Curated list of key publications, datasets, and technical resources for precision medicine bioinformatics.
BioinfoMCP: Bioinformatics Workflows with Model Context Protocol
- Citation: arXiv:2510.02139v1 (2025)
- Link: https://arxiv.org/html/2510.02139v1
- Summary: Pioneering work demonstrating how MCP can orchestrate complex bioinformatics workflows using natural language. Foundation for this repository's architecture.
- Key Contributions: Server design patterns, workflow orchestration, integration strategies
Spatial Transcriptomics: Technologies, Applications, and Experimental Considerations
- Citation: Nucleic Acids Research, Volume 53, Issue 12 (2025)
- Link: https://academic.oup.com/nar/article/53/12/gkaf536/8174767
- Summary: Comprehensive review of spatial transcriptomics technologies including Visium, MERFISH, and seqFISH+
- Relevance: Technical foundation for mcp-spatialtools implementation
STAR: Ultrafast Universal RNA-seq Aligner
- Citation: Dobin et al., Bioinformatics (2013)
- DOI: 10.1093/bioinformatics/bts635
- Summary: Spliced alignment algorithm for RNA-seq data
- Implementation: Used in
mcp-spatialtools.align_spatial_data()
ComBat: Adjusting Batch Effects in Microarray Expression Data
- Citation: Johnson et al., Biostatistics (2007)
- DOI: 10.1093/biostatistics/kxj037
- Summary: Empirical Bayes method for removing batch effects while preserving biological variation
- Implementation: Used in
mcp-spatialtools.perform_batch_correction()
HAllA: Hierarchical All-against-All Association Discovery
- Citation: Rahnavard et al., PLOS Computational Biology (2017)
- DOI: 10.1371/journal.pcbi.1005308
- Summary: Method for discovering associations between high-dimensional datasets
- Implementation: Core algorithm in
mcp-multiomics(95% real)
Meta-Analysis with Stouffer's Method
- Citation: Stouffer et al., "The American Soldier" (1949)
- Summary: Combines p-values from independent tests using Z-score transformation
- Implementation: Used in
mcp-multiomics.calculate_stouffer_meta()
The Cancer Genome Atlas (TCGA) - Ovarian Cancer
- Project: TCGA-OV
- Link: https://portal.gdc.cancer.gov/projects/TCGA-OV
- Data Types: WXS, RNA-seq, SNP arrays, clinical data
- Sample Size: 600+ High-Grade Serous Ovarian Carcinoma samples
- Relevance: Reference cohort for mcp-mocktcga server, pathway curation
TCGA Publications:
- Integrated genomic analyses of ovarian carcinoma (Nature, 2011)
- DOI: 10.1038/nature10166
10x Genomics Public Datasets
- Link: https://www.10xgenomics.com/datasets
- Platforms: Visium, Xenium, Chromium
- Data Types: Spatial gene expression, histology images, spatial coordinates
- Use Cases: Validation data for mcp-spatialtools, educational examples
Visium Spatial Gene Expression
- Human breast cancer datasets
- Mouse brain tissue datasets
- Human ovarian cancer (if available)
- Link: https://www.genome.jp/kegg/
- Pathways Used: PI3K-Akt signaling, p53 signaling, cell cycle, apoptosis
- Implementation: 44 curated pathways in mcp-spatialtools pathway enrichment
- Link: http://geneontology.org/
- Categories Used: Biological Process (GO_BP), Molecular Function, Cellular Component
- Implementation: Pathway enrichment in mcp-spatialtools
- Link: https://www.gsea-msigdb.org/gsea/msigdb/
- Collections Used: Hallmark gene sets, drug resistance signatures
- Implementation: Custom curated pathways in mcp-spatialtools
- Link: https://www.gencodegenes.org/
- Version Used: GRCh38.p14 (hg38)
- Components: Gene annotations, transcript models, regulatory elements
- Implementation: STAR genome index preparation, gene ID mapping
- Link: https://www.ensembl.org/
- Use Case: Alternative genome annotations, variant effect prediction
Benjamini-Hochberg FDR Control
- Citation: Benjamini & Hochberg, Journal of the Royal Statistical Society (1995)
- DOI: 10.1111/j.2517-6161.1995.tb02031.x
- Implementation: FDR correction in pathway enrichment, differential expression
Moran's I Spatial Autocorrelation
- Citation: Moran, Biometrika (1950)
- DOI: 10.2307/2332142
- Summary: Measures spatial autocorrelation (clustering vs random distribution)
- Implementation:
mcp-spatialtools.calculate_spatial_autocorrelation()
Mann-Whitney U Test
- Citation: Mann & Whitney, Annals of Mathematical Statistics (1947)
- Summary: Non-parametric test for comparing two independent groups
- Implementation: Differential expression in mcp-spatialtools
Fisher's Exact Test
- Citation: Fisher, Journal of the Royal Statistical Society (1922)
- Summary: Test for independence in 2×2 contingency tables
- Implementation: Pathway enrichment (gene overlap significance)
- Link: https://hl7.org/fhir/
- Version: R4
- Resources Used: Patient, Condition, Observation, MedicationStatement
- Implementation: mcp-mockepic server structure
- Specification: https://modelcontextprotocol.io/specification/2025-06-18
- GitHub: https://github.com/modelcontextprotocol
- Python SDK: FastMCP framework
ClinicalTrials.gov - Ovarian Cancer
- Link: https://clinicaltrials.gov/
- Search: "ovarian cancer" + "precision medicine"
- Note: For educational reference only - not clinical recommendations
National Cancer Institute (NCI) - Ovarian Cancer
- Link: https://www.cancer.gov/types/ovarian
- Resources: Treatment information, clinical trial finder
If you use any of these references in your research with this repository, please cite both the original publication and this repository:
@software{langit2026precision,
author = {Langit, Lynn},
title = {Precision Medicine MCP Servers: AI-Orchestrated Clinical Bioinformatics},
year = {2026},
url = {https://github.com/lynnlangit/precision-medicine-mcp},
note = {PatientOne - In memory of a dear friend}
}Last Updated: January 31, 2026
Maintained by: Lynn Langit
Contributions: Pull requests welcome to add relevant publications