yun li

yun li

bioinformatician

About

* Ph.D. in Bioinformatics. * Years of work experience in bioinformatics, human genetics, neurology and microbiome. * Extensive research experience in computational methods and software development, NGS data analysis, microbiome, metabolomics, gene expression array, methylation array, SNP array and exome array analysis. * Skilled at project management, external communication, and team collaboration.

Country

united states

City

philadelphia

Industry

biotechnology

Skill

bioinformatics, computational biology, molecular biology, genomics, data analysis, r, systems biology, life sciences, genetics, microarray, metabolomics, metagenomics, microarray analysis, biochemistry, machine learning, sequence analysis, biostatistics

Experience

ucla semel institute for neuroscience and human behavior los angeles ca

postdoctoral fellow

ucla semel institute for neuroscience and human behavior los angeles ca

2011-9 - 2013-8 · 2 yrs
chinese academy of sciences shanghai institutes for biological sciences key lab of systems biology

phd student

chinese academy of sciences shanghai institutes for biological sciences key lab of systems biology

2006-8 - 2011-8 · 5 yrs 1 mo
university of pennsylvania department of biostatistics philadelphia pa

bioinformatician

university of pennsylvania department of biostatistics philadelphia pa

2015-5 - Present · 11 yrs 5 mos

* 1. Comparative metagenomics of microbial communities under formula and breast feeding * Study the effect of formula vs. breast feeding on the microbiome change, and perform repeated measurement design for infants from newborn to 5 month. * Build a QIIME-based pipeline for 16s meta-genomic data preprocessing and basic analysis, including OTU picking, alpha and beta diversity calculation, taxonomy summary. * Apply zero-inflated model on OTU count data for improving repeated measure analysis. * 2. Metabolomics study of Crohn’s disease * Build a workflow for metabolomics LS-MS untargeted data normalization and quality control * Given the metabolomics data at 4 time points for Control, EEN or anti-TNF treated patients, design a predictive model for identifying metabolic markers for the treatment outcome across time points.

Education

university of california, los angeles

university of california, los angeles

bioinformatics

2011-1 - 2013-1 · 2 yrs 1 mo
chinese academy of sciences

chinese academy of sciences

bioinformatics

2006-1 - 2011-1 · 5 yrs 1 mo
zhejiang university

zhejiang university

bioinformatics

2002-1 - 2006-1 · 4 yrs 1 mo

yun li's Contact Information

Email

******@***.com

Phone

(**) *** ****

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