Benjamin-Lee / Benjamin-Lee/deep-rules

Review: Recent Advances of Deep Learning in Bioinformatics and Computational Biology

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paper
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

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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.

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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

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