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Table 1 Features considered in the prediction of nucleolar association

From: PNAC: a protein nucleolar association classifier

Features Data source Description Bins
Amino acid frequency Protein sequences from IPI [27] PNAC considers the relative proportion of leucine, isoleucine, lysine and serine residues 5 bins for each distinct amino acid considered
Targeting motifs Phobius [32], TargetP[33], NoD [34] The predicted presence of signal peptides, transmembrane domains (TMDs), mitochondrial targeting peptides and nucleolar localisation sequences (NoLSs) 9 bins detailed in the Methods
Gene co-expression GDS596 from the Gene Expression Omnibus [42] The average Pearson correlation of expression between the query protein and proteins in the nucleolar-cytoplasmic training group using expression profiles from 79 physiologically normal tissues [35] 5 bins
GO EBI Gene Ontology (GO) annotations [36] for human Biological process and molecular function Gene Ontology (GO) annotations for the query protein are compared to those of the training set proteins 4 bins
Subcellular localisation of interactors HPRD [31], Uniprot [30], IntAct [39] and PIPs [37, 38] subcellular localisation annotations and/or protein interactions A nucleolar proximity score is calculated for all the interactors of the query protein 5 bins