Alexandr Kalinin

Alexandr Kalinin, Ph.D.

Ph.D. Program
Postdoctoral Fellow
Broad Institute of MIT and Harvard



  • Brian Athey
  • Ivo Dinov

Dissertation Title

Cell Nuclear Morphology Analysis Using 3D Shape Modeling, Machine Learning and Visual Analytics

Research Interests

Alex's research focuses on development of machine learning and computational methods for biomedical data analysis with the goal of improving disease diagnosis and treatment. During PhD training at DCMB, Alex worked on quantitative analysis of morphological changes in a cell nucleus associated with reorganization of chromatin architecture and related to altered functional properties such as gene regulation and expression. His contributions included the largest publicly available 3D microscopy imaging dataset for cell nuclear morphology analysis and classification; a new computational technique that combined mathematical surface modeling, machine learning, and interpretation of morphometric characteristics of cell nuclei and nucleoli in 3D; and development of visual analytics and deep learning techniques for the analysis of nuclear morphology data. Alex has also led publications of now highly-cited review articles on applications of deep learning in biomedicine and in pharmacogenomics, specifically. In 2019-2021, Alex has been an International Postdoctoral Fellow jointly at the Shenzhen Research Institute of Big Data, China and DCMB working with Brian Athey and Matthew O'Meara on the analysis of morphological changes in astrocyte nuclei induced by the treatment with valproic acid (VPA). This collaboration continues with the focus on the development of deep learning-based virtual staining techniques for 3D morphological analysis in transmitted-light cell images.

Key Publications

  • Kalinin AA, Allyn-Feuer A, Ade A, Fon GV, Meixner W, Dilworth D, Husain SS, de Wet JR, Higgins GA, Zheng G, Creekmore A, Wiley JW, Verdone JE, Veltri RW, Pienta KJ, Coffey DS, Athey BD, Dinov ID. 3D Shape Modeling for Cell Nuclear Morphological Analysis and Classification. Sci Rep. 2018; 8(1):13658. doi: 10.1038/s41598-018-31924-2. PMID: 30209281; PMCID: PMC6135819.
  • Kalinin AA, Higgins GA, Reamaroon N, Soroushmehr S, Allyn-Feuer A, Dinov ID, Najarian K, Athey BD. Deep learning in pharmacogenomics: from gene regulation to patient stratification. Pharmacogenomics. 2018; 19(7):629-650. doi: 10.2217/pgs-2018-0008. PMID: 29697304; PMCID: PMC6022084.
  • Ching T, Himmelstein DS, Beaulieu-Jones BK, Kalinin AA, Do BT, Way GP, Ferrero E, Agapow PM, Zietz M, Hoffman MM, Xie W, Rosen GL, Lengerich BJ, Israeli J, Lanchantin J, Woloszynek S, Carpenter AE, Shrikumar A, Xu J, Cofer EM, Lavender CA, Turaga SC, Alexandari AM, Lu Z, Harris DJ, DeCaprio D, Qi Y, Kundaje A, Peng Y, Wiley LK, Segler MHS, Boca SM, Swamidass SJ, Huang A, Gitter A, Greene CS. Opportunities and obstacles for deep learning in biology and medicine. J R Soc Interface. 2018; 15(141):20170387. doi: 10.1098/rsif.2017.0387. PMID: 29618526; PMCID: PMC5938574.
  • Kalinin AA, Hou X, Ade AS, Fon GV, Meixner W, Higgins GA, Sexton JZ, Wan X, Dinov ID, O'Meara MJ, Athey BD. Valproic acid-induced changes of 4D nuclear morphology in astrocyte cells. Mol Biol Cell. 2021; 32(18):1624-1633. doi: 10.1091/mbc.E20-08-0502. PMID: 33909457; PMCID: PMC8684733.