G
George Zaki
Researcher at University of Maryland, College Park
Publications - 34
Citations - 445
George Zaki is an academic researcher from University of Maryland, College Park. The author has contributed to research in topics: Multiprocessor scheduling & Image registration. The author has an hindex of 10, co-authored 33 publications receiving 288 citations. Previous affiliations of George Zaki include Johns Hopkins University & Cairo University.
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Journal ArticleDOI
Transcriptional Bursting and Co-bursting Regulation by Steroid Hormone Release Pattern and Transcription Factor Mobility
Diana A. Stavreva,David A. Garcia,Grégory Fettweis,Prabhakar R. Gudla,George Zaki,Vikas Soni,Andrew McGowan,Geneva Williams,Anh Huynh,Murali Palangat,R. Louis Schiltz,Thomas A. Johnson,Diego M. Presman,Matthew L. Ferguson,Gianluca Pegoraro,Arpita Upadhyaya,Gordon L. Hager +16 more
TL;DR: It is demonstrated that transcription factor (TF) nuclear mobility determines burst duration, whereas its bound fraction determines burst frequency, and a striking co-bursting pattern between TSs located at proximal and distal positions in the nucleus is uncovered.
Journal ArticleDOI
Dynamic imaging of nascent RNA reveals general principles of transcription dynamics and stochastic splice site selection.
Yihan Wan,Dimitrios G. Anastasakis,Joseph Rodriguez,Murali Palangat,Prabhakar R. Gudla,George Zaki,Mayank Tandon,Gianluca Pegoraro,Carson C. Chow,Markus Hafner,Daniel R. Larson +10 more
TL;DR: In this paper, a quasi-genome-scale platform for observing synthesis and processing kinetics of single nascent RNA molecules in real time is established, and all observed genes show transcriptional bursting.
Proceedings ArticleDOI
Applying graphics processor acceleration in a software defined radio prototyping environment
TL;DR: A new design flow is proposed that augments a popular existing SDR development environment (GNU Radio), with a dataflow foundation and a stand-alone GPU accelerated library, that gives an SDR developer the ability to prototype a GPU accelerated application and explore its design space fast and effectively.
Journal ArticleDOI
Laparoscopic stereoscopic augmented reality: toward a clinically viable electromagnetic tracking solution.
TL;DR: An integrated, compact, and EM tracking-based stereoscopic AR visualization system, which has the potential for clinical use, has been demonstrated to achieve clinically acceptable accuracy and latency.
Journal ArticleDOI
A cross-study analysis of drug response prediction in cancer cell lines.
Fangfang Xia,Jonathan E. Allen,Prasanna Balaprakash,Thomas Brettin,Cristina Garcia-Cardona,Austin Clyde,Austin Clyde,Judith D. Cohn,James H. Doroshow,Xiaotian Duan,Veronika Dubinkina,Yvonne A. Evrard,Ya Ju Fan,Jason D. Gans,Stewart He,Pinyi Lu,Sergei Maslov,Alexander Partin,Maulik Shukla,Eric Stahlberg,Justin M. Wozniak,Hyunseung Yoo,George Zaki,Yitan Zhu,Rick Stevens,Rick Stevens +25 more
TL;DR: In this paper, a multi-task deep neural network was used to predict drug response as a function of tumor and drug features across different studies, and the performance of a variety of machine learning models was evaluated.