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Biomedical Big Data Revolution | Dr. Stefan Bekiranov | TEDxRVA 

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Find a cure for cancer from the comfort of your living room while in your PJs. It’s more possible today than it was a short time ago. We are currently undergoing a revolution in the field of biomedical research that will enable tailoring preventative strategies and therapies directly for each patient--Precision medicine. Systems Biologist, Stefan Bekiranov talks about what’s driving this revolution and how researchers are finding potential cures to diseases such as cancer at a faster rate than ever before.
This talk was given at a local TEDx event, produced independently of the TED Conferences. It was filmed and edited by Tijo Media at the Carpenter Theatre at Dominion Arts Center in Richmond, VA.
#medicalresearch #UVA #biomedical #bigdata #cancer #research #medicine
After receiving his Bachelor of Science in Electrical Engineering from UCLA, Dr. Stefan Bekiranov worked as a microwave engineer at Raytheon Electromagnetic Systems Division in Santa Barbara. He received his PhD in theoretical condensed matter physics from the University of California at Santa Barbara and went on to do postdoctoral research in statistical/condensed matter physics at the University of Maryland. After that, Dr. Bekiranov conducted more postdoctoral research in computational biology at The Rockefeller University. He pioneered the analysis of high-resolution genomic tiling array data as a Bioinformatics Staff Scientist at Affymetrix. He is now an Associate Professor at the University of Virginia School of Medicine working in the fields of epigenomics and systems biology and has published over 50 papers in peer-reviewed journals. The ultimate goal of his work is to arrive at improved therapeutic targets to treat and hopefully, one day, cure cancer.
This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at ted.com/tedx

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13 июн 2024

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Комментарии : 18   
@Biomeducated
@Biomeducated 5 лет назад
This dramatically reminds me to put more emphasis on learning R, to analyze my future transcriptomics data! Bioinformatics are becoming hugely important! Great talk!
@meeswt5976
@meeswt5976 5 лет назад
This is an amazing talk. I am majoring in Bioinformatics and I’m thinking of doing research medicine. His explanation helped me understand my undergraduate major more. Can’t wait to have my degree.
@rachanamuralinarayanan8484
@rachanamuralinarayanan8484 5 лет назад
I am planning to go for a Bionformatics degree as well. How intensive and stressful is this degree?
@DragonWarriorCodes
@DragonWarriorCodes 5 лет назад
I am a programmer currently self-studying Data Science and have great passion and desire to learn about bioinformatics .. if you recommend any place to start self-studying in this amazing field i would be really grateful.
@Biomeducated
@Biomeducated 5 лет назад
You should! Your skills will be very helpful in biomedical research! Go for it! ;)
@lifefan1
@lifefan1 3 года назад
@@Biomeducated Omg I am one of your subscribers.
@Biomeducated
@Biomeducated 3 года назад
@@lifefan1 cool! :D
@TheTobacko1
@TheTobacko1 Год назад
Invitae will lead this industry
@vijayarya2688
@vijayarya2688 Год назад
Thank you all very much
@iannimrod2726
@iannimrod2726 4 года назад
Our Bioinformatics teacher send us this video to understand better his course object. I think he accomplished that.
@visamap
@visamap Год назад
thank you all very much
@muhammad_awais_ijaz
@muhammad_awais_ijaz 6 лет назад
Great :)
@mechanical_engineering_passion
Amazing 😍
@V.K._.medico
@V.K._.medico 5 лет назад
Great
@pranavjain3905
@pranavjain3905 5 лет назад
great
@science_mbg
@science_mbg 7 лет назад
I wish to get the name of the protein that he was talking
@unintentional666
@unintentional666 6 лет назад
The protein is called Activin A according to the news from his University website. news.virginia.edu/content/uva-researchers-discover-key-lung-cancer-s-spread
@Asaagain
@Asaagain 2 года назад
What about Biologists going into Comp Bio without any CS background???? How would that transition work?
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