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Welcome to hegroup.org!


Welcome to the home page of Dr. Yongqun "Oliver" He's laboratory research group at the University of Michigan! We do both dry-lab (bioinformatics lab) and wet-lab (microbiology and immunology lab) biomedical research.

Our primary bioinformatics research has many topics: (1) Ontology development. Dr. He has initiated and led the development of several community-based ontologies, including Vaccine Ontology (VO), Ontology of Adverse Events (OAE), Ontology of Genes and Genomes (OGG), and Interaction Network Ontology (INO). We are also leading or participating in the development of several other ontologies. These ontologies can be used in many applications such as data integration and literature mining. (2) Ontology tool development. We have developed many ontology software programs, such as OntoFox and Ontobee, which are widely used for ontology reuse, ontology development, and ontology applications. (3) Literature mining, with a focus on ontology-based literature mining approaches. (4) Bayesian network (BN) modeling. BNs can model linear, nonlinear, combinatorial, and stochastic relationships among variables across multiple levels of biological organizations. We have developed new BN algorithms and tools for analysis of gene interaction networks using high throughput gene expression data.

The above and other bioinformatics approaches have been used primarily in the following research areas: (1) Vaccine Informatics. We have developed the VIOLIN vaccine database and analysis system. As a part of VIOLIN, we have developed Vaxign, the first web-based publically available vaccine target design tool based on bioinformatics analysis of genome sequences using the strategy of reverse vaccinology. logy. (2) Bioinformatics analysis of host-microbe interactions. We are interested in developing and applying bioinformatics methods to study the intricate interactions between host (e.g., human and mouse) and microbes (pathogens or bacterial microbiota). (3) Analysis of vaccine and drug adverse event mechanisms. We are interested in applying the Ontology of Adverse Events to study the mechanisms of vaccine and drug-induced adverse events.

Our wet-lab research is focused on the study of Brucella, a facultative intracellular bacterium that causes brucellosis, one of the most common zoonotic diseases in the world in humans and a variety of animal species. Our Brucella research has two focuses: (1) Uncover caspase-2-mediated cell death mechanism and its role in Brucella pathogenesis and immunity. Our studies first identified a new caspase-2-mediated proinflammatory cell death, which exists in macrophages and dendritic cells infected with live attenuated rough Brucella strains (e.g., B. abortus cattle vaccine RB51 and B. suis vaccine candidate VTRS1) (see references: Bronner, O'Riordan, and He, 2013; Li & He, 2012; Chen et al, 2011; Chen & He, 2009). This type of cell death is different from non-proinflammatory apoptosis or caspase-1-mediated proinflammatory pyroptosis, and so we named the cell death "caspase-2-mediated pyroptosis". Interestingly, virulent Brucella inhibits such cell death in infected macrophages (He et al, 2006) but not in dendritic cells (Li & He, 2012). Caspase-2 is critical in regulating cell death, DNA damage, stress, cancer, and microbial infections. Our research aims to continuously elucidate the caspase-2-mediated proinflammatory cell death pathway and its biological effect on microbial pathogenesis and protective immunity against brucellosis and other diseases. (2) Development of effective and safe Brucella vaccines potentially for human use. We are interested in applying reverse vaccinology and more effective adjuvant strategies for Brucella subunit vaccine research and development (R & D).

In a recent paper (He, 2014), Dr. He proposed a new One Network (OneNet) Theory of Life”. The OneNet Theory of Life states that the whole process of a life of an organism is a single complex and dynamic network (called “OneNet”). Ontologies and ontology-based bioinformatics tools, such as those introduced above, can be used to integratively represent and study such OneNet theory and OneNet knowledge of different organisms. The vaccine, adverse event, and Brucella research can be used as models to study the OneNet mechanisms.


 

Your suggestions and comments are welcome. Thank you.

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He Group
University of Michigan Medical School
Ann Arbor, MI 48109
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