About Education Experience Projects Skills Publication Contact Resume

Hi, this is I-Shu Wang

      A motivated graduate student major in Quantitative Biology and Bioinformatics at Carnegie Mellon University, with an expected graduation in Dec 2023. Complemented by a Master's degree in Biochemical Science and Technology from National Taiwan University. Offering a strong academic background and hands-on experience in genomic research, data analysis, and bioinformatics. Proficient in utilizing various computational tools and programming languages, including shell script, Python, Go, R, to derive meaningful insights from biological data. Seeking a full-time position to apply my skills and contribute to cutting-edge research in the field of bioinformatics.

Education

Dec 2023

Carnegie Mellon University

Pittsburgh, PA
Master of Science in Quantitative Biology And Bioinformatics

  • Current GPA: 4.01/4.33
  • Relative Courses: (* Fall Semester)
    • *Computational Molecular Biology and Genomics
    • Bioinformatics Data Integration Practicum
    • Data Analysis for Biological Sciences
    • Algorithms & Advanced Data Structures
    • Fundamentals of Bioinformatics
    • *Introduction to Deep Learning
    • Programming for Scientists
    • *Computational Medicine
    • Machine Learning

National Taiwan University

Taipei, Taiwan
Master of Science in Biochemical Science & Technology

  • Member of Food Chemistry Lab, supervised by Prof. Nan-Wei Su
  • Thesis: The effect of qdoI on the flavon-3-ol phosphorylation by Bacillus subtilis BCRC80517
  • Earned Excellence Award from 2020 Agricultural Chemical Society of Taiwan Annual Poster Competition Sessions

Jun 2020
June 2018

National Chung Cheng University

Chiayi, Taiwan
Bachelor of Science in Biomedical Science

  • Certificate in Functional Genomics Program
  • Relative Courses:
    • Introduction to Systems Biology
    • Introduction to Bioinformatics
    • Introduction to Biostatistics
    • Molecular Biology
    • Microbiology
    • Cell Biology
    • Biochemistry
    • Immunology
    • Virology
    • Genetics

Experience

Jan 2023 - Aug 2023

Graduate Researcher

Carnegie Mellon University

  • Analyzed extensive long-read RNA-seq data (PacBio, NanoPore) on a Linux platform to ascertain gene expression levels
  • Constructed a streamlined pipeline using Snakemake to analyze alternative splicing events within sequencing data and employed parallel programming techniques to significantly reduce at least 75% processing time with multiple samples
  • Designed and developed an interactive web application featuring a user-friendly dropdown menu interface for non-programmers to easily access and interpret data visualization figures

Research Assistant

NGS High Throughput Genomics Core, Academia Sinica

  • Created diverse sequencing libraries and managed Illumina sequencers, including HiSeq, MiSeq, and NextSeq, to acquire top-tier sequencing data
  • Conducted essential laboratory techniques such as qPCR, PCR, DNA and RNA purification, electropherogram analysis, and gel electrophoresis to produce high-quality sequencing libraries
  • Expertly demultiplexed sequencing data and employed Fastqc to meticulously assess the quality of sequencing data, ensuring data integrity
  • Fostered effective communication with customers, adeptly addressing their sequencing requirements and ensuring their complete satisfaction

Feb 2021 - Aug 2021
Aug 2018 - Jun 2020

Graduate Researcher

National Taiwan University

  • Earned Excellence Award from Agricultural Chemical Society of Taiwan Annual Poster Competition Sessions
  • Conducted DNA extractions from bacterial sources and conducted research utilizing BLAST and the NCBI database to engineer a plasmid for a gene knockout system
  • Employed CRISPR-Cas9 techniques to modify a specific enzyme genes in Bacillus subtilis and established a screening system to identify knockout strains and cultured bacteria for research purposes
  • Performed protein purification assays and quantified protein levels using ELISA
  • Operated High-Performance Liquid Chromatography (HPLC) and analyzed NMR and LC-MS-MS data to determine chemical compound structures

Teaching Assistant

National Taiwan University

  • Collaborated with a team of 4 to teach and train over 30 students to learn experiments
  • Designed project outline and moderated discussion for students’ final projects

Aug 2018 - Jan 2019
July 2015 - Aug 2015

Summer Intern for Research Assistant

Academia Sinica

  • Researched on Oncology to treated 2-deoxy-glucose to cancer cells, resulting in the level of heat shock protein and mitosis cycle changed
  • Tested protein level through western blotting, and processed immunofluorescence to visualize mitosis status

Projects

A python script for bacterial genome analysis

Carnegie Mellon University
Pittsburgh, PA
Oct 2022

  • Created a Python script that perform a series of processes from examining whole genomics for bacteria, translating DNA sequences to protein sequences, to using BLAST to compare the protein sequences
  • Scanned the sequence data to get the high potential Open Reading Frame sequences which length were longer than 600 pb and utilized Biopython to establish connections with BLAST and NCBI databases.
  • GitHub
  • Skill:
      Python, BioPython, BLAST, Bioconda

Data analysis and visualization on oncology data

Carnegie Mellon University
Pittsburgh, PA
Dec 2022

  • Conducted comprehensive statistical analysis on oncology data using Python, h arnessing the power of essential libraries such as SciPy, Pandas, NumPy, Seaborn, Statsmodels, Plotly, and Matplotlib
  • Employed advanced statistical techniques and data manipulation to derive actionable insights and trends, which were then effectively communicated through data visualizations
  • Skill:
      Python, Matplotlib, Statsmodels, SciPy, Seaborn, plotly, Jupyter Notebook

Simulation of intercellular viral infection via cell-to-cell transmission

Carnegie Mellon University
Pittsburgh, PA
Dec 2022

  • Contributed to the development of a dynamic simulation model in the Go programming language, enabling users to input critical parameters, including those related to drug or treatment strategies, derived from biological data
  • This user-centric model offered a powerful tool for individuals and researchers to assess the impact and efficacy of specific treatments in combating viral infections within host cells, with the assurance of rigorous unit testing for model accuracy and functionality.
  • Worked with team of 4
  • Skill:
      GO Language, Unit tests, Parallel Programming, Git

Construction of a Transcriptome Assembly and Annotation Pipeline

Carnegie Mellon University
Pittsburgh, PA
Apr 2023

  • Designed and implemented AnnoGenie, a genome annotation pipeline that harnessed evolutionary similarities between species to annotate the gray wolf genome. This achievement was realized by building and deploying the pipeline on Bridge2, a cloud-based high-performance computer, running under Linux
  • The pipeline's core components were scripted in shell scripting, involved utilizing tools such as FastQC, Trimmomatic, HISAT2, Samtools, StringTie, gffRead, and BLAST to create an innovative annotation approach. The project successfully bridged the gap for species lacking transcript assemblies and RNA-seq data, thereby facilitating efficient genome annotation in novel species.
  • Worked with team of 4.
  • Skill:
      High Performance Computing, Pipeline Construction, Shell Language, Genome Alignment, Genome Annotation

Analysis of differential gene expression and pathway enrichment in multiple cancers

Carnegie Mellon University
Pittsburgh, PA
Apr 2023

  • Utilized RNA-seq data from The Cancer Genome Atlas (TCGA) to analyze gene expression in 12 prevalent cancer types. Conducted differential gene expression analysis with DESeq2, revealing shared gene signatures across cancers. Employed Enrichr for pathway-based gene clustering and applied Fisher's method for further statistical analysis.
  • The project yielded insights into common molecular pathways involved in cancer development and progression, with potential implications for targeted therapies and personalized treatments, ultimately contributing to enhanced patient outcomes in oncology
  • Worked with team of 4.
  • GitHub
  • Skill:
      TCGA database, DESeq2, Enrichr, Python, R

Frame-Level Speech Recognition

Carnegie Mellon University
Pittsburgh, PA
Sep 2023

  • Designed and implemented a multilayer perceptron (MLP) for frame-level speech recognition, predicting frame-level phonetic transcriptions from raw Mel Frequency Cepstral Coefficients (MFCCs). The MLP, developed using PyTorch, learned feature representations and nonlinear classification boundaries, with a focus on discriminating between phoneme class labels.
  • Operating within a limited parameter budget of 25MB, extensive optimization efforts were conducted, including testing different loss functions, architectures, and learning rates, aimed at achieving a high accuracy threshold of 90%. The entire model development and training process were processed on the Google Cloud Platform.
  • Skill:
      Pytorch, Google Cloud Platform, Cloud Computing, Deep Learning

Face Verification and recognition

Carnegie Mellon University
Pittsburgh, PA
Oct 2023

  • Developed position-invariant models, specifically Convolutional Neural Networks (CNNs), to handle variations in face positioning, essential in real-world scenarios.
  • Managed the model with a strict parameter limit of 21MB. Explored performance enhancements by modifying existing models and integrating renowned architectures like ResNet and DenseNet. This endeavor aimed to elevate accuracy and achieve superior results in face recognition and verification tasks.
  • Skill:
      Pytorch, Google Cloud Platform, Cloud Computing, Deep Learning, CNN

Skills

Programming Language

Python, R, GO Language, SQL, Shell script

Computational Skills

Experience in Git, paralle programming, linux enviornment, AWS, Google Cloud Platform, Jupyter Notebook

Bioinformatics Tools

NCBI, BLAST, TCGA, Snakemake, Bioconductor, BioPython, DESeq2, Enrichr, various alignment and annotation tools

Data Analysis Packages

Numpy, Pandas, SciPy, Seaborn, Statsmodels, plotly, ggplot, Matplotlib, Scikit-Learn, Pytorch, dash, RShiny

Publication

  • Wang, C.W., Tsai, H.Y., Hsu, C., Hsieh, C.C., Wang, I.S., Chang, C.F., & Su, N.W. (2024). Structure-specific metabolism of flavonol molecules by Bacillus subtilis var. Natto BCRC 80517. Food Chemistry, 136975–136975. https://doi.org/10.1016/j.foodchem.2023.136975

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