References of "Pavlopoulos, Georgios"
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See detailOnTheFly 2.0: a tool for automatic annotation of files and biological information extraction.
Pafilis, Evangelos; Pavlopoulos, Georgios; Satagopam, Venkata UL et al

Poster (2013)

Retrieving all of the necessary information from databases about bioentities mentioned in an article is not a trivial or an easy task. Following the daily literature about a specific biological topic and ... [more ▼]

Retrieving all of the necessary information from databases about bioentities mentioned in an article is not a trivial or an easy task. Following the daily literature about a specific biological topic and collecting all the necessary information about the bioentities mentioned in the literature manually is tedious and time consuming. OnTheFly 2.0 is a web application mainly designed for non-computer experts which aims to automate data collection and knowledge extraction from biological literature in a user friendly and efficient way. OnTheFly 2.0 is able to extract bioentities from individual articles such as text, Microsoft Word, Excel and PDF files. With a simple drag-and-drop motion, the text of a document is extensively parsed for bioentities such as protein/gene names and chemical compound names. Utilizing high quality data integration platforms, OnTheFly allows the generation of informative summaries, interaction networks and at-a-glance popup windows containing knowledge related to the bioentities found in documents. OnTheFly 2.0 provides a concise application to automate the extraction of bioentities hidden in various documents and is offered as a web based application. [less ▲]

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See detailHuman gene correlation analysis (HGCA): A tool for the identification of transcriptionally co-expressed genes
Michalopoulos, Ioannis; Pavlopoulos, Georgios; Malatras, Apostolos et al

in BMC Research Notes (2012), 5(265), 1-11

Background: Bioinformatics and high-throughput technologies such as microarray studies allow the measure of the expression levels of large numbers of genes simultaneously, thus helping us to understand ... [more ▼]

Background: Bioinformatics and high-throughput technologies such as microarray studies allow the measure of the expression levels of large numbers of genes simultaneously, thus helping us to understand the molecular mechanisms of various biological processes in a cell. Findings: We calculate the Pearson Correlation Coefficient (r-value) between probe set signal values from Affymetrix Human Genome Microarray samples and cluster the human genes according to the r-value correlation matrix using the Neighbour Joining (NJ) clustering method. A hyper-geometric distribution is applied on the text annotations of the probe sets to quantify the term overrepresentations. The aim of the tool is the identification of closely correlated genes for a given gene of interest and/or the prediction of its biological function, which is based on the annotations of the respective gene cluster. Conclusion: Human Gene Correlation Analysis (HGCA) is a tool to classify human genes according to their coexpression levels and to identify overrepresented annotation terms in correlated gene groups. It is available at: http://biobank-informatics.bioacademy.gr/coexpression/. [less ▲]

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