Consulting services

Analysis built around the scientific decision.

From a single difficult dataset to a full biomarker program, NeuroHub provides senior scientific guidance and hands-on analytical support for neurodegenerative disease research.

01 · Data integration

High-throughput multimodal analysis

Integrate molecular and clinical datasets while preserving the biological and cohort context needed for interpretation.

  • Genomics and transcriptomics
  • Proteomics and metabolomics
  • Imaging and digital measures
  • Longitudinal clinical phenotypes
02 · Discovery

Biomarker identification

Develop discovery strategies that prioritize reproducibility, clinical relevance, and realistic validation paths.

  • Blood-based biomarker discovery
  • Diagnostic and prognostic signatures
  • Disease subtype and endotype analysis
  • Cross-cohort replication and validation
03 · Modeling

Clinical & statistical analysis

Translate cohort questions into transparent models with defensible assumptions and decision-ready outputs.

  • Cross-sectional and longitudinal models
  • Mixed-effects and time-to-event analysis
  • Feature selection and model validation
  • Sensitivity, subgroup, and missing-data analysis
04 · Systems biology

Network-based analysis

Move beyond single markers to reveal coordinated pathways, disease mechanisms, and convergent biological signals.

  • Gene and pathway network analysis
  • Cross-disease molecular comparisons
  • Multi-omic module prioritization
  • Mechanism-focused interpretation
05 · Translation

Therapeutic target identification

Combine molecular evidence, clinical phenotypes, and external knowledge to prioritize hypotheses for further testing.

  • Target nomination and ranking
  • Evidence triangulation
  • Drug-repurposing hypotheses
  • Validation roadmap development
06 · Scientific delivery

Research strategy & communication

Strengthen the path from analysis plan to a clear scientific story without overstating what the data can support.

  • Study and statistical analysis plans
  • Grant and protocol development
  • Publication-grade figures and tables
  • Manuscript and scientific review

How engagements work

Clear scope. Reproducible work. Usable output.

Every engagement begins with the decision the analysis needs to support, followed by an auditable plan and an explicit interpretation of what the evidence does—and does not—show.

Frame

Clarify the biological question, intended use, available data, constraints, and standards for success.

Analyze

Build a reproducible workflow, evaluate assumptions, run sensitivity analyses, and document key decisions.

Translate

Deliver results, code, figures, and a practical interpretation with specific next steps for validation.

Have a dataset or research question in mind?

Share the scientific problem and where the project is currently stuck.

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