Dr. Przytycka is a Senior Investigator in NLM's Computational Biology Branch. Her group develops computational methods facilitating progress in diverse areas of biomedical sciences: systems biology of cancer, gene regulation, single cell data analysis, drug development. Leveraging her collaborations with experimental biologists, she strives to bring advanced algorithmic techniques to biomedical research and to apply them in biomedically important settings.
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Transcript:
[Przytycka] "My research focuses on building computational methods to address problems in biomedical sciences, with particular interest in developing new methods to study diseases, with particular interest actually in cancer. Before, people were looking at diseases from the perspective of okay, her is a gene, something wrong happens to this gene and you have a disease. But complex diseases do not work this way. Usually something happens to this pathway, something happens to this process and, when something happens to this process, you have a disease. It's not so easy to identify the pathway when you look gene by gene because it may be that every individual participation, when you look from gene by gene perspective, is very small and it's hard to capture. But when you understand that you are to look at the pathway and group of genes the signal gets amplified and you may be able to identify processes that you wouldn't see if you would look at genes in isolation. So, we're trying to look at the diseases from the perspective of these regulated pathways. Some of our recent studies in cancer research are related to understanding the relationship between mutations, a patient may have, and say, drug response. Assume that we identify a pathway, we can ask the question, does the patient have a mutation in this pathway? And this gives us some way of predicting whether or not an individual will respond to a drug. Those questions are indeed very much driven by personalized medicine. I think that the goal would be some of the methods I developed would have a really lasting effect. And, also that some of the biological findings would be important to human health."