Variable-Group Selection on Estimated Metabolites of Curcuma aeruginosa Related to Antioxidant Activity by Using Group Lasso Regression
Authors
Rahmat H.S, Hari Wijayanto, Farit Mochamad Afendi, Bagus Sartono, Rahma Anisa, Dewi Anggraini Septianingsih
Corresponding Author
Hari Wijayanto
Available Online December 2018.
- DOI
- 10.2991/icm2e-18.2018.30How to use a DOI?
- Keywords
- Variable-group selection, group lasso regression, antioxidant, Curcuma aeruginosa
- Abstract
A metabolite may be expressed on a group of variables in mass-spectrometry experiments. Evaluation on metabolite effects should consider this group. Group lasso regression can be used to evaluate these groups. It shrinks some regression coefficients to zero by intermediate penalty on OLS loss function. The data used were antioxidant activity and mass/charge ion from LC-MS output of Curcuma aeruginosa compositions of 3 areas in Java. The significance metabolite groups were 148,060, 202,179, 204,159, 228,123, 238,150, 246,133, 312,274, and 398,335.
- Copyright
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Rahmat H.S AU - Hari Wijayanto AU - Farit Mochamad Afendi AU - Bagus Sartono AU - Rahma Anisa AU - Dewi Anggraini Septianingsih PY - 2018/12 DA - 2018/12 TI - Variable-Group Selection on Estimated Metabolites of Curcuma aeruginosa Related to Antioxidant Activity by Using Group Lasso Regression BT - Proceedings of the 2nd International Conference on Mathematics and Mathematics Education 2018 (ICM2E 2018) PB - Atlantis Press SP - 128 EP - 130 SN - 2352-5398 UR - https://doi.org/10.2991/icm2e-18.2018.30 DO - 10.2991/icm2e-18.2018.30 ID - H.S2018/12 ER -