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Updated: Mar 29, 2026

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
Published on: July 14, 2015
SVD-phy: improved prediction of protein functional associations through singular value decomposition of phylogenetic
Andrea Franceschini1, Jianyi Lin2, Christian von Mering1
1Institute of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, Zurich, 8057, Switzerland, Swiss Institute of Bioinformatics, Quartier Sorge, Bâtiment Génopode, Lausanne, 1015, Switzerland.
Unlabelled:
A successful approach for predicting functional associations between non-homologous genes is to compare their phylogenetic distributions. We have devised a phylogenetic profiling algorithm, SVD-Phy, which uses truncated singular value decomposition to address the problem of uninformative profiles giving rise to false positive predictions. Benchmarking the algorithm against the KEGG pathway database, we found that it has substantially improved performance over existing phylogenetic profiling methods.
Availability And Implementation:
The software is available under the open-source BSD license at https://bitbucket.org/andrea/svd-phy
Contact:
lars.juhl.jensen@cpr.ku.dk
Supplementary Information:
Supplementary data are available at Bioinformatics online.
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