Bring a biological question. Build a computational plan.
A practical starting point for Arkansas investigators considering bioinformatics, multi-omics, AI/ML, reproducible workflow development, or Data Science Core collaboration.
Placeholder page · resources being addedStart by framing the project
Before choosing software, start with the scientific decision the analysis needs to support.
Biological questions
- What is the primary biological or clinical question?
- What comparison, phenotype, or outcome matters?
- What would count as a useful result?
- Is the goal discovery, validation, prediction, or mechanism?
Data readiness
- What data already exist, and in what format?
- How many samples, groups, time points, or replicates?
- What metadata are available?
- What is the intended manuscript, grant, software, or preliminary-data output?
Project areas
Genomics & transcriptomics
RNA-seq, WES/WGS, single-cell analysis, differential expression, variant workflows, and reproducible pipelines.
Proteomics & proteogenomics
Quantitative proteomics, pathway analysis, variant-peptide evidence, and multi-omics integration.
AI & machine learning
Predictive modeling, benchmarking, feature analysis, LLM-assisted scientific workflows, and evidence-aware AI tools.
Clinical & multimodal data
SQL-based data integration, clinical/molecular linkage, reproducible analysis, and translational decision-support concepts.
Scientific computing
Nextflow, HPC, containers, workflow scaling, and emerging computational capabilities including quantum chemistry.
Grant & manuscript support
Study design, computational feasibility, preliminary analyses, figures, methods, and reproducibility planning.
Possible collaboration pathways
Developmental Research / Pilot Projects
Early discussion can help define the computational question, preliminary-data strategy, and realistic analysis plan.
Research Vouchers
Projects that need focused access to Core expertise may be suitable for available voucher mechanisms.
Direct collaboration
Faculty with existing datasets, manuscripts, or grant concepts can begin with a short project-scoping discussion.
Resources coming next
Project intake worksheet
A one-page guide for defining the question, data, analysis, deliverable, and timeline.
Data-readiness checklist
What to organize before analysis begins: sample maps, metadata, file formats, controls, and provenance.
Example project blueprints
Short examples showing how a biological idea becomes an analysis plan, preliminary result, and grant or manuscript.
Collaboration FAQ
Authorship, timelines, responsibilities, data transfer, reproducibility, and what to expect from a computational collaboration.
Have a project in mind?
Send a short description of the biological question, the data you have or plan to generate, and the outcome you hope to achieve. The first conversation can focus on whether the project is ready for analysis and what support pathway makes sense.
Start a collaboration conversation