PubAngioGen: a database and knowledge for angiogenesis and related diseases

Liu, Yongrui; Wang, Huan; He, Yonghong; Wang, Xue; He, Yundong; Lv, Fang; Chen, Huaqing; Pang, Xiufeng; Liu, Mingyao; Shi, Tieliu; Yi, Zhengfang

doi:10.1093/nar/gku1139

Cited by 8 publications

(6 citation statements)

References 29 publications

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“…As stated in the introduction, currently, there is no lncRNA database focused on individual cell type. Furthermore, when similar databases of endothelial cells and angiogenesis were searched, there only three databases are available: Causal Biological Network database 40 , dbANGIO 41 and PubAngioGen 42 . All of these databases are based on rather manual literature/text mining methods.…”

Section: Discussionmentioning

confidence: 99%

ANGIOGENES: knowledge database for protein-coding and noncoding RNA genes in endothelial cells

Müller

Weirick

John

et al. 2016

Sci Rep

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Increasing evidence indicates the presence of long noncoding RNAs (lncRNAs) is specific to various cell types. Although lncRNAs are speculated to be more numerous than protein-coding genes, the annotations of lncRNAs remain primitive due to the lack of well-structured schemes for their identification and description. Here, we introduce a new knowledge database “ANGIOGENES” (http://angiogenes.uni-frankfurt.de) to allow for in silico screening of protein-coding genes and lncRNAs expressed in various types of endothelial cells, which are present in all tissues. Using the latest annotations of protein-coding genes and lncRNAs, publicly-available RNA-seq data was analyzed to identify transcripts that are expressed in endothelial cells of human, mouse and zebrafish. The analyzed data were incorporated into ANGIOGENES to provide a one-stop-shop for transcriptomics data to facilitate further biological validation. ANGIOGENES is an intuitive and easy-to-use database to allow in silico screening of expressed, enriched and/or specific endothelial transcripts under various conditions. We anticipate that ANGIOGENES serves as a starting point for functional studies to elucidate the roles of protein-coding genes and lncRNAs in angiogenesis.

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Section: Discussionmentioning

confidence: 99%

ANGIOGENES: knowledge database for protein-coding and noncoding RNA genes in endothelial cells

Müller

Weirick

John

et al. 2016

Sci Rep

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“…We have developed a number of bioinformatics tools to exploit these resources (Gellert et al, 2013 ; Weirick et al, 2015 , 2016b , 2017 ), including some specifically designed to identify lncRNAs and to associate their expressions in various tissues and cell types, including ECs (e.g., our database ANGIOGENES; Müller et al, 2016 ). Although ECs can be found throughout the human body, there are only few databases available that contain the expression profiles for genes expressed in ECs (e.g., Causal Biological Network database Boué et al, 2015 , dbANGIO4 Savas, 2012 , and PubAngioGen Li et al, 2015 ). Our ANGIOGENE is one of the few that contain the expression profiles of both protein-coding genes and lncRNAs in various ECs based on RNA-seq data.…”

Section: Rna-seq Data Analysis Using Bioinformaticsmentioning

confidence: 99%

Long Non-coding RNAs in Endothelial Biology

2018

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In recent years, the role of RNA has expanded to the extent that protein-coding RNAs are now the minority with a variety of non-coding RNAs (ncRNAs) now comprising the majority of RNAs in higher organisms. A major contributor to this shift in understanding is RNA sequencing (RNA-seq), which allows a largely unconstrained method for monitoring the status of RNA from whole organisms down to a single cell. This observational power presents both challenges and new opportunities, which require specialized bioinformatics tools to extract knowledge from the data and the ability to reuse data for multiple studies. In this review, we summarize the current status of long non-coding RNA (lncRNA) research in endothelial biology. Then, we will cover computational methods for identifying, annotating, and characterizing lncRNAs in the heart, especially endothelial cells.

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“…The most significant site, AT4G01150.1, is related to protein curvature thylakoid chloroplastic. Protein curvature thylakoid chloroplastic tends to be located in leaves and stems, and plays an important role in plant photosynthesis, which affects plant growth [57].…”

Section: Candidate Gene Function Annotationmentioning

confidence: 99%

Functional Mapping of Plant Growth in Arabidopsis thaliana

Liu¹,

Bo²,

Wang³

et al. 2018

Next Generation Plant Breeding

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Most traits important to agriculture, biology, and biomedicine are complex traits, determined by both genetic and environmental factors. The complex traits that change their phenotypes over different stages of development are called dynamic traits. Traditional quantitative trait loci (QTLs) mapping approaches ignore the dynamic changes of complex traits. Functional mapping, as a powerful statistical tool, can not only map QTLs that control the developmental pattern and process of complex traits, but also describe the dynamic changes of complex traits. In this study, we used functional mapping to identify those QTLs that affect height growth in 10th generation recombinant inbred lines derived from two different Arabidopsis thaliana accessions. Functional mapping identified 48 QTLs that are related to height traits. The growth curves of different genotypes can be drawn for each significant locus. By GO gene function annotations, we found that these QTLs detected are associated with the synthesis of biological macromolecules and the regulation of biological functions. Our findings provide unique insights into the genetic control of height growth of A. thaliana and will provide a theoretical basis for the study of complex traits.

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PubAngioGen: a database and knowledge for angiogenesis and related diseases

Cited by 8 publications

References 29 publications

ANGIOGENES: knowledge database for protein-coding and noncoding RNA genes in endothelial cells

ANGIOGENES: knowledge database for protein-coding and noncoding RNA genes in endothelial cells

Long Non-coding RNAs in Endothelial Biology

Functional Mapping of Plant Growth in Arabidopsis thaliana

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