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Martinaa1408/README.md

Hi, I'm Martina!

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Website


About me

  • Product Specialist at Onit, Cesena, in the team that builds healthcare data warehouses and Qlik Cloud dashboards
  • MSc in Bioinformatics (2026) and BSc in Biotechnology (2024), University of Bologna
  • MSc thesis at Neotron Laboratories: a decision support system for food contamination risk
  • Interested in data science for health, food safety and biology, and in teaching it

Skills

  • Data and BI: SQL, Qlik Cloud, data warehousing, dimensional modelling, dashboards
  • Programming: Python, R, Bash, Linux, Git
  • Statistics and machine learning: hypothesis testing, classification on imbalanced data, CNNs for medical images
  • Bioinformatics: sequence analysis, genome assembly and annotation, RNA-seq, DNA methylation, profile HMMs, protein structure
  • Wet lab: Western blot, flow cytometry, cryosectioning, immunohistochemistry

Certifications

  • AI Fluency: Framework and Foundations · Anthropic · 2026
  • Machine Learning Specialization · DeepLearning.AI and Stanford Online · 2026
  • Foundations of Data Science · Google · 2026
  • Introduction to KPIs: Measuring Success in Business · Coursera · 2026
  • Navigating U.S. Food Regulations: Safety and Enforcement · University of Illinois Urbana-Champaign · 2026
  • Nextflow Training Week · Seqera

Projects

Web

Personal website   HTML CSS JavaScript
Portfolio with my studies, thesis, internship, current role and CV.

Lab   HTML JavaScript
Browser tools on healthcare data, food safety, bioinformatics and teaching, built on simulated data.

Bioinformatics at Liceo Ferrari   HTML Python Colab
Slides, notebooks and a student toolkit for two orientation sessions at my former high school.

University

Skin lesion classification   Python PyTorch
Seven-class classification of dermatoscopic images (HAM10000) with EfficientNet-B0, class-weighted loss, Macro-F1 and Grad-CAM.

Yeast protein localization   Python scikit-learn
Machine learning pipeline on the UCI Yeast dataset to predict where a protein is located in the cell.

Signal peptide prediction   Python SVM Deep learning
Group project: data collection, feature analysis and models to predict secretory signal peptides.

Hybrid genome assembly   Illumina Nanopore RNA-seq
Assembly, annotation and transcriptomics of fungal isolates with bioplastic-degrading potential.

DNA methylation analysis   R minfi
Group project: Illumina 450K methylation pipeline.

Kunitz domain detection   HMMER Python
Profile HMM pipeline to find Kunitz-type protease inhibitor domains (Pfam PF00014).

Computational methods   Python Linux
Course notebooks and scripts on data structures, Linux and sequence alignment.

Popular repositories Loading

  1. LB2_project_Group_5 LB2_project_Group_5 Public

    Group project: data collection, feature analysis and models to predict secretory signal peptides.

    Jupyter Notebook 3 3

  2. DNARNA_Group4 DNARNA_Group4 Public

    Group project: Illumina 450K DNA methylation pipeline in R with minfi.

    HTML 2 2

  3. Martinaa1408.github.io Martinaa1408.github.io Public

    My personal website: studies, thesis, internship, current role and CV.

    HTML 1

  4. Kunitz_HMM_project Kunitz_HMM_project Public

    Profile HMM pipeline to find Kunitz-type protease inhibitor domains (Pfam PF00014).

    Jupyter Notebook

  5. ML_basic_project ML_basic_project Public

    Machine learning pipeline on the UCI Yeast dataset to predict protein subcellular localization.

    Jupyter Notebook

  6. Martinaa1408 Martinaa1408 Public

    My personal repository