01 — About
Genome to phenotype, in yeast
I study how yeasts gain, lose, and reshape the ability to use different carbon sources, and how machine learning can connect what is written in a genome to how a cell actually grows. My work draws on the Y1000+ dataset — a panel of 1,154 species spanning the Saccharomycotina subphylum — to ask how gene gain and loss shape metabolism, and to predict function in fungi that have never been studied in the lab. Lately that work centres on xylose, a sugar locked in plant biomass that only some yeasts have evolved to use.
Before Madison I trained as a plant breeder and quantitative geneticist, working on maize, cowpea, and other West African crops. That grounding in field genetics still shapes how I think about heritability, selection, and prediction.
Current focus. I ask why certain yeasts can utilize xylose better than others and how to engineer such cellular powerhouses into efficient chassis for biofuel production. Over 400 million years, xylose utilisation in yeasts has been gained and lost repeatedly, but a few wild species utilise xylose better than industry-engineered strains. I apply computational and statistical genetics coupled with machine learning and modelling approaches to understand the dynamic genetic rules that rewired xylose utilisation in more than 1,000 yeasts.
"The heights by great men reached and kept were not attained by sudden flight, but they, while their companions slept, were toiling upward in the night." — Henry Wadsworth Longfellow
02 — Research
What I work on
Comparative genomics, phylogenomics, and functional genetics of yeast metabolism — on a foundation of quantitative genetics and plant breeding.
A1 Machine learning on Y1000+
Classification models map gene-family (orthogroup) content onto carbon-source growth phenotypes across 1,154 species. Interpretable methods point back to the gene families that drive a trait, turning genome-scale patterns into testable candidates.
A2 Phylogenomics & evolution
Selection tests, ancestral-state reconstruction, and gene-tree-to-species-tree reconciliation trace how carbon-metabolism gene families were gained, lost, and modified across the subphylum.
A3 HXT & PMI40 genetics
CRISPR-Cas9 mutagenesis, growth-curve phenotyping, and sugar-uptake assays test how hexose transporters and mannose metabolism shape what a cell can eat.
A4 Quantitative genetics
Earlier work on combining ability and heterotic grouping in maize, genomic prediction, diversity panels, and selection scans in West African crops anchors how I think about heritability and prediction.
03 — Publications
Selected publications
Peer-reviewed articles. See my Google Scholar for the full, up-to-date list.
04 — Tools & Software
Open-source tools I build
Command-line tools for genomics — designed to be fast, reproducible, and easy to run.
gfc — Genome Format Converters
One command in place of a drawer of one-off scripts: 30 conversions across VCF, GFF3, GTF, BED, GenBank, FASTA, FASTQ, BAM, EIGENSTRAT, PLINK, MAF, MUMmer, HMMER, and Newick, behind one consistent set of flags with a batch mode. Each converter is benchmarked against the tool it replaces (convertf, plink2, AGAT, gffread, UCSC, EMBOSS, pyhmmer).
myconote — Fungal Annotation
A high-performance pipeline that carries a fungal genome from raw assembly to an NCBI-ready submission, with an integrated RNA-seq stack including allele-specific expression. 24 commands, 15 annotation sources, all 25 NCBI genetic codes, and a JSON reproducibility manifest per run. Ships as Docker and Singularity images plus a one-shot installer.
05 — Background
Education & teaching
Education
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2024 – presentPh.D., GeneticsDepartment of Genetics and Medical Genetics, UW–Madison · Hittinger Lab. Molecular and statistical genetics, computational biology.
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2024 – 2026M.Sc., GeneticsDepartment of Genetics and Medical Genetics, UW–Madison. Majors: mathematical modelling, machine learning, genomics and statistical genetics, and advanced matrix algebra.
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2021 – 2023M.Phil., Crop Science (Genetics & Plant Breeding)Department of Crop Science, University of Ghana. Combining ability and heterotic grouping of maize for resistance to maize streak virus.
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2015 – 2019B.Sc., Agriculture — First Class HonoursDepartment of Crop Science, University of Cape Coast.
Teaching & mentorship
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2016 – 2023STEM Teacher — Citadel Home Tuition, GhanaMathematics, Biology, Physics, and Chemistry.
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2019Teaching Intern — University of Cape CoastUndergraduate teaching, grading, and student supervision.
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OngoingFounder & Director — SparkSTEM FoundationSTEM outreach; Project Coordinator (Ghana), JR Biotek Foundation.
06 — News
Recent activity
07 — Skills
Methods & tools
What I use day to day, from the command line to the bench.