Valeriia sherina

Presentation at Rocky 2018

Valeriia Sherina is presenting at Rocky 2018. Title: Fully Bayesian model for non-random missing data in qPCR. Abstract: We propose a new statistical approach to obtain differential gene expression of non-detects in quantitative real-time PCR (qPCR) experiments through Bayesian hierarchical modeling. We propose to treat non-detects as non-random missing data, model the missing data mechanism, and use this model to impute Ct values or obtain direct estimates of relevant model parameters.

Valeriia Sherina starts job at GSK

Congratulations to Valeriia Sherina on starting a new job at GlaxoSmithKline! She’ll be back in early 2019 to defend her thesis.

Valeriia Sherina receives William Jackson Hall Graduate Student Fellowship

Valeriia Sherina has been awarded the William Jackson Hall Graduate Student Fellowship. This merit-based fellowship recognizes Statistics doctoral students whose academic record reflects the major cornerstones of Jack Hall’s distinguished career. Recipients have distinguished themselves through outstanding performance in coursework and qualifying exams, excellence in their service as a graduate student teaching assistant, and timely completion of a dissertation containing work judged to be of particular significance in both its methodological contribution and potential impact in applications.

Valeriia Sherina wins an ENAR Distinguished Student Paper Award

Congratulations to Valeriia Sherina who won an ENAR Distinguished Student Paper Award for the 2018 ENAR Spring Meeting in Atlanta, GA. The award recognizes her paper entitled, Statistical Approaches to Decreasing the Discrepancy of Non-detects in qPCR Data. You can read the preprint here: https://www.biorxiv.org/content/early/2017/12/08/231621