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

Ziyun Ding,a Daisuke Kihara,a,b

a Department of Biological Sciences, Purdue University, West Lafayette, IN 47907
b Department of Computer Science, Purdue University, West Lafayette, IN 47907

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

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, Protein_A annotation from UniProt, and Protein_B annotation from UniProt.

  • Arabidopsis confident prediction
  • Each column from left to right in the following two data sets are protein_A ID, protein_B ID, random forest probability, IAS, PAS, CAS, phylogenetic profile similarity score, Protein_A annotation from UniProt, and Protein_B annotation from UniProt.

  • 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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