TISSUES 2.0: an integrative web resource on mammalian tissue expression
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Abstract: Physiological and molecular similarities between organisms make it possible to translate findings from simpler experimental systems—model organisms—into more complex ones, such as human. This translation facilitates the understanding of biological processes under normal or disease conditions. Researchers aiming to identify the similarities and differences between organisms at the molecular level need resources collecting multi-organism tissue expression data. We have developed a database of gene–tissue associations in human, mouse, rat and pig by integrating multiple sources of evidence: transcriptomics covering all four species and proteomics (human only), manually curated and mined from the scientific literature. Through a scoring scheme, these associations are made comparable across all sources of evidence and across organisms. Furthermore, the scoring produces a confidence score assigned to each of the associations. The TISSUES database (version 2.0) is publicly accessible through a user-friendly web interface and as part of the STRING app for Cytoscape. In addition, we analyzed the agreement between datasets, across and within organisms, and identified that the agreement is mainly affected by the quality of the datasets rather than by the technologies used or organisms compared. Database URL: http://tissues.jensenlab.org/
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Target expression data was primarily extracted from GTEx, the Human Protein Atlas, UniProt and TISSUES.
“Target expression data was primarily extracted from GTEx (12), the Human Protein Atlas (HPA) (13), UniProt and TISSUES (14).”
From TCRD and pharos 2021: mining the human proteome for disease biology (2021) · cites this paper as [14]
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- Authors
- Palasca, O., Santos, A., Stolte, C., Gorodkin, J., & Jensen, L. J.
- Affiliations
- University of Copenhagen (DK)
- New York Genome Center (US)
- Corresponding author
- Gorodkin, Jan
- Jensen, Lars Juhl
- Venue
- Database
- Publisher
- Oxford University Press (OUP)
- Published
- 2018-01-01
- Volume
- 2018
- ISSN
- 1758-0463 (ISSN-L)
- PMC
- PMC5808782
- OpenAlex
- W2792450944
- Cited by
- 182
- References
- 58
- Citations by year
- 2026: 8 · 2025: 25 · 2024: 22 · 2023: 20 · 2022: 35 · 2021: 24 · 2020: 30 · 2019: 11 · 2018: 7
- FWCI
- 6.49
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Database (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, other-oa)
- Funders
- Innovationsfonden (0603-00320B)
- Novo Nordisk (NNF14CC0001)
- Danmarks Frie Forskningsfond (DFF-4005-00443, 4005-00443)
- Novo Nordisk Fonden (NNF 14CC0001)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Biomedical Text Mining and Ontologies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- tissue expression, transcriptomics, proteomics, literature curation, scoring system, confidence scores, model organisms, cross-species translation
- MeSH terms
- Animals, Gene Expression Regulation, Humans, Organ Specificity, Species Specificity, Swine, Databases, Genetic, Mice, Rats, Data Curation
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