CompareSVM: supervised, Support Vector Machine (SVM) inference of gene regularity networks-Reference-Cited by-同舟云学术

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CompareSVM: supervised, Support Vector Machine (SVM) inference of gene regularity networks

Published:2014-11-30 Issue:1 Volume:15 Page:
ISSN:1471-2105
Container-title:BMC Bioinformatics
language:en
Short-container-title:BMC Bioinformatics

Author:

Gillani Zeeshan,Akash Muhammad Sajid Hamid,Rahaman MD Matiur,Chen Ming

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Structural Biology

Link

http://link.springer.com/article/10.1186/s12859-014-0395-x/fulltext.html

Reference12 articles.

1. Pe'er D, Hacohen N: Principles and strategies for developing network models in cancer. Cell. 2011, 144 (6): 864-873. 10.1016/j.cell.2011.03.001.

2. Maetschke SR, Madhamshettiwar PB, Davis MJ, Ragan MA: Supervised, semi-supervised and unsupervised inference of gene regulatory networks. Brief Bioinform. 2014, 15 (2): 195-211. 10.1093/bib/bbt034.

3. Mordelet F, Vert J-P: SIRENE: supervised inference of regulatory networks. Bioinformatics. 2008, 24 (16): i76-i82. 10.1093/bioinformatics/btn273.

4. Cerulo L, Elkan C, Ceccarelli M: Learning gene regulatory networks from only positive and unlabeled data. BMC Bioinformatics. 2010, 11 (1): 228-10.1186/1471-2105-11-228.

5. Ben-Hur A, Noble WS: Kernel methods for predicting protein-protein interactions. Bioinformatics. 2005, 21 (Suppl 1): i38-i46. 10.1093/bioinformatics/bti1016.

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