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Dr. Cleverson Matiolli, PhD

Data Scientist | Molecular Biologist | Machine Learning Expert

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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!

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