Advancing the Microbiome Research Community

The human microbiome has become a recognized factor in promoting and maintaining health. We outline opportunities in interdisciplinary research, analytical rigor, standardization, and policy development for this relatively new and rapidly developing field. Advances in these aspects of the research community may in turn advance our understanding of human microbiome biology. It is now widely recognized that disturbances in our normal microbial populations may be linked to acute infections such as Clostridium difficile and to chronic diseases such as heart disease, cancer, obesity, and autoimmune disorders (Clemente et al., 2012). This has prompted substantial interest in the microbiome from both basic and clinical perspectives. Although our genome is relatively static throughout life, each of our microbial communities changes profoundly from infancy through adulthood, continuing to adapt through ongoing exposures to diet, drugs and environment. Understanding the microbiome and its dynamic nature may be critical for diagnostics and, eventually, interventions based on the microbiome itself. However, several important challenges limit the ability of researchers to enter the microbiome field and/or conduct research most effectively

Standardizing New Diagnostic Tests to Facilitate Rapid Responses to The Covid-19 Pandemic

In order to enhance the data interoperability, an expeditious and accurate standardization solution is highly desirable for naming rapidly emerging novel lab tests, and thus diminishes confusion in early responses to pandemic outbreaks. This is a preliminary study to explore the roles and implementation of medical informatics technology, especially natural language processing and ontology methods, in standardizing information about emerging lab tests during a pandemic, thereby facilitating rapid responses to the pandemic. The ultimate goal of this study is to develop an informatics framework for rapid standardization of lab testing names during a pandemic to better prepare for future public health threats. We first constructed an information model for lab tests approved during the COVID-19 pandemic and built a named entity recognition tool that can automatically extract lab test information specified in the information model from the Emergency Use Authorization(EUA)documents of the U.S. Food and Drug Administration (FDA), thus creating a catalog of approved lab tests with detailed information. To facilitate the standardization of lab testing data in electronic health records, we further developed the COVID-19 TestNorm, a tool that normalizes the names of various COVID-19 lab testing used by different healthcare facilities into standard Logical Observation Identifiers Names and Codes (LOINC). The overall accuracy of COVID-19 TestNorm on the development set was 98.9%, and on the independent test set was 97.4%. Lastly, we conducted a clinical study on COVID-19 re-positivity to demonstrate the utility of standardized lab test information in supporting clinical research. We believe that the result of my study indicates great a potential of medical informatics technologies for facilitating rapid responses to both current and future pandemics

In Silico Approaches and the Role of Ontologies in Aging Research

The 2013 Rostock Symposium on Systems Biology and Bioinformatics in Aging Research was again dedicated to dissecting the aging process using in silico means. A particular focus was on ontologies, as these are a key technology to systematically integrate heterogeneous information about the aging process. Related topics were databases and data integration. Other talks tackled modeling issues and applications, the latter including talks focussed on marker development and cellular stress as well as on diseases, in particular on diseases of kidney and skin