Andrew Lu on Muck Rack

Andrew Lu

As seen in: MSN Singapore, MSN Malaysia, Yahoo News Malaysia, Seeking Alpha, Cell Press, Digit, The Harvard Crimson, JD Supra, Lexology, MensXP.com and
This is my outlet for cheering on the Memphis Grizzlies, Roger Federer, and Carlos Sainz. Georgetown Law, '17. Princeton, '12.
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Articles

Pomona College to Host California Gubernatorial Debate

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By Andrew Lu
| claremontindependent.com
Pomona's Big Bridges auditorium (Photo Credit: Pomona College). Pomona College will host primary candidates for the California governorship in a debate on April 28, College President Gabi Starr announced earlier this month. The 90-minute debate will be hosted at 5:30 p.m. at Bridges Auditorium, which boasts a 2,400 person seating-capacity, with “students, faculty, staff, city and county leaders, distinguished guests and elected officials” expected to be in attendance.
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Man Wins First Place in Women’s 100m Dash at Pomona-Pitzer Track Meet

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By Andrew Lu
| claremontindependent.com
Curren (blue top) competing at Pomona's Strehle Track. (Photo Credit: 4fun) A video showing a man dressed up as a woman to compete in the Women’s 100-Meter Dash at a Pomona-Pitzer track meet went viral on Monday, garnering millions of views across social media platforms. Jonny Curren competed under the name “sara curren” [sic], outpacing 31 female runners to win first place by 0.02 seconds. “I had no idea that we’d run against a man until my teammates started sending me the video.
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FastGxC: Fast and Powerful Context-Specific eQTL Mapping in Bulk and Single-Cell Data

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By Lena Krockenberger, Andrew Lu, Mike Thompson, Cuining Liu
| biorxiv.org
Abstract Context-specific eQTLs mediate genetic risk for complex diseases. However, limitations in current methods for identifying these eQTLs have hindered their comprehensive characterization and downstream interpretation of disease-associated variants. Here, we introduce FastGxC, a method to efficiently and powerfully map context-specific eQTLs by leveraging the correlation structure in genomic studies with repeated sampling, e.g., single-cell RNA-sequencing.
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