TISSUES 2.0: an integrative web resource on mammalian tissue expression

TY - JOUR

T1 - TISSUES 2.0

T2 - an integrative web resource on mammalian tissue expression

AU - Palasca, Oana

AU - Santos, Alberto

AU - Stolte, Christian

AU - Gorodkin, Jan

AU - Jensen, Lars Juhl

PY - 2018/1/1

Y1 - 2018/1/1

N2 - 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.

AB - 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.

U2 - 10.1093/database/bay003

DO - 10.1093/database/bay003

M3 - Journal article

C2 - 29617745

SN - 1758-0463

VL - 2018

SP - 1

EP - 12

JO - Database: The Journal of Biological Databases and Curation

JF - Database: The Journal of Biological Databases and Curation

IS - 1

ER -