Computational biologist and molecular microbiologist
with experience in bioinformatics, transcriptomics,
genomics, metagenomics, multi-omics data integration,
and reproducible computational workflow development.
Experienced in analysing large-scale sequencing datasets
and integrating transcriptomic, metabolomic, microbiome,
phenotypic, and environmental data to investigate complex
biological processes.
Strong programming and data-analysis experience in
Python and R, together with Linux, shell scripting,
high-performance computing, and scientific software
development.
02
Research & Professional Experience
Max Planck Institute for Chemical Ecology ·
Jena, Germany
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Developed and implemented computational workflows
for transcriptomic, metagenomic, metabolomic,
and integrative biological data analyses.
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Analysed RNA-seq datasets and performed
differential gene-expression and functional
analyses using R- and Linux-based workflows.
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Integrated transcriptomic, metabolomic,
microbiome, phenotypic, and environmental
datasets to investigate biological responses
across multiple molecular and organismal levels.
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Developed reproducible Python, R, and Bash
workflows for processing, analysing, and
visualising large biological datasets.
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Managed large sequencing datasets and
computational analyses in high-performance
computing environments.
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Applied statistical and machine-learning
approaches to identify biologically meaningful
patterns within complex datasets.
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Worked closely with experimental scientists
to connect computational results with
biological hypotheses and observations.
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Coordinated collaborative research activities
between scientists in Germany and Norway.
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Contributed to manuscripts, project reports,
scientific presentations, collaborative
proposals, and student supervision.
Masinde Muliro University of Science
and Technology (MMUST) · Kenya
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Conducted research in molecular biology,
microbiology, genomics, biotechnology,
and bioinformatics.
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Taught undergraduate and postgraduate courses
in molecular biology, microbiology,
biotechnology, and bioinformatics.
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Supervised undergraduate, MSc, and PhD
research projects.
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Guided students in experimental design,
biological data analysis, interpretation,
and scientific writing.
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Coordinated student research activities
and contributed to departmental and
collaborative research projects.
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Contributed to research proposal development
and organised workshops, seminars,
and practical bioinformatics training.
PhD in Molecular Biology / Microbiology
Friedrich Schiller University Jena · Germany
Research focused on plant–microbe interactions,
microbial molecular biology, genomics,
transcriptomics, stress responses,
and biological nitrogen fixation.
MSc in Biotechnology
Masinde Muliro University of Science
and Technology · Kenya
BSc in Biochemistry
Masinde Muliro University of Science
and Technology · Kenya
04
Selected Research & Software Projects
BOTAS — Bacterial RNA-seq Analysis Framework
Developed an end-to-end computational framework
for bacterial RNA-seq analysis, including sequence
alignment, gene-level quantification, operon
inference, and reproducible downstream analysis.
Work includes benchmarking using experimental
RNA-seq datasets with emphasis on reproducibility,
computational performance, transparent evaluation,
and usability.
View BOTAS on GitHub →
Multi-omics Integration
Integrated transcriptomic, metabolomic,
microbiome, phenotypic, and environmental
datasets to investigate plant defence responses
across ecological conditions.
Comparative & Evolutionary Genomics
Performed large-scale comparative genomic
and phylogenomic analyses of bacterial regulatory
and symbiosis-associated genes, incorporating
sequence processing, alignment, phylogenetic
inference, annotation, and comparative analysis.
Metagenomics & Microbiome Analysis
Developed and applied workflows for sequence
preprocessing, assembly, taxonomic classification,
functional annotation, comparative analysis,
and biological interpretation of complex
microbial communities.
Reproducible Computational Biology
Developed Python-, R-, Bash-, and Linux-based
workflows for biological sequence analysis,
quantitative processing, statistical evaluation,
visualisation, and reproducible research.
Computational Biology
RNA-seq
Transcriptomics
Genomics
Metagenomics
Comparative Genomics
Functional Genomics
Multi-omics Integration
Differential Expression
Genome Annotation
Phylogenomics
Programming, Statistics & Computing
Python
R
Bash
pandas
NumPy
scikit-learn
Statistical Modelling
Machine Learning
Data Visualization
Linux
HPC — SGE/Slurm
Git/GitHub
Conda
Docker
Bioinformatics Tools
DESeq2
edgeR
featureCounts
Salmon
Kallisto
HISAT2
Bowtie2
Trinity
SPAdes
Kraken2 / Bracken
BLAST / DIAMOND
MAFFT
IQ-TREE
Prokka
Panaroo
06
Scientific Software Development
BOTAS
Computational framework for reproducible
bacterial RNA-seq analysis, including alignment,
gene quantification, and operon analysis.
MLDockKit
Machine-learning-assisted computational toolkit
for molecular docking and biological data analysis.
Scientific Utilities
Development of additional Python-based utilities
for biological sequence analysis, quantitative
data processing, visualization, and reproducible
research workflows.
07
Research Coordination, Supervision & Communication
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Coordinated research implementation and
communication between collaborating scientists
in Germany and Norway.
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Supervised and supported undergraduate,
MSc, and PhD research activities.
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Contributed to collaborative research proposals
involving international partners.
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Organised scientific workshops, seminars,
and bioinformatics training activities.
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Experienced in scientific manuscript preparation,
technical documentation, research presentations,
and interdisciplinary scientific communication.
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Presented and communicated research findings
to multidisciplinary and international audiences.
08
Certification & Professional Development
Google Project Management Professional Certificate
Google / Coursera
Additional professional development in
bioinformatics, data science, artificial intelligence,
and scientific computing.
Computational Biology
Gene Regulation
Single-cell Genomics
Multi-omics Integration
Regulatory Networks
Transcriptomics
Functional Genomics
Systems Biology
Reproducible Bioinformatics
My scientific interests centre on computational
approaches for understanding how molecular and
regulatory changes give rise to complex biological
phenotypes.
I am particularly interested in integrating multiple
molecular layers to identify regulatory relationships
that cannot be resolved from individual datasets alone,
and in extending transcriptomic and multi-omics
approaches toward single-cell transcriptomics,
chromatin-accessibility data, and gene regulatory
network reconstruction.