Protein-protein interaction prediction via Collective Matrix Factorization

By Qian Xu, Evan Wei Xiang, Qiang Yang. 2010

32 citations recorded by the source corpus.

Subfields: Molecular Biology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

1. Qiang Yang
2. Jaime G. Carbonell
3. Meghana Kshirsagar
4. Judith Klein-Seetharaman
5. Qian Xu
6. Yu Zhang
7. Keerthiram Murugesan
8. Inderjit S. Dhillon

Citations in the corpus

• A Survey of Transfer and Multitask Learning in Bioinformatics (2011, methodology): “[47] also explored how to use multitask learning in this area via a technique known as Collective Matrix Factorization (CMF) [48].”
• Multitask Matrix Completion for Learning Protein Interactions Across Diseases (2016, unknown): “Xu et al. (2010) used a CMF-based approach in a multitask learning setting for within-species PPI prediction.”
• Multitask learning for host–pathogen protein interactions (2013, methodology): “Another line of work in PPI prediction (Xu et al. , 2010) uses the Collective Matrix Factorization (CMF) approach proposed by Singh and Gordon (2008).”