学和生态学研究,其开源社区持续优化代码质量,并通过单元测试确保可靠性。对于需要处理大规模生物数据的用户,scikit-bio 提供了可扩展的架构,允许通过自定义模块扩展功能,同时兼容主流计算环境(如Jupyter Notebook、命令行工具)。项目还强调可复现性,所有算法均基于科学验证的原理,并通过文档和示例代码帮助用户快速上手。总体而言,scikit-bio 通过将复杂生物信息学任务转化为可编程的Python接口,降低了科研和工业应用的技术壁垒。 (其他_生物医药 / 资源传输下载)
README
|license| |build| |coverage| |bench| |release| |pypi| |conda| |gitter|
.. image:: logos/logo.svg
:width: 600 px
:target: https://scikit.bio
:alt: scikit-bio logo
*scikit-bio is an open-source, BSD-licensed Python 3 package providing data structures, algorithms and educational resources for bioinformatics.*
Visit the scikit-bio website: https://scikit.bio to learn more about this project.
Releases
--------
Latest release: `0.7.0 `_ (`documentation `_, `changelog `_). Compatible with Python 3.9 and above.
Installation
------------
Install the latest release of scikit-bio using ``conda``::
conda install -c conda-forge scikit-bio
Or using ``pip``::
pip install scikit-bio
See further `instructions on installing `_ scikit-bio on various platforms.
Adoption
--------
Some of the projects that we know of that are using scikit-bio are:
- `QIIME 2 `_, `Qiita `_, `Emperor `_, `tax2tree `_, `ghost-tree `_, `Platypus-Conquistador `_, `An Introduction to Applied Bioinformatics `_.
License
-------
scikit-bio is available under the new BSD license. See `LICENSE.txt `_ for scikit-bio's license, and the `licenses directory `_ for the licenses of third-party software that is (either partially or entirely) distributed with scikit-bio.
Team
----
Our core development team consists of three lead developers: **Dr. Qiyun Zhu** at Arizona State University (ASU) (@qiyunzhu), **Dr. James Morton** at Gutz Analytics (@mortonjt), and **Dr. Daniel McDonald** at the University of California San Diego (UCSD) (@wasade), one software engineer: **Matthew Aton** (@mataton) and one bioinformatician: **Dr. Lars Hunger** (@LarsHunger). **Dr. Rob Knight** at UCSD (@rob-knight) provides guidance on the development and research. **Dr. Greg Caporaso** (@gregcaporaso) at Northern Arizona University (NAU), the former leader of the scikit-bio project, serves as an advisor on the current project.
Credits
-------
We thank the many contributors to scikit-bio. A complete `list of contributors `_ to the scikit-bio codebase is available at GitHub. This however may miss the larger community who contributed by testing the software and providing valuable comments, who we hold equal appreciation to.
Wanna contribute? We enthusiastically welcome community contributors! Whether it's adding new features, improving code, or enhancing documentation, your contributions drive scikit-bio and open-source bioinformatics forward. Start your journey by reading the `Contributor's guidelines `_.
Funding
-------
The development of scikit-bio is currently supported by the U.S. Department of Energy, Office of Science under award number `DE-SC0024320 `_, awarded to Dr. Qiyun Zhu at ASU (lead PI), Dr. James Morton at Gutz Analytics, and Dr. Rob Knight at UCSD.
Citation
--------
If you use scikit-bio for any published research, please see our `Zenodo page `_ for how to cite.
Collaboration
-------------
For collaboration inquiries and other formal communications, please reach out to **Dr. Qiyun Zhu** at `qiyun.zhu@asu.edu`. We welcome academic and industrial partnerships to advance our mission.
Branding
--------
The logo of scikit-bio was created by `Alina Prassas `_. Vector and bitmap image files are available at the `logos `_ directory.
Pre-history
-----------
scikit-bio began from code derived from `PyCogent `_ and `QIIME `_, and the contributors and/or copyright holders have agreed to make the code they wrote for PyCogent and/or QIIME available under the BSD license. The contributors to PyCogent and/or QIIME modules that have been ported to scikit-bio are listed below:
- Rob Knight (@rob-knight), Gavin Huttley (@gavinhuttley), Daniel McDonald (@wasade), Micah Hamady, Antonio Gonzalez (@antgonza), Sandra Smit, Greg Caporaso (@gregcaporaso), Jai Ram Rideout (@jairideout), Cathy Lozupone (@clozupone), Mike Robeson (@mikerobeson), Marcin Cieslik, Peter Maxwell, Jeremy Widmann, Zongzhi Liu, Michael Dwan, Logan Knecht (@loganknecht), Andrew Cochran, Jose Carlos Clemente (@cleme), Damien Coy, Levi McCracken, Andrew Butterfield, Will Van Treuren (@wdwvt1), Justin Kuczynski (@justin212k), Jose Antonio Navas Molina (@josenavas), Matthew Wakefield (@genomematt) and Jens Reeder (@jensreeder).
.. |license| image:: https://img.shields.io/badge/License-BSD%203--Clause-blue.svg
:alt: License
:target: https://opensource.org/licenses/BSD-3-Clause
.. |build| image:: https://github.com/scikit-bio/scikit-bio/actions/workflows/ci.yml/badge.svg
:alt: Build Status
:target: https://github.com/scikit-bio/scikit-bio/actions/workflows/ci.yml
.. |coverage| image:: https://codecov.io/gh/scikit-bio/scikit-bio/graph/badge.svg?token=1qbzC6d2F5
:alt: Coverage Status
:target: https://codecov.io/gh/scikit-bio/scikit-bio
.. |bench| image:: https://img.shields.io/badge/benchmarked%20by-asv-green.svg
:alt: ASV Benchmarks
:target: https://scikit.bio/scikit-bio-benchmarks
.. |release| image:: https://img.shields.io/github/v/release/scikit-bio/scikit-bio.svg
:alt: Release
:target: https://github.com/scikit-bio/scikit-bio/releases
.. |pypi| image:: https://img.shields.io/pypi/dm/scikit-bio.svg?label=PyPI%20downloads
:alt: PyPI Downloads
:target: https://pypi.org/project/scikit-bio/
.. |conda| image:: https://img.shields.io/conda/dn/conda-forge/scikit-bio.svg?label=Conda%20downloads
:alt: Conda Downloads
:target: https://anaconda.org/conda-forge/scikit-bio
.. |gitter| image:: https://badges.gitter.im/Join%20Chat.svg
:alt: Gitter
:target: https://gitter.im/biocore/scikit-bio