A
Ali Shojaie
Researcher at University of Washington
Publications - 146
Citations - 3534
Ali Shojaie is an academic researcher from University of Washington. The author has contributed to research in topics: Graphical model & Estimator. The author has an hindex of 31, co-authored 132 publications receiving 2696 citations. Previous affiliations of Ali Shojaie include Fred Hutchinson Cancer Research Center & University of Michigan.
Papers
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Journal ArticleDOI
Penalized Likelihood Methods for Estimation of Sparse High Dimensional Directed Acyclic Graphs
Ali Shojaie,George Michailidis +1 more
TL;DR: In this paper, an efficient penalized likelihood method for estimating the adjacency matrix of directed acyclic graphs, when variables inherit a natural ordering, was proposed, and the adaptive lasso can consistently estimate the true graph under the usual regularity assumptions.
Journal ArticleDOI
Discovering graphical Granger causality using the truncating lasso penalty
Ali Shojaie,George Michailidis +1 more
TL;DR: This article proposes a novel penalization method, called truncating lasso, for estimation of causal relationships from time-course gene expression data, and provides information on the time lag between activation of transcription factors and their effects on regulated genes.
Journal ArticleDOI
Metabolomic Profiling Reveals Potential Markers and Bioprocesses Altered in Bladder Cancer Progression
Nagireddy Putluri,Ali Shojaie,Ali Shojaie,Vihas T. Vasu,Vihas T. Vasu,Shaiju K. Vareed,Srilatha Nalluri,Vasanta Putluri,Gagan Thangjam,Katrin Panzitt,Christopher Tallman,Charles Butler,Theodore R. Sana,Steven M. Fischer,Gabriel Sica,Daniel J. Brat,Huidong Shi,Huidong Shi,Ganesh S. Palapattu,Yair Lotan,Alon Z. Weizer,Martha K. Terris,Martha K. Terris,Shahrokh F. Shariat,George Michailidis,Arun Sreekumar,Arun Sreekumar +26 more
TL;DR: The metabolomic signature described offers potential as a urinary biomarker for early detection and staging of bladder cancer, highlighting the utility of evaluating metabolomic profiles of cancer to gain insights into bioprocesses perturbed during tumor development and progression.
Journal ArticleDOI
Using Twitter for Demographic and Social Science Research: Tools for Data Collection and Processing.
TL;DR: In this paper, the authors developed an accurate and reliable data processing approach for social science researchers interested in using Twitter data to examine behaviors and attitudes, as well as the demographic characteristics of the populations expressing or engaging in them.
Posted Content
Discovering Graphical Granger Causality Using the Truncating Lasso Penalty
Ali Shojaie,George Michailidis +1 more
TL;DR: In this article, a novel penalization method, called truncating lasso, is proposed for estimation of causal relationships from time-course gene expression data, which can correctly determine the order of the underlying time series, and improves the performance of the lasso-type estimators.