A linear classification approach to model the early cellular responses induced by drugs

Author

Dechang Xu ; Zhiying Liang ; Dayou Cheng ; Cuihong Dai ; Aiju Hou ; Liqiang Pan ; Jianzhong Li

Author_Institution

Sch. of Food Sci. & Eng., Harbin Inst. of Technol., Harbin, China

fYear

2014

fDate

2-5 Nov. 2014

Firstpage

27

Lastpage

29

Abstract

To quantitatively discover the protein sub-cellular translocation pattern which responds to drugs´ treatment doses is a challenge for medical applications with bio-imaging and machine learning on the Single-channel Protein Sub-cellular Location Fluorescence Images without segmentation. This paper suggested a Linear Classification Approach to model the Early Cellular Responses Induced by Drugs. Based on published image-set data, our methods´ Accuracy, Precision, Recall and F-Score will be more than 0.70, 0.71, 0.65 and 0.71 respectively.

Keywords

biomedical optical imaging; cellular biophysics; drugs; fluorescence; image classification; learning (artificial intelligence); medical image processing; patient treatment; proteins; Accuracy; F-Score; Precision; Recall; bioimaging; drug treatment doses; early cellular responses; image-set data; linear classification approach; machine learning; medical applications; protein subcellular translocation pattern; single-channel protein subcellular location fluorescence images; Accuracy; Bioinformatics; Conferences; Digital audio players; Drugs; Protein engineering; Proteins; SIFT-SVM; linear classification; protein sub-cellular translocation;

fLanguage

English

Publisher

ieee

Conference_Titel

Bioinformatics and Biomedicine (BIBM), 2014 IEEE International Conference on

Conference_Location

Belfast

Type

conf

DOI

10.1109/BIBM.2014.6999397

Filename

6999397