Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/Benjamin-Lee/deep-rules
Ten Quick Tips for Deep Learning in Biology
https://github.com/Benjamin-Lee/deep-rules
bioinformatics biology computational-biology data-science deep-learning genomics machine-learning manubot manuscript
Last synced: about 2 months ago
JSON representation
Ten Quick Tips for Deep Learning in Biology
- Host: GitHub
- URL: https://github.com/Benjamin-Lee/deep-rules
- Owner: Benjamin-Lee
- License: other
- Created: 2018-10-09T02:10:24.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2021-11-30T13:28:27.000Z (almost 3 years ago)
- Last Synced: 2024-06-18T23:51:16.695Z (3 months ago)
- Topics: bioinformatics, biology, computational-biology, data-science, deep-learning, genomics, machine-learning, manubot, manuscript
- Language: HTML
- Homepage: https://benjamin-lee.github.io/deep-rules/
- Size: 44.8 MB
- Stars: 227
- Watchers: 27
- Forks: 46
- Open Issues: 65
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE-CC0.md
- Code of conduct: CODE_OF_CONDUCT.md
Awesome Lists containing this project
README
# Ten Quick Tips for Deep Learning in Biology
[](https://Benjamin-Lee.github.io/deep-rules/)
[](https://Benjamin-Lee.github.io/deep-rules/manuscript.pdf)
[](https://github.com/Benjamin-Lee/deep-rules/actions)
[](https://twitter.com/intent/tweet?text=Have%20you%20used%20deep%20learning%20in%20your%20research%3F%20If%20so%2C%20contribute%20to%20the%20Ten%20Simple%20Rules%20for%20Deep%20Learning%20in%20Biology%20paper%21%0A%0Ahttp%3A%2F%2Fgithub.com%2FBenjamin-Lee%2Fdeep-rules)
## Manuscript description
This is the manuscript for a community-written article aimed at [PLOS
Computational Biology](https://journals.plos.org/ploscompbiol/). Deep learning is exploding in
popularity and is increasingly finding its way into biological data analysis.
However, since most biologists receive little (or no) data science training,
using deep learning properly can be a daunting task.
**We're going to try to fix that.** By boiling down the community's knowledge
into ten quick tips, we hope to increase the number of biological researchers
using DL (by making it more inviting) and the quality of the research (by
helping them avoid common mistakes).
Join us!
## Where we are now
Currently, we're submitting a revised version of the manuscript in response to reviewer feedback.
The raw text of the manuscript is stored within the [content directory](content). The rendered manuscript may be viewed as HTML [here](https://Benjamin-Lee.github.io/deep-rules/) or as a PDF [here](https://Benjamin-Lee.github.io/deep-rules/manuscript.pdf).
## How you can help
Help of any kind is highly appreciated. Want to pitch in but not sure how?
- Help us write the [tips](tips.md) into a [manuscript](content).
- Know of anyone who might be interested? [Send them an email!](mailto:@?subject=Ten%20Quick%20Tips%20for%20Using%20Deep%20Learning%20in%20Biology%20paper&body=Take%20a%20look%20at%20the%20Deep%20Tips%20project%2C%20a%20PLOS%20Computational%20Biology%20paper%20written%20collaboratively%20using%20GitHub!%20%0A%0Ahttps%3A%2F%2Fgithub.com%2FBenjamin-Lee%2Fdeep-rules%0A%0AIf%20you%20know%20of%20anyone%20who%20might%20be%20interested%2C%20feel%20free%20to%20forward%20this%20email%20along!)
- Have Twitter followers? [Tweet about the project!](https://twitter.com/intent/tweet?text=Have%20you%20used%20deep%20learning%20in%20your%20research%3F%20If%20so%2C%20contribute%20to%20the%20Ten%20Quick%20Tips%20for%20Deep%20Learning%20in%20Biology%20paper%21%0A%0Ahttps%3A%2F%2Fgithub.com%2FBenjamin-Lee%2Fdeep-rules)
For more information, see [the contribution guidelines](CONTRIBUTING.md). All contributions are subject to the [code of conduct](CODE_OF_CONDUCT.md).
## A note on the project's name
Originally, this paper was going to be titled "Ten simple rules for deep learning in biology." However, the [journal asked](https://github.com/Benjamin-Lee/deep-rules/issues/99) that we change the name to "*n* quick tips for deep learning in biology" to be placed into the educational section as well as to give us more latitude with the number of tips we have. While we changed the name of the paper, for simplicity, we kept the name of the repo as `deep-rules`.
## Manubot
Manubot is a system for writing scholarly manuscripts via GitHub.
Manubot automates citations and references, versions manuscripts using git, and enables collaborative writing via GitHub.
An [overview manuscript](https://greenelab.github.io/meta-review/ "Open collaborative writing with Manubot") presents the benefits of collaborative writing with Manubot and its unique features.
The [rootstock repository](https://git.io/fhQH1) is a general purpose template for creating new Manubot instances, as detailed in [`SETUP.md`](SETUP.md).
See [`USAGE.md`](USAGE.md) for documentation how to write a manuscript.
Please open [an issue](https://github.com/Benjamin-Lee/deep-rules/issues) for questions related to Manubot usage, bug reports, or general inquiries.
### Repository directories & files
The directories are as follows:
+ [`content`](content) contains the manuscript source, which includes markdown files as well as inputs for citations and references.
See [`USAGE.md`](USAGE.md) for more information.
+ [`output`](output) contains the outputs (generated files) from Manubot including the resulting manuscripts.
You should not edit these files manually, because they will get overwritten.
+ [`webpage`](webpage) is a directory meant to be rendered as a static webpage for viewing the HTML manuscript.
+ [`build`](build) contains commands and tools for building the manuscript.
+ [`ci`](ci) contains files necessary for deployment via continuous integration.
### Local execution
The easiest way to run Manubot is to use [continuous integration](#continuous-integration) to rebuild the manuscript when the content changes.
If you want to build a Manubot manuscript locally, install the [conda](https://conda.io) environment as described in [`build`](build).
Then, you can build the manuscript on POSIX systems by running the following commands from this root directory.
```sh
# Activate the manubot conda environment (assumes conda version >= 4.4)
conda activate manubot
# Build the manuscript, saving outputs to the output directory
bash build/build.sh
# At this point, the HTML & PDF outputs will have been created. The remaining
# commands are for serving the webpage to view the HTML manuscript locally.
# This is required to view local images in the HTML output.
# Configure the webpage directory
manubot webpage
# You can now open the manuscript webpage/index.html in a web browser.
# Alternatively, open a local webserver at http://localhost:8000/ with the
# following commands.
cd webpage
python -m http.server
```
Sometimes it's helpful to monitor the content directory and automatically rebuild the manuscript when a change is detected.
The following command, while running, will trigger both the `build.sh` script and `manubot webpage` command upon content changes:
```sh
bash build/autobuild.sh
```
### Continuous Integration
[](https://github.com/Benjamin-Lee/deep-rules/actions)
Whenever a pull request is opened, Travis CI will test whether the changes break the build process to generate a formatted manuscript.
The build process aims to detect common errors, such as invalid citations.
If your pull request build fails, see the Travis CI logs for the cause of failure and revise your pull request accordingly.
When a commit to the `master` branch occurs (for example, when a pull request is merged), Travis CI builds the manuscript and writes the results to the [`gh-pages`](https://github.com/Benjamin-Lee/deep-rules/tree/gh-pages) and [`output`](https://github.com/Benjamin-Lee/deep-rules/tree/output) branches.
The `gh-pages` branch uses [GitHub Pages](https://pages.github.com/) to host the following URLs:
+ **HTML manuscript** at https://Benjamin-Lee.github.io/deep-rules/
+ **PDF manuscript** at https://Benjamin-Lee.github.io/deep-rules/manuscript.pdf
For continuous integration configuration details, see [`.travis.yml`](.travis.yml).
## License
[](http://creativecommons.org/licenses/by/4.0/)
[](https://creativecommons.org/publicdomain/zero/1.0/)
Except when noted otherwise, the entirety of this repository is licensed under a CC BY 4.0 License ([`LICENSE.md`](LICENSE.md)), which allows reuse with attribution.
Please attribute by linking to https://github.com/Benjamin-Lee/deep-rules.
Since CC BY is not ideal for code and data, certain repository components are also released under the CC0 1.0 public domain dedication ([`LICENSE-CC0.md`](LICENSE-CC0.md)).
All files matched by the following glob patterns are dual licensed under CC BY 4.0 and CC0 1.0:
+ `*.sh`
+ `*.py`
+ `*.yml` / `*.yaml`
+ `*.json`
+ `*.bib`
+ `*.tsv`
+ `.gitignore`
All other files are only available under CC BY 4.0, including:
+ `*.md`
+ `*.html`
+ `*.pdf`
+ `*.docx`
Please open [an issue](https://github.com/Benjamin-Lee/deep-rules/issues) for any question related to licensing.