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Open AccessJournal ArticleDOI

AnimalTFDB 3.0: a comprehensive resource for annotation and prediction of animal transcription factors.

TLDR
The new version of AnimalTFDB provides a comprehensive annotation and classification of TFs and cofactors, and will be a useful resource for studies of TF and transcription regulation.
Abstract
The Animal Transcription Factor DataBase (AnimalTFDB) is a resource aimed to provide the most comprehensive and accurate information for animal transcription factors (TFs) and cofactors. The AnimalTFDB has been maintained and updated for seven years and we will continue to improve it. Recently, we updated the AnimalTFDB to version 3.0 (http://bioinfo.life.hust.edu.cn/AnimalTFDB/) with more data and functions to improve it. AnimalTFDB contains 125,135 TF genes and 80,060 transcription cofactor genes from 97 animal genomes. Besides the expansion in data quantity, some new features and functions have been added. These new features are: (i) more accurate TF family assignment rules; (ii) classification of transcription cofactors; (iii) TF binding sites information; (iv) the GWAS phenotype related information of human TFs; (v) TF expressions in 22 animal species; (vi) a TF binding site prediction tool to identify potential binding TFs for nucleotide sequences; (vii) a separate human TF database web interface (HumanTFDB) was designed for better utilizing the human TFs. The new version of AnimalTFDB provides a comprehensive annotation and classification of TFs and cofactors, and will be a useful resource for studies of TF and transcription regulation.

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A molecular cell atlas of the human lung from single-cell RNA sequencing.

TL;DR: Droplet- and plate-based single cell RNA sequencing applied to ~75,000 human cells across all lung tissue compartments and circulating blood, combined with a multi-pronged cell annotation approach, have allowed them to define the gene expression profiles and anatomical locations of 58 cell populations in the human lung.
Journal ArticleDOI

Decoding human fetal liver haematopoiesis

TL;DR: A shift in the haemopoietic composition of fetal liver during gestation away from being predominantly erythroid, accompanied by a parallel change in differentiation potential of HSC/MPPs is demonstrated, which is validated to produce an integrated map of fetal liver haematopoiesis.
Journal ArticleDOI

A cell atlas of human thymic development defines T cell repertoire formation.

TL;DR: The authors' single-cell transcriptome profile of the thymus across the human lifetime and across species provides a high-resolution census of T cell development within the native tissue microenvironment, and identifies novel subpopulations of human thymic fibroblasts and epithelial cells and located them in situ.
Journal ArticleDOI

Transcriptional Basis of Mouse and Human Dendritic Cell Heterogeneity.

TL;DR: Two principal cDC2 lineages are identified defined by distinct developmental pathways and transcriptional regulators, including T-bet and RORγt, two key transcription factors known to define innate and adaptive lymphocyte subsets in human cancer.
References
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TL;DR: This work presents Model-based Analysis of ChIP-Seq data, MACS, which analyzes data generated by short read sequencers such as Solexa's Genome Analyzer, and uses a dynamic Poisson distribution to effectively capture local biases in the genome, allowing for more robust predictions.
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dbSNP: the NCBI database of genetic variation

TL;DR: The dbSNP database is a general catalog of genome variation to address the large-scale sampling designs required by association studies, gene mapping and evolutionary biology, and is integrated with other sources of information at NCBI such as GenBank, PubMed, LocusLink and the Human Genome Project data.
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The Pfam protein families database: towards a more sustainable future

TL;DR: Pfam is now primarily based on the UniProtKB reference proteomes, with the counts of matched sequences and species reported on the website restricted to this smaller set, and the facility to view the relationship between families within a clan has been improved by the introduction of a new tool.
Journal ArticleDOI

FIMO: scanning for occurrences of a given motif.

TL;DR: Find Individual Motif Occurrences (FIMO), a software tool for scanning DNA or protein sequences with motifs described as position-specific scoring matrices, and provides output in a variety of formats, including HTML, XML and several Santa Cruz Genome Browser formats.
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