ArticleBriefings in bioinformatics2017
MTD: a mammalian transcriptomic database to explore gene expression and regulation.
Article in Briefings in bioinformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- SCIG: Machine learning uncovers cell identity genes in single cells by genetic sequence codes.Nucleic acids research · 2025Article
- Exploring the Regulation and Function ofGenes · 2023Article
- Processing and Analysis of RNA-seq Data from Public Resources.Methods in molecular biology (Clifton, N.J.) · 2021Review
- Systematic integrated analysis of genetic and epigenetic variation in diabetic kidney disease.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Unifying cancer and normal RNA sequencing data from different sources.Scientific data · 2018Article
- Database Resources of the BIG Data Center in 2018.Nucleic acids research · 2018Article
- scRNASeqDB: A Database for RNA-Seq Based Gene Expression Profiles in Human Single Cells.Genes · 2017Article
- In silico design of context-responsive mammalian promoters with user-defined functionality.Nucleic acids research · 2017Article
- The BIG Data Center: from deposition to integration to translation.Nucleic acids research · 2017Article
- ANGIOGENES: knowledge database for protein-coding and noncoding RNA genes in endothelial cells.Scientific reports · 2016Article
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A systematic transcriptome survey is essential for the characterization and comprehension of the molecular basis underlying phenotypic variations. Recently developed RNA-seq methodology has facilitated efficient data acquisition and information mining of transcriptomes in multiple tissues/cell lines. Current mammalian transcriptomic databases are either tissue-specific or species-specific, and they lack in-depth comparative features across tissues and species. Here, we present a mammalian transcriptomic database (MTD) that is focused on mammalian transcriptomes, and the current version contains data from humans, mice, rats and pigs. Regarding the core features, the MTD browses genes based on their neighboring genomic coordinates or joint KEGG pathway and provides expression information on exons, transcripts and genes by integrating them into a genome browser. We developed a novel nomenclature for each transcript that considers its genomic position and transcriptional features. The MTD allows a flexible search of genes or isoforms with user-defined transcriptional characteristics and provides both table-based descriptions and associated visualizations. To elucidate the dynamics of gene expression regulation, the MTD also enables comparative transcriptomic analysis in both intraspecies and interspecies manner. The MTD thus constitutes a valuable resource for transcriptomic and evolutionary studies. The MTD is freely accessible at http://mtd.cbi.ac.cn.
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