Technical Knowledge Intermediate 2 years experience
Summary
Strong foundation in Bioinformatics with experience implementing core algorithms for genomic analysis. Built custom implementations of pattern matching and multiple sequence alignment algorithms in Python.
How I Apply This Skill
- Implemented KMP pattern matching algorithm achieving 32% speedup over brute force on genomic data
- Built custom ClustalW multiple sequence alignment using dynamic programming and sum-of-pairs scoring
- Analyzed the Sorangium Cellulosum genome (71% GC content) to understand algorithm performance characteristics
- Debugged complex infinite loop issues in progressive alignment traceback algorithms
- Built an interactive 3D protein structure viewer in Dash with drag-and-drop
.pdb/.cifupload and on-demand RCSB PDB fetching by 4-character ID - Parsed multi-chain structures with HETATM handling for cofactors and ligands (validated on 4HHB hemoglobin: ~4,800 atoms, 4 chains, heme groups)
- Computed a Ramachandran plot from backbone φ/ψ dihedral angles alongside per-chain residue/atom counts and amino acid composition
Key Strengths
- Sequence Analysis: Pattern matching, multiple sequence alignment, genomic data processing
- Algorithm Implementation: KMP, ClustalW, dynamic programming tables, traceback algorithms
- Python Libraries: BioPython, Bio.SeqIO, NumPy for biological data manipulation
- Performance Analysis: Algorithm complexity comparison, benchmarking on real genomic data
- Biological Interpretations: Understanding sequence significance, GC content implicaitons