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Center for Computational Biomedicine

The Center for Computational Biomedicine (CCB) at School of Biomedical Informatics aims to support biomedical discovery by developing, evaluating, and applying novel informatics methods and software to extract and analyze heterogeneous biomedical data. Led by Hua Xu, PhD, the CCB consists of faculty, staff, and students at SBMI. It is a unique research platform that fills in gaps between bioinformatics and clinical informatics research. Current research and service activities of CCB includes:

Healthcare Data Analytics

The CCB is actively promoting the secondary use of electronic health records (EHRs) for clinical and translational research by developing advanced informatics approaches. We are primarily focusing on natural language processing (Dr. Hua Xu (Biomedical Natural Language Processing Lab)) and ontology (Dr. Cui Tao) based approaches for EHR data extraction, normalization, and reasoning. The CCB is part of the BIG DATA initiative at SBMI.

Biomedical Literature Mining

The CCB has a long track record on developing information retrieval and literature-based discovery methods (led by Dr. Trevor Cohen). Such methods have been successfully used to infer cancer-related therapeutic relationships, as well as to support biomedical data interpretation in a number of applications.

Translational Bioinformatics

At the CCB, we also develop advanced bioinformatics approaches to support translational research. For example, Dr. Jim Zheng is developing advanced visualization technologies for 3D genomic structures and planning to apply it to clinical decision support systems. The CCB also provides individual data analysis and multiple data integration services (led by Dr. Jingchun Sun), such as genetic epidemiology data analysis, gene/microRNA expression data analysis, next generation sequencing data analysis, and network-based integrated analysis of heterogeneous data.