Benjamin-Lee / Benjamin-Lee/deep-rules
Review: Recent Advances of Deep Learning in Bioinformatics and Computational Biology
- Dominant language
- HTML
- Stars
- 226
- Forks
- 44
- PR merge metrics
- No merged PRs in 30d
Description
> Extracting inherent valuable knowledge from omics big data remains as a daunting problem in bioinformatics and computational biology. Deep learning, as an emerging branch from machine learning, has exhibited unprecedented performance in quite a few applications from academia and industry. We highlight the difference and similarity in widely utilized models in deep learning studies, through discussing their basic structures, and reviewing diverse applications and disadvantages. We anticipate the work can serve as a meaningful perspective for further development of its theory, algorithm and application in bioinformatic and computational biology.
https://doi.org/10.3389/fgene.2019.00214
Contributor guide
Research direction
The issue contains only an abstract and a DOI link, with no files, tests, or concrete repository change identified. Start by reading the linked paper and determine what contribution is intended; the issue needs a defined location, scope, and completion condition before implementation can begin.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- bioinformatics, machine-learning
- Domain
- bioinformatics, content
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100