TY - GEN
T1 - Multi-label classification based on subcellular region-guided feature description for protein localisation
AU - Rana, Priyanka
AU - Meijering, Erik
AU - Sowmya, Arcot
AU - Song, Yang
PY - 2021/4/16
Y1 - 2021/4/16
N2 - In this paper, we present a multi-label classification pipeline and a novel feature descriptor for the protein subcellular localisation. The challenge here is the development of a computational model that can classify multi-site proteins on a highly imbalanced dataset with a long-tail distribution and multi-label images. To address this challenge, we design a Location-Sorted Random Projections feature descriptor to represent image intensity and gradient of the protein of interest in reference to the correlated cellular region. Multilabel Synthetic Minority Over-sampling Technique is optimised to generate synthetic features with labels to handle class imbalance. Our method achieves the state-of-the-art performance on a large-scale public dataset and demonstrates excellent performance for the minority classes.
AB - In this paper, we present a multi-label classification pipeline and a novel feature descriptor for the protein subcellular localisation. The challenge here is the development of a computational model that can classify multi-site proteins on a highly imbalanced dataset with a long-tail distribution and multi-label images. To address this challenge, we design a Location-Sorted Random Projections feature descriptor to represent image intensity and gradient of the protein of interest in reference to the correlated cellular region. Multilabel Synthetic Minority Over-sampling Technique is optimised to generate synthetic features with labels to handle class imbalance. Our method achieves the state-of-the-art performance on a large-scale public dataset and demonstrates excellent performance for the minority classes.
KW - Protein subcellular localisation
KW - multilabel classification
KW - sorted random projections
UR - http://www.scopus.com/inward/record.url?scp=85107221728&partnerID=8YFLogxK
U2 - 10.1109/ISBI48211.2021.9434145
DO - 10.1109/ISBI48211.2021.9434145
M3 - Conference proceeding contribution
SN - 9781665429474
T3 - IEEE International Symposium on Biomedical Imaging
SP - 1929
EP - 1933
BT - Proceedings of the 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)
PB - IEEE:Institute of Electrical Electronics Engineers Inc
CY - Nice
T2 - 18th IEEE International Symposium on Biomedical Imaging, ISBI 2021
Y2 - 13 April 2021 through 16 April 2021
ER -