Englander Institute for Precision Medicine

Events

Mar
21
11:00am - 12:00pm
Dr. Jakob Nikolas Kather, M.Sc. | "Artificial Intelligence-based Biomarkers in Precision Oncology" (IPM Seminar Series Event) Bio: Dr. Kather is a physician scientist with board certification in internal medicine. He was recently appointed professor of Clinical Artificial Intelligence at Technical University Dresden, Germany. His interdisciplinary research team is working at the interface of computer science and precision oncology. The team is guided by an interdisciplinary idea: physicians are trained in data science and researchers from computer science or technical subjects learn to identify and solve clinically relevant problems. In the last year, the team's research studies were published in Nature Medicine and Nature Cancer, among other venues. Web: www.kather.ai Twitter/X: @jnkath, @katherlab
Dr. Jakob Nikolas Kather, M.Sc.
Apr
02
1:00pm - 2:00pm TBD
Gürkan Bebek, Ph.D., M.S. Assistant Professor Case Western Reserve University Center for Proteomics and Bioinformatics Graduate Program Director — Systems Biology & Bioinformatics MS Program Department of Nutrition Computer & Data Sciences Department Website: Gurkan Bebek
speaker photo
Apr
16
1:00pm - 2:00pm TBD.
Gürkan Bebek, Ph.D., M.S. Assistant Professor Case Western Reserve University Center for Proteomics and Bioinformatics Graduate Program Director — Systems Biology & Bioinformatics MS Program Department of Nutrition Computer & Data Sciences Department Website: Gurkan Bebek Abstract: "Unveiling the Complexity of Cancer: From Network Analysis to Personalized Medicine" Network analysis is revolutionizing our understanding of cancer, offering insights into its complex mechanisms and paving the way for personalized medicine. We will explore this multifaceted approach, beginning with its ability to decipher the functional consequences of specific mutations. Through the analysis of interactions within biological networks, we can discover how mutations, such as those in the APC gene in colorectal cancer, trigger cascading effects and interfere with cellular pathways. This understanding of dysregulated pathways forms the foundation for patient stratification. By analyzing network alterations in cancer patients, we can group individuals based on their unique pathway disruptions. Features discovered by frequent subgraph mining offer insights into the underlying disease mechanisms. This approach holds potential for both prognosis prediction and the development of tailored treatment strategies. As an example, we will explain discovering distinct patient groups in low-grade glioma using our unsupervised bottom-up approach. Specific subnetwork alterations both validate our approach and reveal previously unknown subgroups with distinct clinical needs. This exploration of network analysis in cancer research highlights its transformative power in unraveling the complexities of this disease and paving the way for more targeted therapies.
speaker photo

Weill Cornell Medicine Englander Institute for Precision Medicine 413 E 69th Street
Belfer Research Building
New York, NY 10021