Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

KEGGViewer, a BioJS component to visualize KEGG Pathways.

ABSTRACT: SUMMARY: Signaling pathways provide essential information on complex regulatory processes within the cell. They are moreover widely used to interpret and integrate data from large-scale studies, such as expression or functional screens. We present KEGGViewer a BioJS component to visualize KEGG pathways and to allow their visual integration with functional data. AVAILABILITY: KEGGViewer is an open-source tool freely available at the BioJS Registry. Instructions on how to use the tool are available at http://goo.gl/dVeWpg and the source code can be found at http://github.com/biojs/biojs and DOI: 10.5281/zenodo.7708.

SUBMITTER: Villaveces JM

PROVIDER: S-EPMC3954160 | biostudies-other | 2014

REPOSITORIES: biostudies-other

ACCESS DATA

Json Xml

Publications

KEGGViewer, a BioJS component to visualize KEGG Pathways.

Villaveces Jose M JM Jimenez Rafael C RC Habermann Bianca H BH

F1000Research 20140213

<h4>Summary</h4>Signaling pathways provide essential information on complex regulatory processes within the cell. They are moreover widely used to interpret and integrate data from large-scale studies, such as expression or functional screens. We present KEGGViewer a BioJS component to visualize KEGG pathways and to allow their visual integration with functional data.<h4>Availability</h4>KEGGViewer is an open-source tool freely available at the BioJS Registry. Instructions on how to use the tool ...[more]

PMID: 24715980

Similar Datasets

KnetMaps: a BioJS component to visualize biological knowledge networks.

Project description:KnetMaps is a BioJS component for the interactive visualization of biological knowledge networks. It is well suited for applications that need to visualise complementary, connected and content-rich data in a single view in order to help users to traverse pathways linking entities of interest, for example to go from genotype to phenotype. KnetMaps loads data in JSON format, visualizes the structure and content of knowledge networks using lightweight JavaScript libraries, and supports interactive touch gestures. KnetMaps uses effective visualization techniques to prevent information overload and to allow researchers to progressively build their knowledge.

| S-EPMC6347035 | biostudies-other

PsicquicGraph, a BioJS component to visualize molecular interactions from PSICQUIC servers.

Project description:SUMMARY:Protein interaction networks have become an essential tool in large-scale data analysis, integration, and the visualization of high-throughput data in the context of complex cellular networks. Many individual databases are available that provide information on binary interactions of proteins and small molecules. Community efforts such as PSICQUIC aim to unify and standardize information emanating from these public databases. Here we introduce PsicquicGraph, an open-source, web-based visualization component for molecular interactions from PSIQUIC services. AVAILABILITY:PsicquicGraph is freely available at the BioJS Registry for download and enhancement. Instructions on how to use the tool are available here http://goo.gl/kDaIgZ and the source code can be found at http://github.com/biojs/biojs and DOI: 10.5281/zenodo.7709.

| S-EPMC4097353 | biostudies-other

Epiviz Web Components: reusable and extensible component library to visualize functional genomic datasets.

Project description:Interactive and integrative data visualization tools and libraries are integral to exploration and analysis of genomic data. Web based genome browsers allow integrative data exploration of a large number of data sets for a specific region in the genome. Currently available web-based genome browsers are developed for specific use cases and datasets, therefore integration and extensibility of the visualizations and the underlying libraries from these tools is a challenging task. Genomic data visualization and software libraries that enable bioinformatic researchers and developers to implement customized genomic data viewers and data analyses for their application are much needed. Using recent advances in core web platform APIs and technologies including Web Components, we developed the Epiviz Component Library, a reusable and extensible data visualization library and application framework for genomic data. Epiviz Components can be integrated with most JavaScript libraries and frameworks designed for HTML. To demonstrate the ease of integration with other frameworks, we developed an R/Bioconductor epivizrChart package, that provides interactive, shareable and reproducible visualizations of genomic data objects in R, Shiny and also create standalone HTML documents. The component library is modular by design, reusable and natively extensible and therefore simplifies the process of managing and developing bioinformatic applications.

| S-EPMC6092909 | biostudies-literature

Dual-Principal Component Analysis of the Raman Spectrum Matrix to Automatically Identify and Visualize Microplastics and Nanoplastics.

Project description:As emerging contaminants, microplastics are challenging to characterize, particularly when their size is at the nanoscale. While imaging technology has received increasing attention recently, such as Raman imaging, decoding the scanning spectrum matrix can be difficult to achieve result digitally and automatically via software and usually requires the involvement of personal experience and expertise. Herewith, we show a dual-principal component analysis (PCA) approach, where (i) the first round of PCA analysis focuses on the raw spectrum data from the Raman scanning matrix and generates two new matrices, with one containing the spectrum profile to yield the PCA spectrum and the other containing the PCA intensity to be mapped as an image; (ii) the second round of PCA analysis merges the spectrum from the first round of PCA with the standard spectra of eight common plastics, to generate a correlation matrix. From the correlation value, we can digitally assign the principal components from the first round of PCA analysis to the plastics toward imaging, akin to dataset indexing. We also demonstrate the effect of the data pretreatment and the wavenumber variations. Overall, this dual-PCA approach paves the way for machine learning to analyze microplastics and particularly nanoplastics.

| S-EPMC9620979 | biostudies-literature

Framework, component, and implementation of enhanced recovery pathways.

Project description:The introduction of enhanced recovery pathways (ERPs) has led to a considerable paradigm shift towards evidence-based, multidisciplinary perioperative care. Such pathways are now widely implemented in a variety of surgical specialties, with largely positive results. In this narrative review, we summarize the principles, components and implementation of ERPs, focusing on recent developments in the field. We also discuss 'special cases' in ERPs, including: surgery in frail patients; emergency procedures; and patients with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2/COVID-19).

| S-EPMC9255474 | biostudies-literature

Identification of differential gene pathways with principal component analysis.

Project description:MotivationDevelopment of high-throughput technology makes it possible to measure expressions of thousands of genes simultaneously. Genes have the inherent pathway structure, where pathways are composed of multiple genes with coordinated biological functions. It is of great interest to identify differential gene pathways that are associated with the variations of phenotypes.ResultsWe propose the following approach for detecting differential gene pathways. First, we construct gene pathways using databases such as KEGG or GO. Second, for each pathway, we extract a small number of representative features, which are linear combinations of gene expressions and/or their transformations. Specifically, we propose using (i) principal components (PCs) of gene expression sets, (ii) PCs of expanded gene expression sets and (iii) expanded sets of PCs of gene expressions, as the representative features. Third, we identify differential gene pathways as those with representative features significantly associated with the variations of phenotypes, particularly disease clinical outcomes, in regression models. The false discovery rate approach is used to adjust for multiple comparisons. Analysis of three gene expression datasets suggests that (i) the proposed approach can effectively identify differential gene pathways; (ii) PCs that explain only a small amount of variations of gene expressions may bear significant associations between gene pathways and phenotypes; (iii) including second-order terms of gene expressions may lead to identification of new differential gene pathways; (iv) the proposed approach is relatively insensitive to additional noises; and (v) the proposed approach can identify gene pathways missed by alternative approaches.Supplementary informationSupplementary data are available at Bioinformatics online.

| S-EPMC2732304 | biostudies-literature

Histidine phosphotransfer proteins in fungal two-component signal transduction pathways.

Project description:The histidine phosphotransfer (HPt) protein Ypd1 is an important participant in the Saccharomyces cerevisiae multistep two-component signal transduction pathway and, unlike the expanded histidine kinase gene family, is encoded by a single gene in nearly all model and pathogenic fungi. Ypd1 is essential for viability in both S. cerevisiae and in Cryptococcus neoformans. These and other aspects of Ypd1 biology, combined with the availability of structural and mutational data in S. cerevisiae, suggest that the essential interactions between Ypd1 and response regulator domains would be a good target for antifungal drug development. The goal of this minireview is to summarize the wealth of data on S. cerevisiae Ypd1 and to consider the potential benefits of conducting related studies in pathogenic fungi.

| S-EPMC3754533 | biostudies-literature

Transplantation of prokaryotic two-component signaling pathways into mammalian cells.

Project description:Signaling pathway engineering is a promising route toward synthetic biological circuits. Histidine-aspartate phosphorelays are thought to have evolved in prokaryotes where they form the basis for two-component signaling. Tyrosine-serine-threonine phosphorelays, exemplified by MAP kinase cascades, are predominant in eukaryotes. Recently, a prokaryotic two-component pathway was implemented in a plant species to sense environmental trinitrotoluene. We reasoned that "transplantation" of two-component pathways into mammalian host could provide an orthogonal and diverse toolkit for a variety of signal processing tasks. Here we report that two-component pathways could be partially reconstituted in mammalian cell culture and used for programmable control of gene expression. To enable this reconstitution, coding sequences of histidine kinase (HK) and response regulator (RR) components were codon-optimized for human cells, whereas the RRs were fused with a transactivation domain. Responsive promoters were furnished by fusing DNA binding sites in front of a minimal promoter. We found that coexpression of HKs and their cognate RRs in cultured mammalian cells is necessary and sufficient to strongly induce gene expression even in the absence of pathways' chemical triggers in the medium. Both loss-of-function and constitutive mutants behaved as expected. We further used the two-component signaling pathways to implement two-input logical AND, NOR, and OR gene regulation. Thus, two-component systems can be applied in different capacities in mammalian cells and their components can be used for large-scale synthetic gene circuits.

| S-EPMC4226098 | biostudies-literature

The genetic organisation of prokaryotic two-component system signalling pathways.

Project description:BackgroundTwo-component systems (TCSs) are modular and diverse signalling pathways, involving a stimulus-responsive transfer of phosphoryl groups from transmitter to partner receiver domains. TCS gene and domain organisation are both potentially informative regarding biological function, interaction partnerships and molecular mechanisms. However, there is currently little understanding of the relationships between domain architecture, gene organisation and TCS pathway structure.ResultsHere we classify the gene and domain organisation of TCS gene loci from 1405 prokaryotic replicons (>40,000 TCS proteins). We find that 200 bp is the most appropriate distance cut-off for defining whether two TCS genes are functionally linked. More than 90% of all TCS gene loci encode just one or two transmitter and/or receiver domains, however numerous other geometries exist, often with large numbers of encoded TCS domains. Such information provides insights into the distribution of TCS domains between genes, and within genes. As expected, the organisation of TCS genes and domains is affected by phylogeny, and plasmid-encoded TCS exhibit differences in organisation from their chromosomally-encoded counterparts.ConclusionsWe provide here an overview of the genomic and genetic organisation of TCS domains, as a resource for further research. We also propose novel metrics that build upon TCS gene/domain organisation data and allow comparisons between genomic complements of TCSs. In particular, 'percentage orphaned TCS genes' (or 'Dissemination') and 'percentage of complex loci' (or 'Sophistication') appear to be useful discriminators, and to reflect mechanistic aspects of TCS organisation not captured by existing metrics.

| S-EPMC3018481 | biostudies-literature

Component specificity for the thylakoidal Sec and Delta pH-dependent protein transport pathways.

Project description:Prokaryotes and prokaryote-derived thylakoid membranes of chloroplasts share multiple, evolutionarily conserved pathways for protein export. These include the Sec, signal recognition particle (SRP), and Delta pH/Tat systems. Little is known regarding the thylakoid membrane components involved in these pathways. We isolated a cDNA clone to a novel component of the Delta pH pathway, Tha4, and prepared antibodies against pea Tha4, against maize Hcf106, a protein implicated in Delta pH pathway transport by genetic studies, and against cpSecY, the thylakoid homologue of the bacterial SecY translocon protein. These components were localized to the nonappressed thylakoid membranes. Tha4 and Hcf106 were present in approximately 10-fold excess over active translocation sites. Antibodies to either Tha4 or Hcf106 inhibited translocation of four known Delta pH pathway substrate proteins, but not of Sec pathway or SRP pathway substrates. This suggests that Tha4 and Hcf106 operate either in series or as subunits of a heteromultimeric complex. cpSecY antibodies inhibited translocation of Sec pathway substrates but not of Delta pH or SRP pathway substrates. These studies provide the first biochemical evidence that Tha4 and Hcf106 are specific components of the Delta pH pathway and provide one line of evidence that cpSecY is used specifically by the Sec pathway.

| S-EPMC2199744 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data