Tasci, E.; Chappidi, S.; Zhuge, Y.; Zhang, L.; Cooley Zgela, T.; Sproull, M.; Mackey, M.; Camphausen, K.; Krauze, A.V.
GLIO-Select: Machine Learning-Based Feature Selection and Weighting of Tissue and Serum Proteomic and Metabolomic Data Uncovers Sex Differences in Glioblastoma. Int. J. Mol. Sci. 2025, 26, 4339.
https://doi.org/10.3390/ijms26094339
AMA Style
Tasci E, Chappidi S, Zhuge Y, Zhang L, Cooley Zgela T, Sproull M, Mackey M, Camphausen K, Krauze AV.
GLIO-Select: Machine Learning-Based Feature Selection and Weighting of Tissue and Serum Proteomic and Metabolomic Data Uncovers Sex Differences in Glioblastoma. International Journal of Molecular Sciences. 2025; 26(9):4339.
https://doi.org/10.3390/ijms26094339
Chicago/Turabian Style
Tasci, Erdal, Shreya Chappidi, Ying Zhuge, Longze Zhang, Theresa Cooley Zgela, Mary Sproull, Megan Mackey, Kevin Camphausen, and Andra Valentina Krauze.
2025. "GLIO-Select: Machine Learning-Based Feature Selection and Weighting of Tissue and Serum Proteomic and Metabolomic Data Uncovers Sex Differences in Glioblastoma" International Journal of Molecular Sciences 26, no. 9: 4339.
https://doi.org/10.3390/ijms26094339
APA Style
Tasci, E., Chappidi, S., Zhuge, Y., Zhang, L., Cooley Zgela, T., Sproull, M., Mackey, M., Camphausen, K., & Krauze, A. V.
(2025). GLIO-Select: Machine Learning-Based Feature Selection and Weighting of Tissue and Serum Proteomic and Metabolomic Data Uncovers Sex Differences in Glioblastoma. International Journal of Molecular Sciences, 26(9), 4339.
https://doi.org/10.3390/ijms26094339
