F
Fahad Saeed
Researcher at Florida International University
Publications - 87
Citations - 1556
Fahad Saeed is an academic researcher from Florida International University. The author has contributed to research in topics: Parallel algorithm & Cluster analysis. The author has an hindex of 16, co-authored 86 publications receiving 944 citations. Previous affiliations of Fahad Saeed include University of Illinois at Chicago & Western Michigan University.
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Journal ArticleDOI
Federated Learning: A Survey on Enabling Technologies, Protocols, and Applications.
TL;DR: A more thorough summary of the most relevant protocols, platforms, and real-life use-cases of FL is provided to enable data scientists to build better privacy-preserved solutions for industries in critical need of FL.
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ASD-DiagNet: A Hybrid Learning Approach for Detection of Autism Spectrum Disorder Using fMRI Data.
TL;DR: A framework called ASD-DiagNet for classifying subjects with ASD from healthy subjects by using only fMRI data is proposed and a joint learning procedure using an autoencoder and a single layer perceptron (SLP) which results in improved quality of extracted features and optimized parameters for the model.
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Proteome-Wide Measurement of Protein Half-Lives and Translation Rates in Vasopressin-Sensitive Collecting Duct Cells
Pablo C. Sandoval,Dane H. Slentz,Trairak Pisitkun,Fahad Saeed,Jason D. Hoffert,Mark A. Knepper +5 more
TL;DR: Understanding of the mechanisms underlying vasopressin signaling is extended and a correlation between protein function and protein half-life is indicated, in particular, processes that are rapidly regulated, such as transcription, endocytosis, cell cycle regulation, and ubiquitylation are associated with proteins with especially short half- lives.
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Dynamics of the G protein-coupled vasopressin V2 receptor signaling network revealed by quantitative phosphoproteomics
TL;DR: The data suggest that vasopressin can regulate an array of cellular functions well beyond its classical role in regulating water and solute transport, and greatly expand the current view of GPCR signaling in a physiological context.
Journal ArticleDOI
Identifying protein kinase target preferences using mass spectrometry
Jacqueline Douglass,Ruwan Gunaratne,Davis Bradford,Fahad Saeed,Jason D. Hoffert,Peter J. Steinbach,Mark A. Knepper,Trairak Pisitkun +7 more
TL;DR: A mass spectrometry-based method for profiling the target specificity of a given protein kinase as well as a computational tool for the calculation and visualization of the target preferences are presented.