Dr Heba Sailem has won the Swiss Institute of Bioinformatics Early Career Bioinformatician Award for her work on inferring context-dependent gene functions. Heba was awarded a Sir Henry Wellcome Research Fellowship to develop a machine-learning approach that allows automated linking of microscopy-based phenotypes to gene functions. Her method was published in the leading journal Molecular Systems Biology in 2020.

Heba says: “Analysis of large-scale genetic screening datasets has been a long-standing problem in the field of bioinformatics. These datasets were greatly underutilised owing to challenges in interpreting analysis results. By developing a machine-learning approach that integrates our existing knowledge of gene functions, I was able to implement an intelligent system that generates hypotheses on the meaning of certain biological phenotypes observed under the microscope.”

Her work opens up many new ways to study gene functions, enabling systematically predicting gene functions associated with a specific tissue type or disease. For example, it revealed a new role for the genes responsible for our smell-sensing in the nose in colorectal tissue organisation which correlate with cancer progression. Heba explains: “Currently, gene ontologies provide the most standardised database of gene functions. Despite the intensive use of this database in interpreting large biological datasets, gene ontologies suffer from huge limitations as they generally offer gene annotations independent of tissue type or disease model.”

She continues, “I am very excited about the potential of this approach in advancing our understanding of cancer gene functions and finding new therapeutic targets”

Heba received her award at the hybrid Basel Computational Biology Conference in September.

Read Heba’s article Painting with Big Data, published in the July 2020 Sundial, here.