Top 20 predictions of new drug-gene relationships for PharmGKB, and whether a PGx relationship has been documented in the literature.

<p>*** indicates that an association has been demonstrated experimentally between changes in the expression/activity of the gene/protein and the efficacy of the drug</p><p>** indicates that such an association is likely, but has not yet been studied</p><p>* indicates that the association has been studied experimentally, and the experiment refuted the association. Here we include only associations between pharmaceutical compounds and single genes; predicted associations involving endogenous compounds and/or groups of genes are included in the supplement, however.</p><p>Top 20 predictions of new drug-gene relationships for PharmGKB, and whether a PGx relationship has been documented in the literature.</p

Classifier performance at the task of recognizing (a) PGx associations (dense matrix), (b) drug-target associations (dense matrix), (c) PGx associations (sparse matrix) and (d) drug-target associations (sparse matrix).

<p>Classifier performance at the task of recognizing (a) PGx associations (dense matrix), (b) drug-target associations (dense matrix), (c) PGx associations (sparse matrix) and (d) drug-target associations (sparse matrix).</p

Explanation of the clusters shown in Fig 4.

<p>Clusters with 20 or fewer members are not described in the table in the interest of space.</p

Top 20 predictions of new drug-target relationships for DrugBank.

<p>*** indicates that the drug has been shown experimentally to have modified the activity of the gene/protein</p><p>** means that the interaction is known to DrugBank but is listed under an alternate drug or gene name</p><p>* means the interaction has been studied and is unlikely; P refers to a particular type of parser error in which the ligand of a receptor is mistaken for that receptor; L refers to a lexicon error (see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004216#sec008" target="_blank">Discussion</a>).</p><p>Top 20 predictions of new drug-target relationships for DrugBank.</p

Example of a dependency graph for a Medline 2013 sentence.

<p>(a) The raw sentence. (b) The complete dependency graph for the sentence. (c) The dependency path connecting the gene CYP3A4 with the drug rifampicin. (d) A more compact representation of the dependency path.</p

Selected dependency paths and representative sentences.

<p>The drug and gene names flanking each path are bolded. Some key abbreviations are listed here: <i>appos</i>: appositional modifier, <i>amod</i>: adjectival modifier, <i>prep</i>: prepositional modifier (if <i>prep_of</i>, the specific preposition used is “of”, if <i>prep_to</i>, it’s “to”, if <i>prep_for</i>, it’s “for”), <i>nsubjpass</i>: passive nominal subject, <i>agent</i>: complement of passive verb, <i>dobj</i>: direct object of active verb, <i>nsubj</i>: noun subject of active verb.</p><p>Selected dependency paths and representative sentences.</p

Dendrogram illustrating the semantic relationships among 3514 drug-gene pairs.

<p>In this dendrogram, the leaves represent 3514 drug-gene pairs that co-occur in Medline sentences at least 5 times, and we have cut the dendrogram at various levels (illustrated by the red lines in the interior of the dendrogram) to produce the colored clusters shown around the edges. Drug-gene pairs that are known drug-target relationships from DrugBank are denoted by blue dots, and those that are known PGx relationships from PharmGKB are denoted by orange dots. The heights of the turquoise bars are proportional to how often the corresponding drug-gene pairs co-occur in Medline sentences (a proxy for how well-documented they are).</p