Supplemental Material for
Computational identification of protein-protein interactions in model plant proteomes

Ziyun Ding,a Daisuke Kihara,a,b,c

a Department of Biological Sciences, Purdue University, West Lafayette, IN 47907
b Department of Computer Science, Purdue University, West Lafayette, IN 47907
c Department of Pediatrics, University of Cincinnati, Cincinnati, OH 45229

This paper is in press on Scientific Report.

This page provides the PPIP prediction results in Arabidopsis, corn and soybean.

Supplemental Dataset

    Each column from left to right in the following data set are protein_A ID, protein_B ID, random forest probability, microarray mutual rank, microarray PCC, RNA-seq mutual rank, RNA-seq PCC, IAS, PAS, CAS, phylogenetic profile similarity score, common KEGG pathways, KEGG pathway name, number of common KEGG pathways, neighborhood, neighborhood_transferred, fusion, cooccurence, homology, coexpression, coexpression_transferred, experiments, experiments_transferred ,database, database_transferred, textmining, textmining_transferred, combined_score, Protein_A annotation from UniProt or RefSeq, and Protein_B annotation from UniProt or RefSeq.

  • Arabidopsis confident prediction

  • Corn confident prediction
  • Soybean confident prediction

Contact Information

If you have any questions or suggestions, please feel free to contact us at:

Ziyun Ding (ding48@purdue.edu)

Daisuke Kihara* (PI, dkihara@purdue.edu)

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