Investigating Mitochondrial Gene Expression Patterns in Drosophila melanogaster Using Network Analysis to Understand Aging Mechanisms
Abstract
:1. Introduction
2. Materials and Methods
2.1. Data Sources
2.2. Data Preprocessing and Mapping
2.3. Clustering
2.4. Node Importance
3. Results and Discussion
3.1. Data Quality and Count Matrix
3.2. Life Stages and Clustering
3.3. Module-Trait Relationships
3.4. Network Analysis
3.5. Gene Set Enrichment Analysis
4. Concluding Remarks
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Mangoni, M.; Petrizzelli, F.; Liorni, N.; Bianco, S.D.; Biagini, T.; Napoli, A.; Adinolfi, M.; Guzzi, P.H.; Novelli, A.; Caputo, V.; et al. Investigating Mitochondrial Gene Expression Patterns in Drosophila melanogaster Using Network Analysis to Understand Aging Mechanisms. Appl. Sci. 2023, 13, 7342. https://doi.org/10.3390/app13127342
Mangoni M, Petrizzelli F, Liorni N, Bianco SD, Biagini T, Napoli A, Adinolfi M, Guzzi PH, Novelli A, Caputo V, et al. Investigating Mitochondrial Gene Expression Patterns in Drosophila melanogaster Using Network Analysis to Understand Aging Mechanisms. Applied Sciences. 2023; 13(12):7342. https://doi.org/10.3390/app13127342
Chicago/Turabian StyleMangoni, Manuel, Francesco Petrizzelli, Niccolò Liorni, Salvatore Daniele Bianco, Tommaso Biagini, Alessandro Napoli, Marta Adinolfi, Pietro Hiram Guzzi, Antonio Novelli, Viviana Caputo, and et al. 2023. "Investigating Mitochondrial Gene Expression Patterns in Drosophila melanogaster Using Network Analysis to Understand Aging Mechanisms" Applied Sciences 13, no. 12: 7342. https://doi.org/10.3390/app13127342
APA StyleMangoni, M., Petrizzelli, F., Liorni, N., Bianco, S. D., Biagini, T., Napoli, A., Adinolfi, M., Guzzi, P. H., Novelli, A., Caputo, V., & Mazza, T. (2023). Investigating Mitochondrial Gene Expression Patterns in Drosophila melanogaster Using Network Analysis to Understand Aging Mechanisms. Applied Sciences, 13(12), 7342. https://doi.org/10.3390/app13127342