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matiollipt/README.md

Dr. Cleverson Matiolli, PhD

Data Scientist | Molecular Biologist | Machine Learning Expert

LinkedIn GitHub Kaggle

Professional Overview

With over a decade of experience at the intersection of molecular biology and data science, I specialize in leveraging advanced machine learning techniques to unlock insights from complex biological data. My work focuses on developing innovative solutions for pressing challenges in bioinformatics and computational biology.

  • πŸ”¬ PhD in Genetics and Molecular Biology
  • πŸ’» Specialist in Machine Learning and Big Data
  • 🧬 Expert in bioinformatics and computational biology
  • 🌐 Experienced in multi-omics data integration and analysis

πŸ› οΈ Tech Stack

Python R PyTorch PyG TensorFlow Scikit-learn Pandas SQL RDKit Biopython NetworkX Knowledge Graphs

πŸ” Current Focus

  • πŸ“Š Analyzing biomanufacturing time series data
  • πŸ“Š Developing heterogeneous graph neural networks for protein function prediction (and for other cool applications as well...)
  • 🧠 Exploring advanced applications of Transformers in biological sequence analysis
  • 🌐 Integrating multi-omics data for comprehensive biological insights

πŸ† Key Projects

  • PROT2GO HGNN: A heterogeneous graph neural network for protein function prediction using Gene Ontology annotations
  • Custom Image Processing: Developed scripts for plant phenotyping and root analysis
  • Multi-omics Data Integration: Built pipelines for integrating various types of biological data

🌱 Advancing Agro and Biotech Through Data Science

My work lies at the crucial intersection of data science, agriculture, and biotechnology. I am passionate about harnessing the power of machine learning and bioinformatics to drive innovation in these vital sectors:

  • Crop Improvement: Utilizing genomic data and machine learning to accelerate crop breeding programs and enhance traits such as yield, disease resistance, and climate adaptability.
  • Precision Agriculture: Developing predictive models for optimizing resource use, pest management, and harvest timing based on multi-source data integration.
  • Biotech Innovations: Applying graph neural networks and knowledge graphs to uncover novel protein functions and potential targets for biotechnological applications.
  • Sustainable Solutions: Leveraging data-driven approaches to support sustainable farming practices and reduce environmental impact in agricultural systems.

I am committed to bridging the gap between cutting-edge data science techniques and real-world agricultural and biotechnological challenges. My goal is to contribute to a more sustainable, efficient, and productive future in these critical domains.

Let's connect and explore how we can push the boundaries of agro and biotech innovation through the power of data!

Popular repositories Loading

  1. matiollipt matiollipt Public

    Config files for my GitHub profile.

  2. GO-graph-EDA GO-graph-EDA Public

    Exploratory Data Analysis: Gene Ontology Directed Acyclic Multigraph

    Jupyter Notebook

  3. GO-graph-definition-text-transformer GO-graph-definition-text-transformer Public

    Fine-tunning text transformers with GO graph term definitions for classification and feature extraction (embedding)

    Jupyter Notebook

  4. sonar_nn_pytorch sonar_nn_pytorch Public

    Exploring sonar data to identify rocks and cilinders.

    Jupyter Notebook