Demo Data from EDBT 2026 / reviewers in the wild / expert
Gabriela Bindea
dblp:36/7063
· DBLP profile ↗
4ranked-venue papers
2as first author
0since 2021 · last 2019
0000-0001-6013-6645ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 4 · 2 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
3 papers |
Bioinformatics and computational biology · 100% |
Topics — the 5 heaviest of 7, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › systems bioinformatics
pathway analysis |
0.6 | 3 | 2019 | Automated exploration of gene ontology term and pathway networks with ClueGO-REST · Bioinform. 2019 CluePedia Cytoscape plugin: pathway insights using integrated experimental and in silico data · Bioinform. 2013 ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks · Bioinform. 2009 |
Bioinformatics and computational biology › functional genomics
functional enrichment analysis |
0.5 | 2 | 2019 | Automated exploration of gene ontology term and pathway networks with ClueGO-REST · Bioinform. 2019 ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks · Bioinform. 2009 |
Bioinformatics and computational biology › functional genomics › functional enrichment analysis
gene set enrichment analysis |
0.2 | 1 | 2013 | CluePedia Cytoscape plugin: pathway insights using integrated experimental and in silico data · Bioinform. 2013 |
Bioinformatics and computational biology › systems bioinformatics › pathway analysis
pathway visualization |
0.2 | 1 | 2013 | CluePedia Cytoscape plugin: pathway insights using integrated experimental and in silico data · Bioinform. 2013 |
Bioinformatics and computational biology › protein function prediction
gene ontology annotation |
0.1 | 1 | 2009 | ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks · Bioinform. 2009 |
Methods — techniques the papers use, named apart from their topics
cytoscape · 0.4REST API · 0.4statistical dependency analysis · 0.2enrichment analysis · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Automated exploration of gene ontology term and pathway networks with ClueGO-RESTabstractSUMMARY: Large scale technologies produce massive amounts of experimental data that need to be investigated. To improve their biological interpretation we have developed ClueGO, a Cytoscape App that selects representative Gene Onology terms and pathways for one or multiple lists of genes/proteins and visualizes them into functionally organized networks. Because of its reliability, userfriendliness and support of many species ClueGO gained a large community of users. To further allow scientists programmatic access to ClueGO with R, Python, JavaScript etc., we implemented the cyREST API into ClueGO. In this article we describe this novel, complementary way of accessing ClueGO via REST, and provide R and Phyton examples to demonstrate how ClueGO workflows can be integrated into bioinformatic analysis pipelines. AVAILABILITY AND IMPLEMENTATION: ClueGO is available in the Cytoscape App Store (http://apps.cytoscape.org/apps/cluego). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Bernhard Mlecnik, Jérôme Galon, Gabriela Bindea |
Bioinform. | 3 |
| 2013 | CluePedia Cytoscape plugin: pathway insights using integrated experimental and in silico dataabstractSUMMARY: The CluePedia Cytoscape plugin is a search tool for new markers potentially associated to pathways. CluePedia calculates linear and non-linear statistical dependencies from experimental data. Genes, proteins and miRNAs can be connected based on in silico and/or experimental information and integrated into a ClueGO network of terms/pathways. Interrelations within each pathway can be investigated, and new potential associations may be revealed through gene/protein/miRNA enrichments. A pathway-like visualization can be created using the Cerebral plugin layout. Combining all these features is essential for data interpretation and the generation of new hypotheses. The CluePedia Cytoscape plugin is user-friendly and has an expressive and intuitive visualization. AVAILABILITY: http://www.ici.upmc.fr/cluepedia/ and via the Cytoscape plugin manager. The user manual is available at the CluePedia website. Gabriela Bindea, Jérôme Galon, Bernhard Mlecnik |
Bioinform. | 1 |
| 2009 | ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networksabstractAbstract Summary: We have developed ClueGO, an easy to use Cytoscape plug-in that strongly improves biological interpretation of large lists of genes. ClueGO integrates Gene Ontology (GO) terms as well as KEGG/BioCarta pathways and creates a functionally organized GO/pathway term network. It can analyze one or compare two lists of genes and comprehensively visualizes functionally grouped terms. A one-click update option allows ClueGO to automatically download the most recent GO/KEGG release at any time. ClueGO provides an intuitive representation of the analysis results and can be optionally used in conjunction with the GOlorize plug-in. Availability: http://www.ici.upmc.fr/cluego/cluegoDownload.shtml Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online. Gabriela Bindea, Bernhard Mlecnik, Hubert Hackl, Pornpimol Charoentong, Marie Tosolini, Amos Kirilovsky, Wolf-Herman Fridman, Franck Pagès, Zlatko Trajanoski, Jérôme Galon |
Bioinform. | 1 |
| 2009 | iLAP: a workflow-driven software for experimental protocol development, data acquisition and analysisabstractBACKGROUND: In recent years, the genome biology community has expended considerable effort to confront the challenges of managing heterogeneous data in a structured and organized way and developed laboratory information management systems (LIMS) for both raw and processed data. On the other hand, electronic notebooks were developed to record and manage scientific data, and facilitate data-sharing. Software which enables both, management of large datasets and digital recording of laboratory procedures would serve a real need in laboratories using medium and high-throughput techniques. RESULTS: We have developed iLAP (Laboratory data management, Analysis, and Protocol development), a workflow-driven information management system specifically designed to create and manage experimental protocols, and to analyze and share laboratory data. The system combines experimental protocol development, wizard-based data acquisition, and high-throughput data analysis into a single, integrated system. We demonstrate the power and the flexibility of the platform using a microscopy case study based on a combinatorial multiple fluorescence in situ hybridization (m-FISH) protocol and 3D-image reconstruction. iLAP is freely available under the open source license AGPL from http://genome.tugraz.at/iLAP/. CONCLUSION: iLAP is a flexible and versatile information management system, which has the potential to close the gap between electronic notebooks and LIMS and can therefore be of great value for a broad scientific community. Gernot Stocker, Maria Fischer, Dietmar Rieder, Gabriela Bindea, Simon Kainz, Michael Oberstolz, James G. McNally, Zlatko Trajanoski |
BMC Bioinform. | 4 |