GAIN-BRCA: a graph-based AI-net framework for breast cancer subtype classification using multiomics data

Authors

Jai Chand Patel (ORCID: https://orcid.org/0000-0001-9118-6899)
Sahil Sethi (ORCID: https://orcid.org/0009-0001-3891-9798)
Chittibabu Guda (ORCID: https://orcid.org/0000-0002-5393-9316)
Sushil Kumar Shakyawar (ORCID: https://orcid.org/0000-0003-4046-6836)

Institutions

University of Nebraska Medical Center (US)

Publication Details

Journal: Bioinformatics Advances
Published: 2024-12-26
DOI: https://doi.org/10.1093/bioadv/vbaf116
Citations: 2
Primary Topic: Gene expression and cancer classification
Type: article
Field-Weighted Citation Impact: 0.47

Funders

National Institutes of Health

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article

GAIN-BRCA: a graph-based AI-net framework for breast cancer subtype classification using multiomics data

Jai Chand Patel, Sahil Sethi, Chittibabu Guda, Sushil Kumar Shakyawar

Dec 26, 2024

2 citations

Bioinformatics Advances

Gene expression and cancer classification

0.47

article

GAIN-BRCA: a graph-based AI-net framework for breast cancer subtype classification using multiomics data

Jai Chand Patel, Sahil Sethi, Chittibabu Guda, Sushil Kumar Shakyawar

December 26, 2024article en

2 citations

Abstract

No abstract available for this paper.

Bioinformatics AdvancesVol. 5(1)

University of Nebraska Medical Center (US)

National Institutes of Health

Openalex Percentile: Top 33%

Gene expression and cancer classification

0.47

DOI Open Access PDF OpenAlex

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GAIN-BRCA: a graph-based AI-net framework for breast cancer subtype classification using multiomics data — Jai Chand Patel, Sahil Sethi, et al. · Bioinformatics Advances (2024) | TGRS Research Map | TGRS