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Find video protocols related to scientific articles indexed in Pubmed.
DDMGD: the database of text-mined associations between genes methylated in diseases from different species.
Nucleic Acids Res.
PUBLISHED: 11-16-2014
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Gathering information about associations between methylated genes and diseases is important for diseases diagnosis and treatment decisions. Recent advancements in epigenetics research allow for large-scale discoveries of associations of genes methylated in diseases in different species. Searching manually for such information is not easy, as it is scattered across a large number of electronic publications and repositories. Therefore, we developed DDMGD database (http://www.cbrc.kaust.edu.sa/ddmgd/) to provide a comprehensive repository of information related to genes methylated in diseases that can be found through text mining. DDMGD's scope is not limited to a particular group of genes, diseases or species. Using the text mining system DEMGD we developed earlier and additional post-processing, we extracted associations of genes methylated in different diseases from PubMed Central articles and PubMed abstracts. The accuracy of extracted associations is 82% as estimated on 2500 hand-curated entries. DDMGD provides a user-friendly interface facilitating retrieval of these associations ranked according to confidence scores. Submission of new associations to DDMGD is provided. A comparison analysis of DDMGD with several other databases focused on genes methylated in diseases shows that DDMGD is comprehensive and includes most of the recent information on genes methylated in diseases.
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Aberrant methylation of NPY, PENK, and WIF1 as a promising marker for blood-based diagnosis of colorectal cancer.
BMC Cancer
PUBLISHED: 08-05-2013
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DNA methylation is a well-known epigenetic mechanism involved in epigenetic gene regulation. Several genes were reported hypermethylated in CRC, althought no gene marker was proven to be individually of sufficient sensitivity or specificity in routine clinical practice. Here, we identified novel epigenetic markers and assessed their combined use for diagnostic accuracy.
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Combining position weight matrices and document-term matrix for efficient extraction of associations of methylated genes and diseases from free text.
PLoS ONE
PUBLISHED: 01-01-2013
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In a number of diseases, certain genes are reported to be strongly methylated and thus can serve as diagnostic markers in many cases. Scientific literature in digital form is an important source of information about methylated genes implicated in particular diseases. The large volume of the electronic text makes it difficult and impractical to search for this information manually.
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Profiling target genes of FGF18 in the postnatal mouse lung: possible relevance for alveolar development.
Physiol. Genomics
PUBLISHED: 08-30-2011
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Better understanding alveolarization mechanisms could help improve prevention and treatment of diseases characterized by reduced alveolar number. Although signaling through fibroblast growth factor (FGF) receptors is essential for alveolarization, involved ligands are unidentified. FGF18, the expression of which peaks coincidentally with alveolar septation, is likely to be involved. Herein, a mouse model with inducible, lung-targeted FGF18 transgene was used to advance the onset of FGF18 expression peak, and genome-wide expression changes were determined by comparison with littermate controls. Quantitative RT-PCR was used to confirm expression changes of selected up- and downregulated genes and to determine their expression profiles in the course of lung postnatal development. This allowed identifying so-far unknown target genes of the factor, among which a number are known to be involved in alveolarization. The major target was adrenomedullin, a promoter of lung angiogenesis and alveolar development, whose transcript was increased 6.9-fold. Other genes involved in angiogenesis presented marked expression increases, including Wnt2 and cullin2. Although it appeared to favor cell migration notably through enhanced expression of Snai1/2, FGF18 also induced various changes consistent with prevention of epithelial-mesenchymal transition. Together with antifibrotic effects driven by induction of E prostanoid receptor 2 and repression of numerous myofibroblast markers, this could prevent alveolar septation-driving mechanisms from becoming excessive and deleterious. Last, FGF18 up- or downregulated genes of extracellular matrix components and epithelial cell markers previously shown to be up- or downregulated during alveolarization. These findings therefore argue for an involvement of FGF18 in the control of various developmental events during the alveolar stage.
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Identification of SPOCK2 as a susceptibility gene for bronchopulmonary dysplasia.
Am. J. Respir. Crit. Care Med.
PUBLISHED: 08-11-2011
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Bronchopulmonary dysplasia is the most common chronic respiratory disease in premature infants. Genetic factors might contribute to bronchopulmonary dysplasia susceptibility.
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[Breast cancer: nomograms to predict pathologic response after preoperative chemotherapy].
J Med Liban
PUBLISHED: 07-24-2009
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If the benefit of adjuvant chemotherapy may be determined at the level of a population, to determine the real chemosensitivity of a tumor at the individual level is impossible. The concept of neoadjuvant chemotherapy in patients with localized breast cancer is interesting because it helps to know the chemosensitivity of a tumor "in vivo". It is possible to use a single criterion to predict the effectiveness of targeted therapies. The chemotherapy is not a targeted therapy, and to determine a biological predictive marker of the response has been impossible so far. The development of mathematical models and use of molecular biology may help to predict chemosensitivity. Initial results are promising. The validation of published works is necessary, but applications are numerous.
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Direct comparison of logistic regression and recursive partitioning to predict chemotherapy response of breast cancer based on clinical pathological variables.
Breast Cancer Res. Treat.
PUBLISHED: 01-02-2009
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The purpose was to compare logistic regression model (LRM) and recursive partitioning (RP) to predict pathologic complete response to preoperative chemotherapy in patients with breast cancer. The two models were built in a same training set of 496 patients and validated in a same validation set of 337 patients. Model performance was quantified with respect to discrimination (evaluated by the areas under the receiver operating characteristics curves (AUC)) and calibration. In the training set, AUC were similar for LRM and RP models (0.77 (95% confidence interval, 0.74-0.80) and 0.75 (95% CI, 0.74-0.79), respectively) while LRM outperformed RP in the validation set (0.78 (95% CI, 0.74-0.82) versus 0.64 (95% CI, 0.60-0.67). LRM model also outperformed RP model in term of calibration. In these real datasets, LRM model outperformed RP model. It is therefore more suitable for clinical use.
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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.