Ferran Sanz

Prof. Ferran Sanz


Research Focus & Metrics

Academic Career Length

52Years (1975-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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19 October 2016 in Nucleic Acids Research
Verified
Journal Article
Open access
PDF file
JPjanet pinero
janet pinero
ÀBÀlex Bravo
Àlex Bravo
NQNúria Queralt-Rosinach
Núria Queralt-Rosinach
AGAlba Gutiérrez-Sacristán
Alba Gutiérrez-Sacristán
JDJordi Deu-Pons
Jordi Deu-Pons
LFLaura I. Furlong
Laura I. Furlong
The information about the genetic basis of human diseases lies at the heart of precision medicine and drug discovery. However, to realize its full potential to support these goals, several problems, such as fragmentation, heterogeneity, availability and different conceptualization of the data must be overcome. To provide the community with a resource free of these hurdles, we have developed DisGeNET (http://www.disgenet.org), one of the largest available collections of genes and variants involved in human diseases. DisGeNET integrates data from expert curated repositories, GWAS catalogues, animal models and the scientific literature. DisGeNET data are homogeneously annotated with controlled vocabularies and community-driven ontologies. Additionally, several original metrics are provided to assist the prioritization of genotype–phenotype relationships. The information is accessible through a web interface, a Cytoscape App, an RDF SPARQL endpoint, scripts in several programming languages and an R package. DisGeNET is a versatile platform that can be used for different research purposes including the investigation of the molecular underpinnings of specific human diseases and their comorbidities, the analysis of the properties of disease genes, the generation of hypothesis on drug therapeutic action and drug adverse effects, the validation of computationally predicted disease genes and the evaluation of text-mining methods performance.

4 November 2019 in Nucleic Acids Research
Verified
Journal Article
Open access
PDF file
JPjanet pinero
janet pinero
JRJuan Manuel Ramírez-Anguita
Juan Manuel Ramírez-Anguita
JSJosep Saüch-Pitarch
Josep Saüch-Pitarch
FRFrancesco Ronzano
Francesco Ronzano
ECEmilio Centeno
Emilio Centeno
LFLaura I. Furlong
Laura I. Furlong
One of the most pressing challenges in genomic medicine is to understand the role played by genetic variation in health and disease. Thanks to the exploration of genomic variants at large scale, hundreds of thousands of disease-associated loci have been uncovered. However, the identification of variants of clinical relevance is a significant challenge that requires comprehensive interrogation of previous knowledge and linkage to new experimental results. To assist in this complex task, we created DisGeNET (http://www.disgenet.org/), a knowledge management platform integrating and standardizing data about disease associated genes and variants from multiple sources, including the scientific literature. DisGeNET covers the full spectrum of human diseases as well as normal and abnormal traits. The current release covers more than 24 000 diseases and traits, 17 000 genes and 117 000 genomic variants. The latest developments of DisGeNET include new sources of data, novel data attributes and prioritization metrics, a redesigned web interface and recently launched APIs. Thanks to the data standardization, the combination of expert curated information with data automatically mined from the scientific literature, and a suite of tools for accessing its publicly available data, DisGeNET is an interoperable resource supporting a variety of applications in genomic medicine and drug R&D.

1 January 2015 in Database: The Journal of Biological Databases and Curation
Verified
Journal Article
Open access
PDF file
JPjanet pinero
janet pinero
NQNúria Queralt-Rosinach
Núria Queralt-Rosinach
ÀBÀlex Bravo
Àlex Bravo
JDJordi Deu-Pons
Jordi Deu-Pons
ABAnna Bauer-Mehren
Anna Bauer-Mehren
LFLaura I. Furlong
Laura I. Furlong
DisGeNET is a comprehensive discovery platform designed to address a variety of questions concerning the genetic underpinning of human diseases. DisGeNET contains over 380 000 associations between >16 000 genes and 13 000 diseases, which makes it one of the largest repositories currently available of its kind. DisGeNET integrates expert-curated databases with text-mined data, covers information on Mendelian and complex diseases, and includes data from animal disease models. It features a score based on the supporting evidence to prioritize gene-disease associations. It is an open access resource available through a web interface, a Cytoscape plugin and as a Semantic Web resource. The web interface supports user-friendly data exploration and navigation. DisGeNET data can also be analysed via the DisGeNET Cytoscape plugin, and enriched with the annotations of other plugins of this popular network analysis software suite. Finally, the information contained in DisGeNET can be expanded and complemented using Semantic Web technologies and linked to a variety of resources already present in the Linked Data cloud. Hence, DisGeNET offers one of the most comprehensive collections of human gene-disease associations and a valuable set of tools for investigating the molecular mechanisms underlying diseases of genetic origin, designed to fulfill the needs of different user profiles, including bioinformaticians, biologists and health-care practitioners. Database URL: http://www.disgenet.org/

19 October 2017 in Archives of Toxicology
Verified
Journal Article
Closed access
PDF file
MLMarcel Leist
Marcel Leist
AGAhmed Ghallab
Ahmed Ghallab
RGRabea Graepel
Rabea Graepel
RMRosemarie Marchan
Rosemarie Marchan
RHReham Hassan
Reham Hassan
Jan G HengstlerJan G Hengstler
Jan G Hengstler

21 September 2010 in Bioinformatics
Verified
Journal Article
Closed access
ABAnna Bauer-Mehren
Anna Bauer-Mehren
MRMichael Rautschka
Michael Rautschka
FSFerran Sanz
Ferran Sanz
LFLaura I. Furlong
Laura I. Furlong
Summary: DisGeNET is a plugin for Cytoscape to query and analyze human gene–disease networks. DisGeNET allows user-friendly access to a new gene–disease database that we have developed by integrating data from several public sources. DisGeNET permits queries restricted to (i) the original data source, (ii) the association type, (iii) the disease class or (iv) specific gene(s)/disease(s). It represents gene–disease associations in terms of bipartite graphs and provides gene centric and disease centric views of the data. It assists the user in the interpretation and exploration of the genetic basis of human diseases by a variety of built-in functions. Moreover, DisGeNET permits multicolouring of nodes (genes/diseases) according to standard disease classification for expedient visualization. Availability: DisGeNET is compatible with Cytoscape 2.6.3 and 2.7.0, please visit http://ibi.imim.es/DisGeNET/DisGeNETweb.html for installation guide, user tutorial and download Contact: lfurlong@imim.es Supplementary information: Supplementary data are available at Bioinformatics online.

13 July 2020 in Nature Methods
Verified
Journal Article
Closed access
PDF file
IEIsmael Rodríguez Espigares
Ismael Rodríguez Espigares
MTMariona Torrens-Fontanals
Mariona Torrens-Fontanals
JTJohanna K. S. Tiemann
Johanna K. S. Tiemann
DADavid Aranda-García
David Aranda-García
JRJuan Manuel Ramírez-Anguita
Juan Manuel Ramírez-Anguita
JSJana Selent
Jana Selent