Jun Yu

- siRNA related algorithm Development - Data Sciences, Machine Learning for Drug Discovery - Bioinformatics, Systems Biology, Pipeline Management, and Cloud Computing

- Cloud computing with AWS, Databricks, and Sequera Nextflow Tower - Data science, high performance machine learning algorithms for R&D - Domain algorithm development for siRNA therapeutics - Apply and develop tools to derive insights and testable hypotheses from large biological datasets - Drive data mining projects on in-house generated data - Provide biological interpretation for genetic, genomic and epigenetic associations derived from large scale human, animal and pathogen databases - Work collaboratively in a cross-functional team environment to provide conceptual input in experimental design. - Summarize, visualize, and communicate analyses and findings to key stakeholders. - Generate technical reports, prepare presentation slides, and improve existing analytics tools.

- Maintained, validated and implemented industrial level germline, somatic variant calling (with Sentieon), RNA-seq, ChIP-seq/ATAC-SEQ, single cell RNA-seq (10X genomics cellranger) pipelines using nextflow language. - Generated majority of the revenue for the company by performing regular and customized NGS projects for clients including Pfizer, Takeda, Memorial Sloan Kettering Cancer Center, and others. - Proficiency in creating reproducible workflows with Git, Gitlab, Jupyter/RMarkdown, docker, and cloud computing environments such as Amazon Web Services.

- Generated customized programming solutions, in collaboration with other principle investigators, to improve user interaction with available bioinformatics resources. - Developed and adapted computational tools to analyze and integrate high-throughput experimental data such as microarray, RNA-SEQ, CHIP-SEQ, ATAC-SEQ, whole genome and exome sequencing. - Performed statistical & functional analysis of the processed data in the field of transcriptome, epigenomes & cancer genomics. Conducted disease target discovery and validation with RNAi and CRISPR library screening. - Independently developed, implemented and maintained custom designed computational solutions relevant for ongoing lab-based projects. - Data mined on publicly available databases, including NCBI GEO, TCGA, UCSC Genome Browser, and ENCODE to gain the insight to explain the experimental results. - Interpreted, presented study results in support of laboratory members; collaborated in the publication of scientific papers.

- Investigated the signal mechanism of pulmonary arterial hypertension (PAH). - Used cells and tissues from patients and animal models to perform research (collaborate with Dr. Serpil Ezrum at Cleveland Clinic, OH and Dr. Nicolas Hill at Tufts Medical Center, Boston, MA). - Tested the cell penetrating peptides which regulate specific signal molecules to intervene the PAH development (Collaborate with Dr. Dale Mireke at Dartmouth College, NH) - Designed, analyzed and interpreted gene expression microarray, whole transcriptome sequencing and proteomics (Mass Spectrometry) assays. - As a faculty member of Genome Science Institute, actively worked with microarray resource core facility at Boston University Clinical and Translational Science and Center for Biomedical Mass Spectrometry at Boston Medical Center. - Reviewed grant applications for National Alzheimer’s Disease Society. - Instructed advance course on “Biochemical Mechanisms of Aging.”

- Investigated the role of angiotensin II in cardiovascular function by combining receptor mutagenesis and transgenic animal model. - Applied cell-penetrating peptides to specifically regulating receptor and kinase signaling. - Lectured, Biochemical Mechanisms of Aging (2006) and Biochemistry B (2004) Courses - Completed additional statistics courses from BU school of public health: SAS with Statistical Application, Introductory Statistical Computing, Intermediate Statistical Computing, Statistical Genetics, Design and Analysis of Microarray Experiments and Next Generation Sequencing.

- Identified functional motifs in receptors for bradykinin, angiotensin II and prostaglandin - Teaching assistant, Medical Student Biochemistry Lab (1999-2001)

School of Engineering coursework included: Mathematics for Information Systems; PC Architecture and System; Unix System/ C Programming; C++ & Object-Oriented Programing; Java & Object-Oriented Design; Data Structure; Computer Architecture; Network & Tele-communication; Operating System; Database Management System; Web programming (JavaScript, PHP/MySQL).