class ErfanZohrabi: def __init__(self): self.role = "MSc Bioinformatics @ University of Bologna" self.background = "BSc Cellular & Molecular Biology (GPA: 17.87/20)" self.focus = ["LLMs in Genomics", "Deep Learning for Biology", "Protein Language Models", "Multi-Omics Integration"] self.passion = "Decoding life's algorithms through AI & computation" def current_research(self): return { "genomics" : "DNA/Protein sequence classification with Deep Learning", "llm_bio" : "Large Language Models applied to biological sequences", "omics" : "Single-cell & multi-omics data integration", "ai_safety" : "Trustworthy AI in clinical genomics" }
| Domain | Technologies |
|---|---|
| Foundation Models | Transformers · BERT/GPT Architectures · Protein Language Models (PLM) |
| Genomic LLMs | DNABERT · AlphaFold · ESM · ProtTrans |
| Deep Learning | PyTorch · TensorFlow · CNNs · RNNs · Attention Mechanisms |
| Generative AI | VAEs · GANs · Diffusion Models · Sequence Generation |
| Graph Neural Nets | GNNs for PPI Networks · Molecular Graphs (CS224W Stanford) |
| NLP for Biology | Biomedical Text Mining · Drug Discovery · Sequence Tokenization |
┌────────────────────────────────────────────────────────────────────────┐
│ BIOINFORMATICS SKILL TREE │
├─────────────────────┬──────────────────────┬───────────────────────────┤
│ SEQUENCE ANALYSIS │ STRUCTURAL BIO │ OMICS & SYSTEMS │
│ ●くろまる DNA Classification│ ●くろまる Protein Folding │ ●くろまる scRNA-seq Analysis │
│ ●くろまる Sequence Alignment│ ●くろまる AlphaFold/PLM │ ●くろまる Multi-Omics Integration │
│ ●くろまる Promoter Analysis │ ●くろまる Signal Peptides │ ●くろまる Genomics + Proteomics │
│ ●くろまる Methylation (ILL) │ ●くろまる HMM Profiles │ ●くろまる Transcriptomics │
│ ●くろまる Variant Calling │ ●くろまる Domain Annotation │ ●くろまる Epigenomics │
├─────────────────────┼──────────────────────┼───────────────────────────┤
│ CLINICAL GENOMICS │ TOOLS & PIPELINES │ ML FOR BIO │
│ ●くろまる Pathogenicity Pred│ ●くろまる MEGA11 │ ●くろまる Random Forest │
│ ●くろまる ClinVar Analysis │ ●くろまる Biopython │ ●くろまる SVM / KNN │
│ ●くろまる PolyPhen / SIFT │ ●くろまる BLAST / HMMER │ ●くろまる Neural Networks │
│ ●くろまる Cancer Genomics │ ●くろまる Illumina Arrays │ ●くろまる PSO Optimization │
│ ●くろまる KCNB1 Variants │ ●くろまる Jupyter / RStudio │ ●くろまる LOOCV / Cross-Val │
└─────────────────────┴──────────────────────┴───────────────────────────┘
Breast Cancer Prediction
ML & DL classification of promoter DNA sequences for breast cancer prediction. Compared KNN, SVM (RBF), Neural Networks, and AdaBoost achieving 96.3% accuracy with PSO-optimized SVM.
SVM Neural Networks PSO KNN AdaBoost
ML for Genetic Variant Prediction
Random Forest model on ClinVar data to classify KCNB1 gene variants as pathogenic or benign. Benchmarked against PolyPhen and SIFT in-silico tools.
Random Forest LOOCV ClinVar PolyPhen SIFT
Illumina Infinium Array
Statistical analysis of fluorescent intensity data and methylation statuses from Illumina arrays using R. Covers probe characteristics, beta values, and differential methylation.
R Epigenomics Statistical Modeling Illumina
Protein Sequence ML Model
Predictive modeling of signal peptides in protein sequences using ML — critical for understanding protein secretion and subcellular localization.
Protein ML Signal Peptides Sequence Analysis
Lab of Bioinformatics Project
Built a Profile Hidden Markov Model (pHMM) for the Kunitz-type protease inhibitor domain — a rigorous structural bioinformatics exercise using HMMER and MSA.
HMM HMMER MSA Domain Annotation
Personal Research Website
Personal portfolio built with HTML/CSS/JS showcasing research, experience, and projects in bioinformatics, AI, and computational biology.
HTML CSS JavaScript GitHub Pages
| Year | Title | Journal |
|---|---|---|
| 2022 | Applications of Python Programming in Bioinformatics (Biopython) | Journal of Ghin |
| 2021 | Cancer Cell Cycle in Breast & Testicular Cancer | Journal of Ghin |
| 2020 | Targeted Drug Delivery for Cancer Treatment | Journal of Ghin |
🔬 ACTIVE RESEARCH AREAS
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🧬 Large Language Models (LLMs) for DNA/RNA sequence analysis
🔤 Protein Language Models (ESM, ProtTrans, AlphaFold integration)
🧠 Deep Reinforcement Learning for DNA sequence alignment
🕸️ Graph Neural Networks in Computational Biology
⚗️ AI + CRISPR: smart gene-editing target identification
🔬 Single-cell & Spatial Transcriptomics with Deep Learning
🌐 Multi-Omics Data Integration (Genomics + Proteomics + Transcriptomics)
🔒 Trustworthy & Interpretable AI for Clinical Genomics
🧪 Generative Models for Protein Sequence Design
🧲 Biomedical Text Mining for Drug Discovery
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
| Degree | Institution | Focus |
|---|---|---|
| MSc Bioinformatics | University of Bologna | ML, Deep Learning in Genomics, Multi-Omics, Structural Bio |
| BSc Cellular & Molecular Biology | University of Damghan | GPA: 17.87/20 · Genetics, Biostatistics, Programming |