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

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

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

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.

Original languageEnglish
Title of host publicationProceedings - 2014 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2014
EditorsHuiru Zheng, Xiaohua Tony Hu, Daniel Berrar, Yadong Wang, Werner Dubitzky, Jin-Kao Hao, Kwang-Hyun Cho, David Gilbert
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages27-29
Number of pages3
ISBN (Electronic)9781479956692
DOIs
Publication statusPublished - 29 Dec 2014
Externally publishedYes
Event2014 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2014 - Belfast, United Kingdom
Duration: 2 Nov 20145 Nov 2014

Publication series

NameProceedings - 2014 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2014

Conference

Conference2014 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2014
Country/TerritoryUnited Kingdom
CityBelfast
Period2/11/145/11/14

Keywords

  • linear classification
  • protein sub-cellular translocation
  • SIFT-SVM

Fingerprint

Dive into the research topics of 'A linear classification approach to model the early cellular responses induced by drugs'. Together they form a unique fingerprint.

Cite this