TISSUES

Tissue expression database

JensenLab
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SETD1B tissues

SETD1B [ENSP00000474253]

Histone-lysine N-methyltransferase SETD1B; Histone methyltransferase that specifically methylates 'Lys- 4' of histone H3, when part of the SET1 histone methyltransferase (HMT) complex, but not if the neighboring 'Lys-9' residue is already methylated. H3 'Lys-4' methylation represents a specific tag for epigenetic transcriptional activation. The non-overlapping localization with SETD1A suggests that SETD1A and SETD1B make non-redundant contributions to the epigenetic control of chromatin structure and gene expression. Specifically tri-methylates 'Lys-4' of histone H3 in vitro; Belongs to the class V-like SAM-binding methyltransferase superfamily.

Synonyms:  SETD1B,  SETD1Bp,  hSETD1B,  A0A0A0MQV9,  Q9UPS6 ...

Linkouts:  STRING  Pharos  UniProt

0 1 2 3 4 5 Confidence

The tissue associations are derived from manually curated knowledge in UniProtKB and via automatic text mining of the biomedical literature, which has not been manually verified. The confidence of each association is signified by stars, where ★★★★★ is the highest confidence and ★☆☆☆☆ is the lowest. Download files from earlier versions are archived on figshare.

Each tissue–gene association is based on a text-mining score, which is proportional to 1) the absolute number of comentionings and 2) the ratio of observed to expected comentionings (i.e. the enrichment). These scores are normalized to z-scores by comparing them to a random background. This is represented by stars, each star corresponding to two standard deviations above the mean of the background distribution.

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, Center for non-coding RNA in Technology and Health, and the Commonwealth Scientific and Industrial Research Organisation (CSIRO).

Currently maintained by Qingyao Huang at Swiss Institute of Bioinformatics, University of Zurich. Licensed under CC BY 4.0.