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Application of Generative Adversarial Networks on RNASeq Data to Uncover COVID-19 Severity Biomarkers.

Advances in Biomarker Sciences and Technology

Yvette K. Kalimumbalo, Rosaline W. Macharia, Peter W. Wagacha

Citations:

1

References:

57

Keywords
Coronavirus disease 2019 (COVID-19)
Generative grammar
Adversarial system
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
2019-20 coronavirus outbreak
Computational biology
Computer science
Generative adversarial network
Artificial intelligence
Biology
Medicine
Virology
Internal medicine
Deep learning
Infectious disease (medical specialty)
Disease
Outbreak
Sustainable Development Goals (SDG)
Zero hunger
2025
Article

Open Access

Publisher

Elsevier BV

2-Y Citation Average

2.471

DOI

https://doi.org/10.1016/j.abst.2025.01.002

Language

en

Application of Generative Adversarial Networks on RNASeq Data to Uncover COVID-19 Severity Biomarkers.

Application of Generative Adversarial Networks on RNASeq Data to Uncover COVID-19 Severity Biomarkers.

Advances in Biomarker Sciences and Technology

Yvette K. Kalimumbalo, Rosaline W. Macharia, Peter W. Wagacha

Citations:

1

References:

57

Keywords
Coronavirus disease 2019 (COVID-19)
Generative grammar
Adversarial system
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
2019-20 coronavirus outbreak
Computational biology
Computer science
Generative adversarial network
Artificial intelligence
Biology
Medicine
Virology
Internal medicine
Deep learning
Infectious disease (medical specialty)
Disease
Outbreak
Sustainable Development Goals (SDG)
Zero hunger
2025
Article

Open Access

Publisher

Elsevier BV

2-Y Citation Average

2.471

DOI

https://doi.org/10.1016/j.abst.2025.01.002

Language

en