Biology subjects

Matentzoglu, N.

Publications and source records attributed to Matentzoglu, N..

2 recordsLinked to original sources

bioRxiv2020

KG-COVID-19: a framework to produce customized knowledge graphs for COVID-19 response

Integrated, up-to-date data about SARS-CoV-2 and coronavirus disease 2019 (COVID-19) is crucial for the ongoing response to the COVID-19 pandemic by the biomedical research community. While rich biological knowledge exists for SARS-CoV-2 and related viruses (SARS-CoV, MERS-CoV), integrating this knowledge is difficult and time consuming, since much of it is in siloed databases or in textual format. Furthermore, the data required by the research community varies drastically for different tasks - the optimal data for a machine learning task, for example, is much different from the data used to populate a browsable user interface for clinicians. To address these challenges, we created KG-COVID-19, a flexible framework that ingests and integrates biomedical data to produce knowledge graphs (KGs) for COVID-19 response. This KG framework can also be applied to other problems in which siloed biomedical data must be quickly integrated for different research applications, including future pandemics. BIGGER PICTUREAn effective response to the COVID-19 pandemic relies on integration of many different types of data available about SARS-CoV-2 and related viruses. KG-COVID-19 is a framework for producing knowledge graphs that can be customized for downstream applications including machine learning tasks, hypothesis-based querying, and browsable user interface to enable researchers to explore COVID-19 data and discover relationships.

bioinformatics↗

bioRxiv2020

The Planarian Anatomy Ontology: A resource to connect data within and across experimental platforms

As the planarian Schmidtea mediterranea (Smed) gains popularity as a research organism, the need for standard anatomical nomenclature is increasingly apparent. A controlled vocabulary streamlines data annotation, improves data organization, and enhances cross-platform and cross-species searchability. We created the Planarian Anatomy Ontology (PLANA), an extendable framework of defined Smed anatomical terms organized using relationships. The most current version contains over 800 terms that describe Smed anatomy from subcellular to system-level across all life cycle stages, in intact animals, and regenerating body fragments. Terms from other anatomy ontologies were imported into PLANA to promote ontology interoperability and comparative anatomy studies. To demonstrate the utility of PLANA for data curation, we created web-based resources for planarian embryogenesis, including a staging series and molecular fate mapping atlas, as well as a searchable Planarian Anatomy Gene Expression database, which integrates a variety of published gene expression data and allows retrieval of information of all published sequences associated with specific planarian anatomical regions. Finally, we report methods for continued curation of PLANA, providing a path for expansion and evolution of this community resource. Summary StatementWe report construction of an anatomy ontology for an emerging research organism and show its use to curate and mine data across multiple experimental platforms.

developmental biology↗