ml4bio-workshop

Materials for a workshop introducing machine learning to biologists

https://github.com/carpentries-incubator/ml4bio-workshop

Science Score: 67.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 3 DOI reference(s) in README
  • Academic publication links
    Links to: zenodo.org
  • Academic email domains
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (12.6%) to scientific vocabulary

Keywords

alpha carpentries-incubator education english lesson machine-learning
Last synced: 6 months ago · JSON representation ·

Repository

Materials for a workshop introducing machine learning to biologists

Basic Info
Statistics
  • Stars: 23
  • Watchers: 11
  • Forks: 9
  • Open Issues: 64
  • Releases: 3
Topics
alpha carpentries-incubator education english lesson machine-learning
Created over 7 years ago · Last pushed 11 months ago
Metadata Files
Readme Contributing License Code of conduct Citation Authors

README.md

Machine Learning for Biologists (ML4Bio) workshop

Binder DOI

Recent advances in high-throughput technologies have led to rapid growth in the amount of omics data. These massive datasets, accompanied by numerous data points enriched over the past decades, are extremely valuable in the discovery of complex biological structures, but also present challenges in various aspects of data analysis. This workshop introduces biologists to concepts in machine learning, a powerful set of models for drawing inference from data. Upon completion of the workshop, attendees will be able to identify machine learning applications, examine factors that influence model selection, recognize major methodological flaws in a machine learning experiment, and gain a greater appreciations for machine learning.

This repository contains materials for the ML4Bio workshop. It generates the corresponding lesson website from The Carpentries lesson template.

Getting started

Visit the software setup page for instructions on installing the ml4bio software and downloading the example datasets, guides, and slides contained in this repository.

Overview

In addition to the materials needed to build the lesson website, this repository contains the following files and subdirectories: - binder: a configuration file to enable running the illustration.ipynb notebook interactively using Binder - data: example datasets to use with the ml4bio classification software, including both real and toy (illustrative simulated) datasets - fig: figures for the lessons and guides - guide: tutorials about the ml4bio software, machine learning concepts, and various classifiers - planning: materials for instructors to plan the workshop - scripts: ml4bio installation scripts - illustration.ipynb: a Jupyter notebook the demonstrates the machine learned workshop in Python code

The ml4bio repository contains the Python software.

Contributing

We welcome contributions to improve the workshop! The best way to provide suggestions or propose contributions is in the GitHub issues.

Maintainers

Current maintainers of this lesson are

Authors

A list of contributors to the lesson can be found in AUTHORS and the GitHub contributors.

Citation

To cite this lesson, please consult with CITATION

Licenses

The original workshop materials and guides created in this repository are licensed under the Creative Commons Attribution 4.0 International Public License. However, the guides also contain images from third-party sources, as noted in the image links and guide references. See the linked original image sources for their licenses and terms of reuse.

The workshop template is derived from The Carpentries lesson template. The template is Copyright © 2018–2020 The Carpentries and licensed CC BY 4.0. See the license for additional information.

Owner

  • Name: carpentries-incubator
  • Login: carpentries-incubator
  • Kind: organization

Citation (CITATION)

An approachable, flexible and practical machine learning workshop for biologists.
Chris S Magnano, Fangzhou Mu, Rosemary S Russ, Milica Cvetkovic, Debora Treu, Anthony Gitter.
Bioinformatics, 38:Supplement_1, 2022. doi:10.1093/bioinformatics/btac233

See the AUTHORS file for the list of current authors.

GitHub Events

Total
  • Create event: 2
  • Release event: 2
  • Issues event: 5
  • Watch event: 2
  • Issue comment event: 3
  • Push event: 8
  • Pull request review event: 1
  • Pull request event: 3
  • Fork event: 2
Last Year
  • Create event: 2
  • Release event: 2
  • Issues event: 5
  • Watch event: 2
  • Issue comment event: 3
  • Push event: 8
  • Pull request review event: 1
  • Pull request event: 3
  • Fork event: 2

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 78
  • Total pull requests: 27
  • Average time to close issues: 10 months
  • Average time to close pull requests: 3 months
  • Total issue authors: 6
  • Total pull request authors: 4
  • Average comments per issue: 2.51
  • Average comments per pull request: 0.93
  • Merged pull requests: 22
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 4
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 2
  • Pull request authors: 0
  • Average comments per issue: 0.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • agitter (71)
  • fmu2 (2)
  • cmilica (2)
  • csmagnano (2)
  • xiaohk (1)
  • tobyhodges (1)
Pull Request Authors
  • agitter (13)
  • cmilica (9)
  • csmagnano (3)
  • xiaohk (2)
  • kassabry (1)
Top Labels
Issue Labels
Pull Request Labels

Dependencies

binder/environment.yml pypi
  • ml4bio *