Detection of gene annotations and protein-protein interaction associated disorders through transitive relationships between integrated annotations

Abstract

BackgroundIncreasingly high amounts of heterogeneous and valuable controlled biomolecular annotations are available, but far from exhaustive and scattered in many databases. Several annotation integration and prediction approaches have been proposed, but these issues are still unsolved. We previously created a Genomic and Proteomic Knowledge Base (GPKB) that efficiently integrates many distributed biomolecular annotation and interaction data of several organisms, including 32,956,102 gene annotations, 273,522,470 protein annotations and 277,095 protein-protein interactions (PPIs).ResultsBy comprehensively leveraging transitive relationships defined by the numerous association data integrated in GPKB, we developed a software procedure that effectively detects and supplement consistent biomolecular annotations not present in the integrated sources. According to some defined logic rules, it does so only when the semantic type of data and of their relationships, as well as the cardinality of the relationships, allow identifying molecular biology compliant annotations. Thanks to controlled consistency and quality enforced on data integrated in GPKB, and to the procedures used to avoid error propagation during their automatic processing, we could reliably identify many annotations, which we integrated in GPKB. They comprise 3,144 gene to pathway and 21,942 gene to biological function annotations of many organisms, and 1,027 candidate associations between 317 genetic disorders and 782 human PPIs. Overall estimated recall and precision of our approach were 90.56 % and 96.61 %, respectively. Co-functional evaluation of genes with known function showed high functional similarity between genes with new detected and known annotation to the same pathway; considering also the new detected gene functional annotations enhanced such functional similarity, which resembled the one existing between genes known to be annotated to the same pathway. Strong evidence was also found in the literature for the candidate associations detected between Cystic fibrosis disorder and the PPIs between the CFTR_HUMAN, DERL1_HUMAN, RNF5_HUMAN, AHSA1_HUMAN and GOPC_HUMAN proteins, and between the CHIP_HUMAN and HSP7C_HUMAN proteins.ConclusionsAlthough identified gene annotations and PPI-genetic disorder candidate associations require biological validation, our approach intrinsically provides their in silico evidence based on available data. Public availability within the GPKB (http://www.bioinformatics.deib.polimi.it/GPKB/) of all identified and integrated annotations offers a valuable resource fostering new biomedical-molecular knowledge discoveries.

Integration and Querying of Genomic and Proteomic Semantic Annotations for Biomedical Knowledge Extraction

“…Thus, it allows subsequently using such associations for biomedical knowledge discovery (e.g. by transitive relationship inference [30], optionally involving also the synthesized entries).…”

“…a gene concept OID). Furthermore, new entries can be inferred from the integrated data [30]. The Inferred attribute in the integrated tables is used to keep track of the inference method employed, if any, to derive an entry.…”

“…Furthermore, the GPDW integrates 626,516 valuable interaction data from IntAct between different biomolecular entities, including 609,864 protein-protein interactions. In addition, the GPDW contains 3,616,108 semantic annotations of 988,899 genes which we recently detected by transitive relationship from the integrated annotations of the proteins that these genes encode; the semantic processing that we used to this purpose is thoroughly illustrated and discussed in [30].…”

“…Full provenance information for each retrieved association (annotation or interaction) is provided. When annotations are inferred by transitive relationships [30], an additional window provides the available annotations on which each inferred annotation is based. All extracted data can be downloaded in text format for their easy further use.…”

Preface: BITS2014, the annual meeting of the Italian Society of Bioinformatics

“…Masseroli et al [ 14 ] describe the Genomic and Proteomic Knowledge Base (GPKB), a global bioinformatics repository to detect and complement biomolecular annotations and candidate protein-protein interactions (PPI)-associated disorders. GPKB includes many distributed biomolecular annotation and interaction data of several organisms, such as 1,566,842 gene annotations, 91,581,198 protein annotations and 209,674 PPIs.…”