This role has proven a great opportunity for me to develop inclusive research insights, Here I am responsible for implementing a hypothesis-driven approach to analyze Human Gene Expression (GTEx) data while demonstrating contributions of transcription activity to GTEx level which is subsequently accepted for the poster session at ASHG 2019. I carry out in-depth pathway enrichment analysis to integrate pathway information and multiple data modalities of cancer cells using single-sample Gene Set… Show more This role has proven a great opportunity for me to develop inclusive research insights, Here I am responsible for implementing a hypothesis-driven approach to analyze Human Gene Expression (GTEx) data while demonstrating contributions of transcription activity to GTEx level which is subsequently accepted for the poster session at ASHG 2019. I carry out in-depth pathway enrichment analysis to integrate pathway information and multiple data modalities of cancer cells using single-sample Gene Set Enrichment (ssGSEA). I align STRING's protein-protein Interaction (PPI) networks with drug targets to assess therapeutic efficacy on cancerous genes using a random walk with a restart algorithm. Perform cluster analysis of single-cell breast cancer RNA-seq data to compare treatment effectiveness. I formulate parsers to retrieve and re-format data from public databases such as patient genomic profiles from TCGA, GEO, and cancer cell line drug screening datasets from GDSC and CCLE.Following are some key contributions from this role:• Designed novel transfer learning model for predicting clinical drug sensitivity from cancer cell lines and deployed to TCGA, Patient-derived Xenograft (PDX), and clinical trial data; acknowledged for presidential poster award at PGRN-ASHG 2021.• Created and executed inclusive neural networks for anticipating drug response in cancer and explaining underlying cancer biology through signaling pathways; recognized as top 100 downloaded cancer papers in 2021.• Assessed performance of machine learning algorithm to predict cancer cells' responses to immunotherapies, chemotherapies, and targeted therapies.• Applied Machine Learning/Deep Learning to multi-omics for precision medicine• Completed and published two projects as well as submitted one for review.• Constructed Bayesian networks for the analysis of the causal relationship between the pro-coagulation activity of Mesenchymal stem cell and blood coagulation in trauma patients Show less

While acting as a Bioinformatics Analyst, I was accountable for offering data analysis service for physicians as well as conducting 16s RNA analysis workflow design from quality data filter, data comparison, to research result presentation. My role was remarkable in successful execution of microbiome analysis using QIIME. I efficiently leveraged non-negative matrix factorization algorithm for cancer survival prediction. Implemented algorithm for internal research projects such as using… Show more While acting as a Bioinformatics Analyst, I was accountable for offering data analysis service for physicians as well as conducting 16s RNA analysis workflow design from quality data filter, data comparison, to research result presentation. My role was remarkable in successful execution of microbiome analysis using QIIME. I efficiently leveraged non-negative matrix factorization algorithm for cancer survival prediction. Implemented algorithm for internal research projects such as using non-negative factorization for data integration analysis of multiple genomic data to predict cancer survival rate.Here is one of the key achievements from this position:• Troubleshot DNA sequencing issues and installed Python package (bcbio-nextgen) in Linux platform for RNA-seq data analysis. Show less

During this tenure, as a Bioinformatics Analyst, one of my primary tasks was to educate technicians and Ph.D. students on Python programming and next generation sequencing (NGS) data analysis. I gained all-inclusive acumen of statistical modeling primarily in differential expression analysis of RNA-seq data. I juxtaposed genetic differences among different drug-resistant tuberculosis isolates. My exceptional collaborative skills enabled me to work with wet-lab researchers responsible for… Show more During this tenure, as a Bioinformatics Analyst, one of my primary tasks was to educate technicians and Ph.D. students on Python programming and next generation sequencing (NGS) data analysis. I gained all-inclusive acumen of statistical modeling primarily in differential expression analysis of RNA-seq data. I juxtaposed genetic differences among different drug-resistant tuberculosis isolates. My exceptional collaborative skills enabled me to work with wet-lab researchers responsible for validating results to select highly confident variants. I cooperated with Taiwan CDC's scientists to source potential variants.Here are a couple of accomplishments from this role:• Developed automatic variant calling pipelines for DNA-seq data, resulting in producing two journal papers, one user manual, and one tutorial document.• Processed large-scale sequencing data (DNA-seq and RNA-seq) and utilized bioinformatics tools for variant detection, and differential expression analysis.I also have additional experience in the following roles:Graduate Research Assistant, National Chi Nan University, Nantou, TaiwanGraduate Research Assistant, Biomedical Instrument and Sensor Lab, National Chi Nan University, Nantou, Taiwan Show less