"It was truly a pleasant surprise to receive the scholarship. I didn’t even know I was nominated," says Lisa Menacher.
Lisa Menacher’s journey into applying machine learning in biology began with a previous project under the same supervisor, as part of her international master’s programme in statistics and machine learning.
"I knew I wanted to continue working in biology, and the master’s thesis gave me an opportunity to build on my previous experience and to apply machine learning to an interesting field of study."
In her thesis, she focused on addressing complicated challenges in cancer treatment, particularly the problem of standard treatments often yielding different results for different individuals.
"Cancer is a very complex disease, and treatments often don’t work equally well for everyone. Precision medicine aims to account for biological differences between individuals."
Lisa Menacher used machine learning to analyse gene expression, a measurement of the activity of genes, that is often used for drug response prediction in cancer. Traditionally, gene activity is measured as an average from many cells simultaneously, which can obscure important details. She tested a method that seeks to extract information about individual cell types from such average measurements. However, the results showed that the method only slightly improved accuracy. Despite this, she remains hopeful.
"Biology is incredibly diverse. Future research could focus on specific cancer or tissue types, which might yield better results."
She also emphasised the challenge of working with limited datasets, meaning the information used to train AI models. In the medical field, obtaining large amounts of relevant data is often difficult. Another challenge for her was the time-consuming process of integrating and processing the data.
Freediving and Cooking
In her free time, she enjoys freediving and spends a lot of time cooking with friends. Originally from Germany, Lisa Menacher highlights the sense of community she has found through the international programme.
"Food often brings us together," she adds with a smile.
Collaboration between computer scientists and biologists
She has now begun a new chapter as a PhD student, transitioning to research in forensic medicine. Her project involves analysing small molecules in blood samples to investigate causes of death or times of death using machine learning. Although her new focus differs from her previous work in cancer research, she remains deeply interested in the combination of biology and computer science.
"There are so many collaborations between computer scientists and biologists combining these fields. I’m excited to see where it leads."
