SenNet Interview Series: Nicola Neretti and Vidyani Suryadevara скачать в хорошем качестве

SenNet Interview Series: Nicola Neretti and Vidyani Suryadevara

In the eleventh episode of the SenNet Interview Series, we're joined by Dr. Nicola Neretti and Dr. Vidyani Suryadevara. In this interview, they discuss their landmark paper "SenNet recommendations for detecting senescent cells in different tissues" published in June 2024 in Nature. You can read the article in its entirety here: https://shorturl.at/Sfpj9 Dr. Nicola Neretti has been working on interdisciplinary projects which involve signal/image processing, and the modeling of biological systems at Brown University. His current focus is the application of high throughput techniques such as RNA-seq to study changes in the transcriptional network caused by genetic and environmental interventions that extend life span in model organisms. His most recent work includes the development of computational methods to detect age-associated chromatin changes and activation of transposable elements. Nerettilab website: http://nerettilab.com. Dr. Vidyani Suryadevara is an instructor in Radiology at the Rad/Molecular Imaging Program at Stanford University. She is also a member of the Wu Tsai Human Performance Alliance and the Wu Tsai Neurosciences Institute. You can find out more about Dr. Suryadevara here: https://med.stanford.edu/profiles/vid... ___________ The SenNet Interview Series is an anthology of video interviews with the researchers involved in the SenNet Consortium. In these interviews, scientists offer insights into their ongoing senescence research and initiatives within the Consortium. The Common Fund’s Cellular Senescence Network (SenNet) Program was established to comprehensively identify and characterize the differences in senescent cells across the body, across various states of human health, and across the lifespan. SenNet will provide publicly accessible atlases of senescent cells, the differences among them, and the molecules they secrete, using data collected from multiple human and model organism tissues. To identify and characterize these rare cells, SenNet will develop innovative tools and technologies that build upon previous advances in single cell analysis, such as those from the Common Fund’s Human Biomolecular Atlas Program and Single Cell Analysis Program. Lastly, SenNet aims to unite cellular senescence researchers by developing common terms and classifications for senescent cells. For more information, visit sennetconsortium.org.