Twitter. Snapchat. Facebook. WeChat. A phone call. A hug. A conversation over lunch. There are numerous ways we communicate. Either by instinct or trial and error, we learn some modes of communication are better for specific types of information, and some types of people. Enabling our learning are human cells we often take for granted: brain cells. These cells, and all cells in our body, also learn how to communicate with each other.
Cellular communication and an ability to switch modes of communication is particularly critical during processes of tissue growth and regeneration. Yet much about the way cells communicate and interact is still unknown. In this talk, I will share how we are developing and integrating methods in data science and visualization, modeling and experiments to interpret the way human cells communicate. Examples will be presented with applications to understanding how stem cells in the blood signal as they become cancerous, and how neural stem cells transform into neurons through intricate coordination of chemical, mechanical and electrical cell-cell communication. While studies have focused on one or two modes of cell communication, how the three are interconnected in differentiating cells: chemical signaling, spatial patterning and electrical activity, has yet to be well understood. The integrated quantitative-experimental work introduced in this talk is illuminating how hemopoietic cells develop malignancy, and how neural cells switch their modes of communication to form electrically functional neuronal networks – and ultimately how variations in cellular communication correlate to variability in daily measures of human behavior.
Amina received her PhD in Bioengineering from the University of California, Berkeley and UCSF, and a B.S. in Chemical Engineering from Rice University. Following her postdoctoral training in Biomedical Engineering at Johns Hopkins University, School of Medicine, she joined Rice University where she is an Assistant Professor in the Department of Bioengineering. Amina's research interests are in cellular systems biology. Her lab's research vision is to interpret human cells' communication during processes of growth and regeneration in order to understand and improve health. Towards this vision, the Qutub Lab develops coupled computational-experimental methods to analyze human cells and interpret cellular data. Amina served as scientific lead of the 2014-2015 DREAM Biomedical Big Data Algorithm Challenge to develop predictive algorithms for acute myeloid leukemia, and in 2017, co-launched the Texas Medical Center data workshops. Amina is a NSF CAREER and NSF Neural & Cognitive Systems awardee; and her research is supported by NSF, NIH, the Cancer Prevention Research Institute of Texas, the Kleberg Foundation and the Hamill Foundation. Amina is also cofounder of DiBS, an adaptive data visualization startup developing technologies to learn, present and interpret high-dimensional biomedical data.