Science Score: 44.0%

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  • CITATION.cff file
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  • codemeta.json file
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  • Scientific vocabulary similarity
    Low similarity (4.9%) to scientific vocabulary
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Repository

Basic Info
  • Host: GitHub
  • Owner: taehojo
  • Language: Python
  • Default Branch: master
  • Size: 3.29 MB
Statistics
  • Stars: 5
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created over 2 years ago · Last pushed over 1 year ago
Metadata Files
Readme Citation

README.md

c-SWAT: Circular-Sliding Window Association Test

Overview

The circular-Sliding Window Association Test (c-SWAT) is a novel deep learning approach that considers correlations between features, utilizing modules such as WGCNA (Weighted Gene Co-expression Network Analysis) to enhance classification prediction performance. Figure2

Requirements

  • Python 3.6.10
  • For other dependencies, check requirements.txt.

Execution Examples

bash python c-SWAT.py data/ADNI_norm.csv data/wgcna.txt data/classes.txt

Contact

For questions or support, please contact [tjo(at)iu.edu].

:bookmark: c-SWAT citation:

Jo, Taeho, et al. "Circular-SWAT for deep learning based diagnostic classification of Alzheimer’s disease: Application to metabolome data." eBioMedicine (accepted, 2023)

:bookmark: Example of SWAT application:

Jo, Taeho, et al. "Deep learning-based identification of genetic variants: application to Alzheimer’s disease classification." Briefings in Bioinformatics (2022)

Owner

  • Name: Taeho Jo
  • Login: taehojo
  • Kind: user
  • Location: Indiana, USA
  • Company: Indiana University School of Medicine

Computational Biologist, Ph.D

Citation (citation.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Jo"
  given-names: "Taeho"
  orcid: "https://orcid.org/0000-0003-1765-5735"
title: "Circular-SWAT for deep learning based diagnostic classification of Alzheimer's disease: application to metabolome data"
version: 1.0.0
date-released: 2023-10-06
url: " https://www.github.com/taehojo/c-SWAT"

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