⚠️ WARNING: This profile contains traces of genomics, questionable variable names, an unhealthy attachment to S. aureus, and a dangerous amount of Python. Proceed with caution.

🧾 TL;DR: Biochemist. Self-taught bioinformatician. I turn petabytes of pathogen genomes into things public health people can act on. Also I argue about football.

BSc Biochemistry from KNUST. Self-taught bioinformatician. I take huge messy sequencing data and turn it into insights people can actually use.

I break code and I fix code, and I will be honest, mostly I am touching things I should not be touching. It usually works out.

I am resilient regardless of what you say. I always think comeback. Because I am Culer💙❤️. Blaugrana💙❤️. That Barcelona. Yes, this is a bioinformatics profile and yes, that is relevant to my personality.

ESKAPEE pathogens are the reason I wake up. Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Enterobacter spp., and Escherichia coli. The whole resistance gang.

My favourite bug is S. aureus. Not because it is charming. Because its 2.9 MB genome fits comfortably inside my 500 GB storage, and I respect a pathogen that knows how to travel light.

Pathogenesis and virulence are my home turf. I want to know how these things cause damage, and how we catch them doing it.

I am actively seeking a PhD in Microbiology and Infectious Disease.

Here is the pitch in one line: I want to translate pathogen genomic data into clinical and public health action. Not just produce another figure. Not just deposit another assembly. Translate. From a FASTQ file sitting on a server to a decision someone can make about an outbreak, a treatment, or a resistance mechanism.

I bring the wet-side literacy of a biochemistry degree and the dry-side muscle of self-taught bioinformatics. I can talk to the microbiologist at the bench and to the person maintaining the cluster. I have shipped tools that other people use. I have broken things and fixed them and learned the difference.

If your lab works on ESKAPEE pathogens, antimicrobial resistance, virulence, or genomic surveillance, we should talk. I come with pipelines and opinions.

• StaphScope · unified MLST, spa, SCCmec, AMR, virulence, plasmid and capsule typing for S. aureus. MRSA's least favourite pipeline.

  

  

• EcoliTyper · nine analyses, one automated run. E. coli genotyping that finishes in minutes instead of your entire afternoon.

  

  

• AcinetoScope · seven analysis modules from FASTA to actionable report. Built for A. baumannii outbreak investigations and carbapenemase tracking.

  

  

• PseudoScope · MLST, PAST serotyping, AMR, virulence, and a visualisation dashboard for P. aeruginosa. Runs locally so your data stays your data.

  

  

• ESKAPE Web Platform · seven species pipelines behind one browser interface. Live at eskape.bio, built so people without a terminal can still use the tools.

  

  

• SAURUS · 134,299 S. aureus genomes, eleven typing and annotation modules, one queryable interface. Web at saurus-db.org, CLI at pip install saurus-cli.

  

  

• EnteroScope · tailored workflow for the Enterobacter cloacae complex. CREC analysis, HPC-friendly, mutation reporting included.

  

• ABYSS · A. baumannii genomic resource. Pasteur MLST, IC lineages, capsule typing, carbapenemases, metadata, and one-click accession export.

  

• ECLIPSE · E. coli surveillance resource. Stack filters by ST, phylogroup, serotype, or gene content and leave with a clean accession list.

  

• SAURUS-CLI · the terminal side of SAURUS. Query 134k genomes, filter by lineage and geography, export accessions. Bundled data, no API keys, no network calls.

  

• saurus-db.org · the domain and website behind SAURUS. Point, click, filter, export. The database's public face. saurus-db.org

  

ARGUS is Antimicrobial Resistance Genomic Unified Surveillance. One family of independent, open genomic surveillance sites, one per WHO priority ESKAPE pathogen. Accession-first, metadata-integrated, no login, no install, MIT licensed.

The current line-up: SAURUS for S. aureus, ECLIPSE for E. coli, ABYSS for A. baumannii. More siblings are planned. The goal is simple to say and annoying to build: ingest raw sequencing data, type it, cluster it, and surface outbreaks before they become headlines.

Watch the repos. It is going to be good.

• QIIME and the microbiome. Currently learning. The microbiome is humbling and I respect it.
• Python. Always Python. It is the one relationship that has lasted.
• AI, used properly. I am learning to use it better every single day instead of pretending I already do, which is the most honest sentence in this README.
• Football. See above. Blaugrana. No further questions.

Right now I am: learning microbiome analysis with QIIME, living in Python, and learning to use AI better every single day instead of pretending I already do. (Yes, it is repeated. It is that important.)