Tissue-based map of the human proteome

By Mathias Uhlen, Linn Fagerberg, B. Hallström, C. Lindskog, P. Oksvold, Adil Mardinoglu, Åsa Sivertsson, C. Kampf, E. Sjöstedt, A. Asplund and 26 more. 2015

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Subfields: Molecular Biology, Spectroscopy

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Citations in the corpus

Folding membrane proteins by deep transfer learning (2017, background): “It is estimated that 20-40% of all genes in most genomes encode MPs (Uhlén et al., 2015, Krogh et al., 2001) and larger genomes contain a higher fraction of MPs (Wallin and Heijne, 1998).”
A deep proteome and transcriptome abundance atlas of 29 healthy human tissues (2018, methodology): “Any potential lncRNA or aTIS peptide was required to originate from just one single sequence collection only (i.e. lncRNA or aTIS and no other database), be identified both by Mascot and Andromeda, to fulfil stringent score cut-offs (see methods), to be backed up by the expression of the underlying ”
Deep learning sequence-based ab initio prediction of variant effects on expression and disease risk (2018, methodology): “…expression model should ideally utilize TSS-specific expression quantification, gene level expression measured by RNA-seq or microarray are usually a good approximation of transcription level from the representative TSS of each gene 52,53 , and are usually measured with higher sequencing depth.”
g:Profiler: a web server for functional enrichment analysis and conversions of gene lists (2019 update) (2019, background): “This covers currently KEGG (19), Reactome (20) and WikiPathways (21); miRNA targets from miRTar-Base (22) and regulatory motif matches from TRANSFAC (23); tissue specificity based on expression data from Human Protein Atlas (24); protein complexes data from CO-RUM (25) and human disease phenotype as”
Codon identity regulates mRNA stability and translation efficiency during the maternal‐to‐zygotic transition (2016, positive): “The human tissue data were extracted from RNA-seq of coding RNA from tissue samples of 122 human individuals representing 32 different tissues (Uhlen et al, 2015).”
An atlas of the protein-coding genes in the human, pig, and mouse brain (2020, methodology): “The data presented here havemade it possible to compare the brain enrichment of all genes with the whole-body tissue specificity using the Tissue Atlas resource (1).”
COVID-19 and comorbidities: Deleterious impact on infected patients (2020, background): “ACE-2 receptors present on liver cells mediate the entry of SARS-CoV-2 inside the liver cells [31].”
Integrated interactions database: tissue-specific view of the human and model organism interactomes (2015, methodology): “A protein was considered expressed in a tissue if its level based on Human Protein Atlas (30) was anything other than ‘Not detected’ or its level based on PaxDb (31) was greater than 0.”
Integrated intra‐ and intercellular signaling knowledge for multicellular omics analysis (2020, neutral): “Or for the resulting networks used to make the conclusions it would be good to show the number of resources from which the nodes/data points were extracted, to make the case that this integrated resource is necessary for this analysis.”