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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