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gary-malpartida/README.md

Hi, I'm Gary Malpartida

Biologist and research specialist with a background in molecular biology, genetics, epidemiology, laboratory quality, and scientific data analysis. My work sits at the intersection of biomedical research, public health, data-driven problem solving, and technical evaluation.

I use this GitHub as a portfolio of projects that reflect the way I work: structured, evidence-based, reproducible, and aligned with real-world scientific and analytical workflows.

Areas of Focus

  • Molecular biology and genetics
  • Epidemiology and public health data analysis
  • Laboratory quality control and validation
  • Scientific documentation and technical reporting
  • Biomedical data interpretation and research support
  • AI / LLM evaluation for scientific and healthcare-related domains

What You’ll Find in This GitHub

This profile brings together projects that demonstrate both domain expertise and analytical execution. Repositories are designed to reflect practical work in:

  • molecular and biomedical data analysis
  • epidemiological reporting and surveillance workflows
  • laboratory data validation and quality control
  • reproducible notebooks for scientific analysis
  • evaluation frameworks for AI-generated biomedical content

Technical Toolkit

Programming & analysis

  • Python
  • SQL
  • Excel / spreadsheet-based reporting

Python libraries and workflows

  • pandas
  • NumPy
  • matplotlib
  • Jupyter Notebook
  • data cleaning and exploratory analysis workflows

Scientific and operational strengths

  • molecular biology and genetics workflows
  • epidemiological data management and interpretation
  • laboratory quality processes and documentation
  • structured evaluation, annotation, and review of technical content

Featured Projects

Molecular Biology Data Analysis

A repository focused on organizing, cleaning, and analyzing molecular biology datasets using reproducible notebook-based workflows.

Epidemiology Surveillance Project

A public health analytics project centered on descriptive epidemiology, dataset cleaning, and surveillance-oriented reporting.

LLM Evaluation for Biomedical Responses

A structured evaluation framework for assessing AI-generated responses in biomedical and scientific contexts using scoring rubrics, prompt sets, and error categorization.

Laboratory Quality Control Tools

A collection of scripts and templates designed to support laboratory data validation, duplicate checks, missing-value review, and quality control reporting.

Bioinformatics Mini Pipeline

A lightweight bioinformatics workflow built to demonstrate sequence-oriented data handling, preprocessing, and summary reporting.

Scientific Data Reporting Portfolio

A portfolio repository containing concise scientific reporting examples, mini-analyses, and structured technical outputs for research and evaluation use cases.

Current Interests

I am particularly interested in projects related to:

  • AI training, evaluation, and quality review for scientific and healthcare domains
  • biomedical and public health data analysis
  • molecular biology and genetics support roles
  • technical annotation, benchmarking, and domain-specific evaluation
  • research operations, documentation, and analytical reporting

Working Style

I value:

  • reproducibility over one-off analysis
  • clarity in documentation
  • structured reasoning and traceable decisions
  • technically sound outputs that are easy to review, reuse, and scale

Contact

Thanks for visiting my GitHub.

Popular repositories Loading

  1. gary-malpartida gary-malpartida Public

  2. llm-evaluation-biomedical-responses llm-evaluation-biomedical-responses Public

    A reproducible framework for evaluating Large Language Model (LLM) responses in biomedical domains using structured criteria and Python-based analysis.

    Python

  3. biomedical-dataset-quality-assessment biomedical-dataset-quality-assessment Public

    Python-based biomedical data quality assessment workflow for dataset validation, quality metrics, visualization, and reproducible data quality reporting.

    Jupyter Notebook