I. Core Bioinformatics & Computational Biology
1. Custom Bioinformatics Pipelines
What you get: End-to-end, reproducible workflows that turn raw data into publishable results
Perfect for:
- "I have sequencing data but lack bioinformatics infrastructure"
- "I need a standardized pipeline for my lab's recurring analyses"
- "I want to integrate multiple data sources for systems biology research"
Deliverables:
Fully documented Python/R pipelines with version control
Quality control reports and visualizations
Integration with NCBI, UniProt, PDB, Pfam, and custom databases
Training documentation for your team
2. AI & Machine Learning/Deep Learning for Biological Data
What you get: State-of-the-art ML/DL models that predict protein function, classify sequences, and extract patterns from high-dimensional biological data
Perfect for:
- "I want to predict peptide/protein activity without expensive wet-lab screening"
- "I need a custom classifier for my biological dataset"
- "I want to leverage deep learning for omics data analysis"
Deliverables:
Custom-trained models (TensorFlow, PyTorch, scikit-learn)
Feature engineering and dimensionality reduction
Cross-validation, hyperparameter optimization, and performance metrics
Model interpretation and biological validation
Production-ready code or web interface (optional)
3. Protein Structural Bioinformatics & Docking
What you get: Identify druggable pockets, predict binding affinities, and generate testable hypotheses for experimental validation
Perfect for:
- "I need to validate a therapeutic target computationally before wet-lab work"
- "I want to screen potential inhibitors against a protein target"
- "I need structural insights to design better experiments"
Deliverables:
High-quality 3D models using AlphaFold2/3
Structural analysis reports with PyMOL/ChimeraX visualizations
Protein-ligand docking results (AutoDock Vina) with binding affinity predictions
Publication-ready figures and biological interpretation
Recommendations for experimental validation
4. Viral Bioinformatics & Host–Pathogen Interaction
What you get: Deep insights into viral mechanisms, host interactions, and immune evasion strategies using cutting-edge immunoinformatics
Perfect for:
- "I'm studying a viral pathogen and need computational host-range prediction"
- "I want to identify viral proteins that evade immune responses"
- "I need comparative genomics and evolutionary analysis of viral strains"
Deliverables:
Viral protein characterization and functional annotation
ML-based prediction of immune evasion and molecular mimicry
Virus–host interaction networks
Phylogenetic and comparative genomics analysis
5. Proteomics & Omics Data Analysis
What you get: From raw mass spec or RNA-seq data to biological insights and publication-ready figures
Perfect for:
- "I have LC-MS/MS data and need differential protein expression analysis"
- "I need RNA-seq analysis with proper statistical validation"
- "I want to integrate transcriptomic and proteomic data"
Deliverables:
Complete LC-MS/MS proteomics analysis pipeline
RNA-seq differential expression analysis (DESeq2, edgeR)
Multi-omics data integration and visualization
GO enrichment and pathway analysis
Publication-quality figures and statistical reports
