ArticleOpen biology2019
EmExplorer: a database for exploring time activation of gene expression in mammalian embryos.
Article in Open biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.
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Who cites it
26 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Cross-species meta-analysis of transcriptome changes during the morula-to-blastocyst transition: metabolic and physiological changes take center stage.American journal of physiology. Cell physiology · 2021Pooled it
- LivestockDev: A multi-omics resource for exploring cross-species comparison of livestock embryogenesis.Zoological research · 2026Article
- Deciphering Sequence Determinants of Zygotic Genome Activation Genes: Insights From Machine Learning and the ZGAExplorer Platform.Cell proliferation · 2025Article
- Toti: An integrated multi-omics database to decipher the epigenetic regulation of gene expression in totipotent stem cells.Stem cell reports · 2025Article
- Machine Learning-Based identification of resistance genes associated with sunflower broomrape.Plant methods · 2025Article
- Alternative splicing dynamics during gastrulation in mouse embryo.Scientific reports · 2025Article
- DNA sequence analysis landscape: a comprehensive review of DNA sequence analysis task types, databases, datasets, word embedding methods, and language models.Frontiers in medicine · 2025Review
- Activation of telomerase via madecassic acid enhances the developmental competence of the SCNT-derived bovine embryos.Frontiers in cell and developmental biology · 2025Article
- Extraction of Innate Immune Genes in Dairy Cattle and the Regulation of Their Expression in Early Embryos.Genes · 2024Review
- scapGNN: A graph neural network-based framework for active pathway and gene module inference from single-cell multi-omics data.PLoS biology · 2023Article
- EmAtlas: a comprehensive atlas for exploring spatiotemporal activation in mammalian embryogenesis.Nucleic acids research · 2023Article
- Change point detection for clustered expression data.BMC genomics · 2022Article
- Review
- Capture and metabolomic analysis of the human endometrial epithelial organoid secretome.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Article
- Development and Validation of a Novel 11-Gene Prognostic Model for Serous Ovarian Carcinomas Based on Lipid Metabolism Expression Profile.International journal of molecular sciences · 2020Article
- Machine Learning of Single-Cell Transcriptome Highly Identifies mRNA Signature by Comparing F-Score Selection with DGE Analysis.Molecular therapy. Nucleic acids · 2020Article
- Characterization of the relationship between FLI1 and immune infiltrate level in tumour immune microenvironment for breast cancer.Journal of cellular and molecular medicine · 2020Article
- A Comparative Analysis of Single-Cell Transcriptome Identifies Reprogramming Driver Factors for Efficiency Improvement.Molecular therapy. Nucleic acids · 2020Article
- Identification of immune-enhanced molecular subtype associated with BRCA1 mutations, immune checkpoints and clinical outcome in ovarian carcinoma.Journal of cellular and molecular medicine · 2020Article
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7 authors.
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Abstract
Understanding early development offers a striking opportunity to investigate genetic disease, stem cell and assisted reproductive technology. Recent advances in high-throughput sequencing technology have led to the rising influx of omics data, which have rapidly boosted our understanding of mammalian developmental mechanisms. Here, we review the database EmExplorer (a database for exploring time activation of gene expression in mammalian embryos), which systematically organizes the genes from development-related pathways, and which we have already established and continue to update it. The current version of EmExplorer incorporates over 26 000 genes obtained from 306 functional pathways in five species. The function annotations of development-related genes were also integrated into EmExplorer. To facilitate data extraction, the database also contains the following information. (i) The dynamic expression values for each development stage are matched to the corresponding genes. (ii) A two-layer search tool which supports multi-option searching, such as by official symbol, pathway name and function annotation. The returned entries can directly link to the analysis results for the corresponding gene or pathway in the analysis module. (iii) The analysis module provides different gene comparisons at the multi-species level and functional pathway level, which shows the species specificity and stage specificity at the gene or pathway level. (iv) The analysis based on the hypergeometric distribution test reveals the enrichment of gene functions at a particular stage of one organism's pathway. (v) The browser is designed for users with ambiguous searching goals and greatly helps new users to get a general idea of the contents of the database. (vi) The experimentally validated pathways are manually curated and shown on the home page. EmExplorer will be helpful for elucidating early developmental mechanisms and exploring time activation genes. EmExplorer is freely available at http://bioinfor.imu.edu.cn/emexplorer .
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