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Dr Heba Sailem Sir Henry Wellcome Research Fellow


Heba Sailem DPhil

Research Fellow


Heba's research is focused on developing innovative AI approaches to identify the genetic factors that regulate the organisation of cells in various contexts. In 2017, she was awarded a four-year Sir Henry Wellcome Research Fellowship to develop computer vision methods to knowledge-driven machine learning methods for analysing large bioimaging datasets.

Before joining Oxford University, she did her PhD at the Institute of Cancer Research in London in Computational Systems Biology. She studied Computer Information Systems for her bachelor’s degree and Data Warehousing and Data Mining for her master’s degree.

Google Scholar

Research Interests

  • Cellular imaging
  • Computational systems biology
  • Computer vision and machine learning
  • Data visualisation
  • Data integration

Current Projects

  • Knowledge-driven machine learning
  • Profiling of vascular networks
  • Cell tracking using deep learning

Research Groups

Related Academics

Primary Author

  1. Sailem H., Arias-Garcia M., Bakal C., Zisserman A., Rittscher J., (2017) Discovery of rare phenotypes in cellular images using weakly supervised deep learning, International Conference on Computer Vision Workshop.
  2. Sailem, H. and Bakal, C. (2017) Identification of clinically predictive metagenes that encode components of a network coupling cell shape to transcription by image-omics. Genome Research.
  3. Mardakheh, FK.*, Sailem, H.*, Kümper S., Tape CJ., Mccully R., Anjomani-Virmouni S., Jorgensen C., Poulogiannis G., Marshall CJ., Bakal, C. (2016). A global analysis of protein-protein colocalisations to reveal novel functional associations. Molecular BioSystems.
  4. Sailem, H., Sero, J., & Bakal, C. (2015) Visualizing cellular imaging data using PhenoPlot. Nature Communications. (Highlighted in Nature Methods)
  5. Sero, J.*, Sailem, H.*, Ardy, R., Almuttaqi, H., Zhang, T., & Bakal, C. Cell Shape and context regulate the nuclear translocation of NF-kappaB in breast epithelial and tumor Cells. Molecular Systems Biology.
  6. Sailem, H., Bousgouni, V., Cooper, S., & Bakal, C. (2014). Cross-talk between Rho and Rac GTPases drives deterministic exploration of cellular shape space and morphological heterogeneity. Open Biology.

*: The authors contributed equally

Ancillary Author

  1. Natrajan R., Sailem H., Mardakheh FK., Arias-Garcia M., Tape CJ., Dowsett M., Bakal C., & Yuan Y. (2016) Microenvironmental heterogeneity parallels breast cancer progression: a histology-genomic integration analysis. PLOS Medicine.
  2. Yin, Z., Sailem, H., Sero, J., Ardy, R., Wong, S., Bakal, C. (2014). How cells explore shape space: A quantitative statistical perspective of cellular morphogenesis. Bioessays.
  3. Yin, Z., Sadok, A., Sailem, H., McCarthy, A., Xia, X., Li, F., … Bakal, C. (2013). A screen for morphological complexity identifies regulators of switch-like transitions between discrete cell shapes. Nature Cell Biology.
  4. Garcia, M. A., Alvarez, M. S., Sailem, H., Bousgouni, V., Sero, J., & Bakal, C. (2012). Differential RNAi screening provides insights into the rewiring of signalling networks during oxidative stress. Molecular BioSystems.


  1. Nketiaa A., Sailem H., Rohdee G., Machirajub R., Rittscher J., (2017) Analysis of live cell images: Methods, tools and opportunities, Methods.
  2. Sailem, H., Cooper, S., Bakal, C. (2016). Visualizing quantitative microscopy data: History and challenges. Critical Reviews in Biochemistry and Molecular Biology.
  3. Evans, L., Sailem, H., Vargas, P. P., & Bakal, C. (2013). Inferring signalling networks from images. Journal of Microscopy.