Services
This page describes working capability directions based on demonstrated research and repository artifacts. It does not claim an established consulting history, fixed service packages, or guaranteed outcomes.
Scientific data analysis
I can help organize and analyze experimental or biological datasets where the scope matches the documented experience on this site. Relevant work may include:
- data cleaning, reshaping, and exploratory review;
- statistical analysis in R;
- analysis of experimental, longitudinal, phenotypic, or genetic data;
- transparent interpretation with assumptions and limitations.
Reproducible analytical workflows
I can help turn repeated analytical work into a documented workflow that connects source data, methods, figures, outputs, and interpretation. Current demonstrated tools include R, Quarto, Markdown/QMD, Git, and structured source and claim management.
This is not a claim of regulated validation, formal compliance auditing, or enterprise data engineering.
Scientific visualization and communication
Current capability areas include publication-oriented scientific figures, multi-panel layouts, correlation and genetic-analysis graphics, methods documentation, figure captions, concise research narratives, and English-language scientific writing.
Quantitative biology and genetics
Documented specialist context includes controlled plant experiments, quantitative phenotyping, image and time-series measurement, genotype quality control, GWAS/QTL-oriented analysis, and candidate-region interpretation in maize research.
The scope does not include unverified breeding outcomes, field-trial delivery, clinical analysis, or broad production bioinformatics.
Research-facing tools
The Hydrotropism Analyzer demonstrates experience translating a scientific measurement problem into a repeatable research system and quantitative workflow. This site also demonstrates lightweight static technical publishing and evidence-control workflows. Application development is not presented as an established service because supporting source and deployment evidence has not been reviewed for public use.
Engagement
Useful starting information includes the scientific question, data type and structure, desired deliverable, existing code or figures, timing, and confidentiality constraints.
No claim is made here about clients, project volume, pricing, turnaround time, publication success, model performance, funding, or business outcomes.
Email [email protected] or review the contact guidance to discuss fit and scope.