Dimitry Shin

Assistant Professor


Pathology and Anatomical Sciences


E-mail


573-882-6940


Education

  • Ph.D., Biomedical Informatics, University of Missouri
  • M.Sc., Computer Science, Moscow State Academy of Computer Science and Engineering

Academic Appointments

  • Assistant Professor, Translational and Cancer Bioinformatics, Department of Pathology and Anatomical Sciences, School of Medicine, University of Missouri, Columbia, MO
  • Pathobiology Doctoral Faculty, Pathobiology Area PhD Program, Veterinary School, University of Missouri, Columbia, MO
  • Core Faculty, MU Informatics Institute, Graduate Studies, University of Missouri, Columbia, MO

Administrative Appointments

Director of Pathology Informatics/IT, Department of Pathology and Anatomical Sciences, School of Medicine, University of Missouri, Columbia, MO

Research Description

Dr. Shin studies computational methods in biomedicine. He leads the Translational and Cancer Bioinformatics laboratory in MU School of Medicine, supervising PhD students and posdoctoral fellows. His primary research area is advanced computerized inference methods in personalized medicine. In his most recent work, Dr. Shin introduced the field of computational morphoproteomics in which visual patterns of protein expression from WSI immunohistochemical studies are used to infer complex interplay of signal transduction pathways to design effective combinatorial therapies for theranostics.

Dr. Shin has also been leading the Informatics/IT division of MU Pathology and Anatomical Sciences department for over 10 years. Under his leadership, new computer systems have been designed, implemented and supported, including ANA, flow cytometry, bone marrow, molecular pathology laboratory information systems and biorepository software, pathology digital dictation system, and high definition microscopy telepathology system. He has been involved in many aspects of PAS department operations, including outreach medical examiners services, and development of electronic teaching materials for anatomy and pathology education.

Recently Dr. Shin has established Whole Slide Image Analytics laboratory, which provides services for researchers and medical practitioners. WSI lab members are currently developing online WSI hematopathology and histology atlases in collaboration with Dr. Richard Hammer, MD , Dr. Donald Doll, MD and Dr. Krause, PhD.

Interests

  • translational bioinformatics
  • personalized medicine
  • computational cancer biology
  • knowledge-driven imaging informatics
  • whole slide image analytics
  • machine learning, data mining and computational intelligence

Representative Publications

  1. Shin D*, Arthur G, Popescu M, Korkin D, Shyu C, Uncovering influence links in molecular knowledge networks to streamline personalized medicine. J Biomed Inform (2014), http://dx.doi.org/10.1016/j.jbi.2014.08.0034
  2. D. Shin*, E. Rogatsky, A. Stoyanov*, “Simultaneous monitoring of multiple transitions in mass spectrometric analysis improves limit of detection for low abundance substances in complex biological samples.” J Chromatograph Separat Techniq 4: 206. doi:10.4172/2157- 7064.1000206, 2014
  3. Chen Z, Shin D, Chen S, Mikhail K, Hadass O, et al. (2014) Histological Quantitation of Brain Injury Using Whole Slide Imaging: A Pilot Validation Study in Mice. PLoS ONE 9(3): e92133. doi:10.1371/journal.pone.0092133
  4. Orr Hadass, Brittany N. Tomlinson, Major Gooyit, Shanyan Chen, Justin J. Purd, Jennifer M. Walker, Chunyang Zhang, Andrew B. Giritharan, Whitley Purnell, Christopher R. Robinson, Dmitriy Shin, Valerie A. Schroeder, Mark A. Suckow, Agnes Simonyi, Grace Y. Sun, Shahriar Mobashery, Jiankun Cui, Mayland Chang*, Zezong Gu*, “Selective Inhibition of Matrix Metalloproteinase-9 Attenuates Secondary Damage Resulting from Severe Traumatic Brain Injury.”, PLOS One, 2013, 8:10
  5. D. Shin*, G. Arthur, C. Caldwell, M. Popescu, M. Petruc, A. Diaz-Arias, and C. Shyu, “A pathologist-in-the-loop IHC antibody test selection using the entropy-based probabilistic method,” Journal of Pathology Informatics, vol. 3, no. 1, p. 1, 2012.
  6. Multi-resolution tile-based follicle detection using color and textural information of follicular lymphoma IHC slides Han J., Shin D., Arthur G., Shyu C., BIBM, 2010