Melax Tech, along with the San Diego Supercomputer Center at UC San Diego, announces the securing of a Phase I NIH SBIR contract focused on the development and enhancement of innovative user-focused informatic tools for use in basic and clinical research on infectious, immune and allergic diseases.
The Phase 1 contract, valued at $300,000, has been awarded by the National Institutes of Health (NIH) to develop a COVID-19 Dataset Knowledge Graph (COVID-DKG) to facilitate integrated analysis of heterogeneous COVID-19 data sets. The work is being done in partnership with the San Diego Supercomputer Center (SDSC), where researchers contribute experience gained in developing Knowledge Graphs by participating in the NSF Open Knowledge Network initiative, as well as other COVID-19 related projects.
Despite existing efforts making COVID-19 data sets available for research uses, the volume and the heterogeneity of COVID-19 data make it difficult for researchers to find, understand and reuse relevant data sets for their research purposes.
According to Dr. Jingcheng Du, director of Natural Language Processing (NLP) research at Melax Tech, when researchers want to conduct studies across domains, they often spend tremendous effort and time finding and learning about available data sources. “The COVID-DKG has built-in components that support semantic search, visualization and integrated online analysis on open COVID-19 data sets, thus facilitating research and development in combating the COVID-19 pandemic,” said Du.
Dr. Peter Rose, director of the Structural Bioinformatics Lab and lead for Bioinformatics and Biomedical Applications at SDSC, added, “Knowledge Graphs connect the dots by providing links among otherwise isolated COVID-19 data sets, enabling researchers to gain new insights. For example, a data set published by one journal may be joined with another data set in a different data repository to facilitate new types of analyses.”
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