TISSUES

Overview

TISSUES is a comprehensive, integrative web resource that aggregates and unifies evidence about tissue-specific gene and protein expression in mammals. Developed by the Jensen Lab and maintained at the Swiss Institute of Bioinformatics, University of Zurich, TISSUES provides a weekly-updated platform that combines multiple sources of tissue expression data with confidence scoring and intuitive visualization.

Data Sources

TISSUES integrates evidence from three main types of sources:

1. Manual Curation

• Literature-derived tissue expression annotations
• Expert-curated relationships from published studies
• High-confidence tissue-protein associations

2. High-Throughput Data

• Large-scale proteomics screens
• Transcriptomics experiments
• Gene expression profiling studies

3. Text Mining

• Automatic extraction from scientific literature
• Co-occurrence analysis of genes/proteins with tissue terms
• Literature-wide association mining

Data Integration

All evidence is unified through:

• Mapping to common protein identifiers
• Standardization using Brenda Tissue Ontology terms
• Assignment of confidence scores for each evidence type
• Cross-source comparison and integration

Features

Visualization

• Schematic human body representation
• Expression patterns displayed on anatomical diagrams
• Intuitive overview of tissue-specific expression

Confidence Scoring

• Unified scoring system across all evidence types
• Facilitates comparison between different data sources
• Enables assessment of evidence quality and reliability

Weekly Updates

• Regular incorporation of new literature
• Integration of newly published datasets
• Continuous expansion of coverage

Use Cases

TISSUES can be used for:

• Identifying tissue-specific expression patterns
• Validating target tissue localization for drug development
• Exploring potential off-target effects
• Comparative analysis across tissues
• Integration into systems biology workflows

Funding

Supported by the Novo Nordisk Foundation, Danish Council for Independent Research, Innovation Fund Denmark, National Institutes of Health, and CSIRO.

Development Team

Originally developed by Alberto Santos, Oana Palasca, Christian Stolte, Kalliopi Tsafou, Sune Frankild, Janos Binder, Sean O’Donoghue, Jan Gorodkin, and Lars Juhl Jensen from the Novo Nordisk Foundation Center for Protein Research and collaborating institutions.

Currently maintained by Qingyao Huang at Swiss Institute of Bioinformatics, University of Zurich.