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KEGG (Kyoto Encyclopedia of Genes and Genomes) is a collection of databases dealing with genomes, biological pathways, diseases, drugs, and chemical substances.KEGG is utilized for bioinformatics research and education, including data analysis in genomics, metagenomics, metabolomics and other omics studies, modeling and simulation in systems biology, and translational research in drug development.
KEGG PATHWAY Database (Univ. of Kyoto) MANET database (University of Illinois) Reactome: navigable map of human biological pathways, ranging from metabolic processes to hormonal signalling (Ontario Institute for Cancer Research, European Bioinformatics Institute, NYU Langone Medical Center, Cold Spring Harbor Laboratory)
In addition to various primary data formats (e.g. GPML, BioPAX, Reactome, [10] KEGG, and RDF [11]), WikiPathways supports a variety of ways to integrate and interact with pathway content. These include directed link-outs, image maps, RSS feeds and deep web services. [12] This enables reuse in projects like COVID19 Disease Map. [13]
SPRESI web: InfoChem Gesellschaft für chemische Information mbH organic molecules and reactions organic structures from literature "SPRESI". 5,800,000 SpringerMaterials Springer: solid materials CAS InChI physical properties from literature "SpringerMaterials". 155,165 + 494,942 STITCH EMBL from Biocarta, BioCyc, GO, KEGG, and Reactome
For input, MetPA expects either a list of compound names (identified as statistically significant or significant perturbed) or a metabolite concentration table with phenotypic labels (i.e. sick vs. healthy). The list of compounds can include common names, HMDB IDs or KEGG IDs with one compound per row. Compound concentration tables must have ...
The ‘KEGG Organisms’ section, which is divided into eukaryotes and prokaryotes, encompasses many organisms for which gene and DNA information can be searched by typing in the enzyme of choice. BioCyc, EcoCyc, and MetaCyc: BioCyc Is a collection of 3,000 pathway/genome databases (as of Oct 2013), with each database dedicated to one organism.
NASQAR (Nucleic Acid SeQuence Analysis Resource) is an open source, web-based platform for high-throughput sequencing data analysis and visualization. [9] [10] GSEA can be run using the R-based clusterProfiler package. [11] NASQAR currently supports GO Term and KEGG Pathway enrichment with all organisms supported by an Org.Db database. [12]
Following annotation, KEGG (Kyoto Encyclopedia of Genes and Genomes) enables visualization of metabolic pathways and molecular interaction networks captured in the transcriptome. [ 13 ] In addition to being annotated for GO terms, contigs can also be screened for open reading frames (ORFs) in order to predict the amino acid sequence of proteins ...