As a Senior Medical Informaticist, Christopher supports the company’s Health Language solutions by providing physician documentation within the electronic medical record, along with integrating advanced technology, such as clinical natural language processing.

One of his greatest professional rewards is being able to help clients quickly and efficiently find and make use of pertinent information locked within their systems.

In his spare time, Christopher enjoys all seasons in the beautiful Colorado outdoors, playing guitar, beer, and the occasional boardgame with friends.

He earned his PhD from the University of Colorado with a major in Computational Bioscience and a Bachelor of Science degree from Baylor University with a major in Bioinformatics.

As an author, his publications include:

  • Cohen, K., Verspoor, K., Fort, K., Funk, C., Bada, M., Palmer, M., & Hunter, L. (2017). The colorado richly annotated full text (craft) corpus: Multi-model annotation in the biomedical domain, 1379–1394.
  • Funk, C., Cohen, K., Hunter, L., & Verspoor, K. (2016). Gene Ontology synonym generation rules lead to increased performance in biomedical concept recognition Journal of biomedical semantics, 7(1), 1–16.
  • Jiang, Y., Oron, T., Clark, W., Bankapur, A., D’Andrea, D., Lepore, R., Funk, C., Kahanda, I., Verspoor, K., Ben-Hur, A., & others (2016). An expanded evaluation of protein function prediction methods shows an improvement in accuracy Genome biology, 17(1), 1–19.
  • Funk, C., Kahanda, I., Ben-Hur, A., & Verspoor, K. (2015). Evaluating a variety of text-mined features for automatic protein function prediction with GOstruct Journal of biomedical semantics, 6(1), 9.
  • Funk, C. (2015). Recognition and normalization of terminology from large biomedical ontologies and their application for pharmacogene and protein function prediction. (Doctoral dissertation, University of Colorado Anschutz Medical Campus. Strauss Health Sciences Library).
  • Kahanda, I., Funk, C., Verspoor, K., & Ben-Hur, A. (2015). PHENOstruct: Prediction of human phenotype ontology terms using heterogeneous data sources F1000Research, 4.
  • Bada, M., Baumgartner Jr, W., Funk, C., Hunter, L., & Verspoor, K. (2014). Semantic precision and recall for concept annotation of text Proceedings of Bio-Ontologies, 30–37.
  • Kahanda, I., Funk, C., Ullah, F., Verspoor, K., & Ben-Hur, A. (2015). A close look at protein function prediction evaluation protocols GigaScience, 4(1), s13742–015.
  • Funk, C., Hunter, L., & Cohen, K. (2014). Combining heterogenous data for prediction of disease related and pharmacogenes, 328–339.
  • Funk, C., Baumgartner, W., Garcia, B., Roeder, C., Bada, M., Cohen, K., Hunter, L., & Verspoor, K. (2014). Large-scale biomedical concept recognition: an evaluation of current automatic annotators and their parameters BMC bioinformatics, 15(1), 59.
  • Radivojac, P., Clark, W., Oron, T., Schnoes, A., Wittkop, T., Sokolov, A., Graim, K., Funk, C., Verspoor, K., Ben-Hur, A., & others (2013). A large-scale evaluation of computational protein function prediction Nature methods, 10(3), 221–227.
  • Sokolov, A., Funk, C., Graim, K., Verspoor, K., & Ben-Hur, A. (2013). Combining heterogeneous data sources for accurate functional annotation of proteins. In BMC bioinformatics (pp. S10).
  • Verspoor, K., Cohen, K., Lanfranchi, A., Warner, C., Johnson, H., Roeder, C., Choi, J., Funk, C., Malenkiy, Y., Eckert, M., & others (2012). A corpus of full-text journal articles is a robust evaluation tool for revealing differences in performance of biomedical natural language processing tools BMC bioinformatics, 13(1), 207.
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