Skip to content
Free planNo credit card requiredStart writing

article · Figshare · 2015

Additional file 1 of Identifying binary protein-protein interactions from affinity purification mass spectrometry data

Zhang, Xiao-Fei, Ou-Yang, Le, Xiaohua Hu, Dao-Qing Dai

Cited by 0Open access

Abstract

Supplementary figures and text. This file provides the supplementary figures (Figures S1-S7) that illustrate the comparative performances and the supplementary text which presents the parameter estimation method, convergence analysis, computational complexity analysis and comparative experiments with other regularization methods. (PDF 406 KB)

Cite this paper

APA 7

Zhang, X.-F., Ou-Yang, L., Hu, X., & Dai, D.-Q. (2015). Additional file 1 of Identifying binary protein-protein interactions from affinity purification mass spectrometry data. Figshare. https://doi.org/10.6084/m9.figshare.c.3641141_d1

MLA 9

Zhang, Xiao-Fei, et al. “Additional file 1 of Identifying binary protein-protein interactions from affinity purification mass spectrometry data.” Figshare, 2015, https://doi.org/10.6084/m9.figshare.c.3641141_d1.

Chicago

Zhang, Xiao-Fei, Le Ou-Yang, Xiaohua Hu, and Dao-Qing Dai. 2015. “Additional file 1 of Identifying binary protein-protein interactions from affinity purification mass spectrometry data.” Figshare. https://doi.org/10.6084/m9.figshare.c.3641141_d1.

Harvard

Zhang, X.-F. et al. (2015) ‘Additional file 1 of Identifying binary protein-protein interactions from affinity purification mass spectrometry data’, Figshare. Available at: https://doi.org/10.6084/m9.figshare.c.3641141_d1.

BibTeX
@article{zhang2015additional,
  title = {{Additional file 1 of Identifying binary protein-protein interactions from affinity purification mass spectrometry data}},
  author = {Zhang, Xiao-Fei and Ou-Yang, Le and Hu, Xiaohua and Dai, Dao-Qing},
  journal = {Figshare},
  year = {2015},
  doi = {10.6084/m9.figshare.c.3641141_d1}
}

Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.