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NicoHadas/README.md

Nicholas Hadaš

Bioinformatics @ Washington University in St. Louis

Website Google Scholar LinkedIn PyPI

My Research

My primary research interest is in developing deep learning frameworks to model cellular function and better understand disease pathogenesis. I create computational tools and employ machine learning to investigate disease mechanisms using biological and biomedical data.

Projects

  • CiliaTracks — Tracking, analysis and classification of particle trajectories
  • Airway Transcriptomics — GRN analysis using generative transformers
  • scAgent — Agentic system for single-cell data
  • Biomedical Informatics - EHR modeling

Popular repositories Loading

  1. Annovar_Tool Annovar_Tool Public

    Identifies Pathogenic Genes in Annovar Data

    Python

  2. CardiacArrest_Mortality_Predictive_Model CardiacArrest_Mortality_Predictive_Model Public

    Cardiac arrest predictive mortality model in ICU patients using the MIMIC-IV database

    Jupyter Notebook

  3. MRI_Brain_Tumor_Classification_CNN MRI_Brain_Tumor_Classification_CNN Public

    Convolution Neural Network model for automated multi-class classification of brain tumors using Kaggle MRI data

    Jupyter Notebook

  4. sc_Perturbation_Transformer sc_Perturbation_Transformer Public

    Transformer-based generative model to predict genome-wide expression changes, following unseen genetic perturbations

    Jupyter Notebook

  5. NicoHadas.github.io NicoHadas.github.io Public

    HTML

  6. scAgent scAgent Public

    Agentic AI system with self correction to probe our single-cell data

    Jupyter Notebook