# A Linked Data Application for Harmonizing Heterogeneous Biomedical Information
## 3 Initial Model and New Information Sources
### The Additional Biomedical Information Sources  
The list of additional data sources integrated with the updated knowledge model is reported in Table 2 which also includes a reference to the official website. The _Human Phenotype Ontology_ (HPO) provides a standardized vocabulary of phenotypic abnormalities found in human diseases. It currently includes over 13,000 terms and more than 156,000 annotations describing phenotypic anomalies divided into five sub-ontologies that classify anomalies, link them to diseases, describe the mode of inheritance, the modifiers of clinical symptoms, the clinical course, and the frequency of specific clinical features. The ontological scheme is developed by the _Monarch Initiative_, using medical literature to improve biomedical research on rare diseases [25]. \begin{table}
\begin{tabular}{l l l} \hline \hline
**Information Source** & **Format** & **Website** \\ \hline Human Phenotype Ontology (HPO) & OWL, OBO & hpo.jax.org \\ HPO-ORDO Ontological Module (HOOM) & OWL & bioportal.bioontology.org/ontologies/HOOM \\ Human Protein Atlas (HPA) & TSV & www:protein atlas.org \\ Drug–Gene Interaction Database (DGIdb) & TSV & www.dgidb.org \\ ChEMBL Database & RDF, SQL & www.ebi.ac.uk/chembl \\ \hline \hline \end{tabular}
\end{table} 
Table 2: List of additional biomedical information sources. Figure 1: Visual representation of the initial integration model. The _HPO-ORDO Ontological Module_ (HOOM) is an ontology that integrates ORDO information on rare diseases with HPO information on phenotypic anomalies. HOOM qualifies the annotations between clinical entities and phenotypic anomalies according to the frequency and integrates the notion of diagnostic criterion. HOOM is intended for researchers and pharmaceutical companies wishing to co-analyze associations of rare and common disease phenotypes. Being designed to integrate the information of two different models, it does not contain instances but only classes and relationships. The _Human Protein Atlas_ (HIPA) maps human proteins in cells, tissues, and organs using the integration of several omic technologies, including antibody-based imaging, mass spectrometry-based proteomics, transcriptomics, and systems biology [26]. It has contributed to thousands of publications in the field of human biology and disease and is recognized by the intergovernmental organization ELIXIR as a central European resource for the life science community. HPA consists of ten parts, each focusing on a particular aspect of the genome-wide analysis of human proteins. In particular, the _HPA Tissue Section_ has been used in this work. This section describes the expression profiles in human tissues of genes at both the _mRNA_ and protein levels. The protein expression data of 44 normal human tissue types is derived from antibody-based protein profiling using immunohistochemistry. Protein data covers 15,323 genes (i.e., 76% of protein-coding genes) for which antibodies are available. The mRNA expression data is derived from deep RNA sequencing (RNA-seq) from 256 different types of normal tissue. The _Drug-Gene Interaction Database_ (DGIdb) is a Web resource that provides information on drug-gene interactions and druggable genes from publications, databases, and other Web sources [27]. Data on drugs, genes, and interactions are normalized and merged into conceptual groups. In the current version (4.0), DGIdb includes 100,273 interaction statements and 33,577 druggable gene category claims. In total, it includes 10,606 druggable genes and 54,591 drug-gene interactions, covering 41,102 genes and 14,449 drugs. DGIdb is accessible via a Web-based search interface, an application programming interface (API), and is downloadable as a collection of TSV archives. The _ChEMBL_ database is a large open-access drug discovery database managed by the _European Molecular Biology Laboratory_ (EMBL). It is handled manually and has the purpose of capturing data and knowledge across the pharmaceutical research and development process.