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Find video protocols related to scientific articles indexed in Pubmed.
A method for increasing expressivity of Gene Ontology annotations using a compositional approach.
BMC Bioinformatics
PUBLISHED: 03-04-2014
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The Gene Ontology project integrates data about the function of gene products across a diverse range of organisms, allowing the transfer of knowledge from model organisms to humans, and enabling computational analyses for interpretation of high-throughput experimental and clinical data. The core data structure is the annotation, an association between a gene product and a term from one of the three ontologies comprising the GO. Historically, it has not been possible to provide additional information about the context of a GO term, such as the target gene or the location of a molecular function. This has limited the specificity of knowledge that can be expressed by GO annotations.
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An integrated ontology resource to explore and study host-virus relationships.
PLoS ONE
PUBLISHED: 01-01-2014
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Our growing knowledge of viruses reveals how these pathogens manage to evade innate host defenses. A global scheme emerges in which many viruses usurp key cellular defense mechanisms and often inhibit the same components of antiviral signaling. To accurately describe these processes, we have generated a comprehensive dictionary for eukaryotic host-virus interactions. This controlled vocabulary has been detailed in 57 ViralZone resource web pages which contain a global description of all molecular processes. In order to annotate viral gene products with this vocabulary, an ontology has been built in a hierarchy of UniProt Knowledgebase (UniProtKB) keyword terms and corresponding Gene Ontology (GO) terms have been developed in parallel. The results are 65 UniProtKB keywords related to 57 GO terms, which have been used in 14,390 manual annotations; 908,723 automatic annotations and propagated to an estimation of 922,941 GO annotations. ViralZone pages, UniProtKB keywords and GO terms provide complementary tools to users, and the three resources have been linked to each other through host-virus vocabulary.
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Representing kidney development using the gene ontology.
PLoS ONE
PUBLISHED: 01-01-2014
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Gene Ontology (GO) provides dynamic controlled vocabularies to aid in the description of the functional biological attributes and subcellular locations of gene products from all taxonomic groups (www.geneontology.org). Here we describe collaboration between the renal biomedical research community and the GO Consortium to improve the quality and quantity of GO terms describing renal development. In the associated annotation activity, the new and revised terms were associated with gene products involved in renal development and function. This project resulted in a total of 522 GO terms being added to the ontology and the creation of approximately 9,600 kidney-related GO term associations to 940 UniProt Knowledgebase (UniProtKB) entries, covering 66 taxonomic groups. We demonstrate the impact of these improvements on the interpretation of GO term analyses performed on genes differentially expressed in kidney glomeruli affected by diabetic nephropathy. In summary, we have produced a resource that can be utilized in the interpretation of data from small- and large-scale experiments investigating molecular mechanisms of kidney function and development and thereby help towards alleviating renal disease.
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Nuclear phosphoinositides and their impact on nuclear functions.
FEBS J.
PUBLISHED: 07-22-2013
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Polyphosphoinositides (PPIn) are important lipid molecules whose levels are de-regulated in human diseases such as cancer, neurodegenerative disorders and metabolic syndromes. PPIn are synthesized and degraded by an array of kinases, phosphatases and lipases which are localized to various subcellular compartments and are subject to regulation in response to both extra- and intracellular cues. Changes in the activities of enzymes that metabolize PPIn lead to changes in the profiles of PPIn in various subcellular compartments. Understanding how subcellular PPIn are regulated and how they affect downstream signaling is critical to understanding their roles in human diseases. PPIn are present in the nucleus, and their levels are changed in response to various stimuli, suggesting that they may serve to regulate specific nuclear functions. However, the lack of nuclear downstream targets has hindered the definition of which pathways nuclear PPIn affect. Over recent years, targeted and global proteomic studies have identified a plethora of potential PPIn-interacting proteins involved in many aspects of transcription, chromatin remodelling and mRNA maturation, suggesting that PPIn signalling within the nucleus represents a largely unexplored novel layer of complexity in the regulation of nuclear functions.
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The Gene Ontology (GO) Cellular Component Ontology: integration with SAO (Subcellular Anatomy Ontology) and other recent developments.
J Biomed Semantics
PUBLISHED: 06-21-2013
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The Gene Ontology (GO) (http://www.geneontology.org/) contains a set of terms for describing the activity and actions of gene products across all kingdoms of life. Each of these activities is executed in a location within a cell or in the vicinity of a cell. In order to capture this context, the GO includes a sub-ontology called the Cellular Component (CC) ontology (GO-CCO). The primary use of this ontology is for GO annotation, but it has also been used for phenotype annotation, and for the annotation of images. Another ontology with similar scope to the GO-CCO is the Subcellular Anatomy Ontology (SAO), part of the Neuroscience Information Framework Standard (NIFSTD) suite of ontologies. The SAO also covers cell components, but in the domain of neuroscience.
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Dovetailing biology and chemistry: integrating the Gene Ontology with the ChEBI chemical ontology.
BMC Genomics
PUBLISHED: 03-07-2013
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The Gene Ontology (GO) facilitates the description of the action of gene products in a biological context. Many GO terms refer to chemical entities that participate in biological processes. To facilitate accurate and consistent systems-wide biological representation, it is necessary to integrate the chemical view of these entities with the biological view of GO functions and processes. We describe a collaborative effort between the GO and the Chemical Entities of Biological Interest (ChEBI) ontology developers to ensure that the representation of chemicals in the GO is both internally consistent and in alignment with the chemical expertise captured in ChEBI.
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PtdIns5P is an oxidative stress-induced second messenger that regulates PKB activation.
FASEB J.
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Oxidative stress initiates signaling pathways, which protect from stress-induced cellular damage, initiate apoptosis, or drive cells into senescence or into tumorigenesis. Oxidative stress regulates the activity of the cell survival factor PKB, through the regulation of PtdIns(3,4,5)P? synthesis. Whether oxidative stress regulates other phosphoinositides to control PKB activation is not clear. Here we show that PtdIns5P is a redox-regulated second messenger. In response to hydrogen peroxide (H?O?), we measured an increase in PtdIns5P in cells derived from human osteosarcoma, U2OS (5-fold); breast tumors, MDA-MB-468 (2-fold); and fibrosarcoma, HT1080 (3-fold); and in p53-null murine embryonic fibroblasts (8-fold). In U2OS cells, the increase in H?O?-dependent PtdIns5P did not require mTOR, PDK1, PKB, ERK, and p38 signaling or PIKfyve, a lipid kinase that increases PtdIns5P in response to osmotic and oncogenic signaling. A reduction in H?O?-induced PtdIns5P levels by the overexpression of PIP4K revealed its role in PKB activation. Suppression of H?O?-induced PtdIns5P generation reduced PKB activation and, surprisingly, reduced cell sensitivity to growth inhibition by H?O?. These data suggest that inhibition of PIP4K signaling might be useful as a novel strategy to increase the susceptibility of tumor cells to therapeutics that function through increased oxidative stress.
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What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.