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Sergio Contrino

dblp:29/4458 · DBLP profile ↗
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4ranked-venue papers
0as first author
1since 2021 · last 2024
0000-0003-3409-5231ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 4 · 1 since 2021

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%
Databases, data mining, and information retrieval
1 paper
Data integration and cleaning · 50% Query processing and optimization · 50%

Topics — the 5 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › data integration
biological data integration
0.112012
InterMine: a flexible data warehouse system for the integration and analysis of heterogeneous biological data · Bioinform. 2012
Bioinformatics and computational biology › biological database
gene expression database
0.112005
The ArrayExpress gene expression database: a software engineering and implementation perspective · Bioinform. 2005
Bioinformatics and computational biology › biological database
microarray data management
0.112005
The ArrayExpress gene expression database: a software engineering and implementation perspective · Bioinform. 2005
Data integration and cleaning
heterogeneous data integration
0.012012
InterMine: a flexible data warehouse system for the integration and analysis of heterogeneous biological data · Bioinform. 2012
Bioinformatics and computational biology › protein sequence analysis
protein sequence annotation
0.011997
Protein Sequence Annotation in the Genome Era: The Annotation Concept of SWISS-PROT + TREMBL · ISMB 1997

Methods — techniques the papers use, named apart from their topics

web services · 0.3database design · 0.1
YearPublicationVenuePosition
2024 Sharing sensitive data in life sciences: an overview of centralized and federated approaches
abstract
Biomedical data are generated and collected from various sources, including medical imaging, laboratory tests and genome sequencing. Sharing these data for research can help address unmet health needs, contribute to scientific breakthroughs, accelerate the development of more effective treatments and inform public health policy. Due to the potential sensitivity of such data, however, privacy concerns have led to policies that restrict data sharing. In addition, sharing sensitive data requires a secure and robust infrastructure with appropriate storage solutions. Here, we examine and compare the centralized and federated data sharing models through the prism of five large-scale and real-world use cases of strategic significance within the European data sharing landscape: the French Health Data Hub, the BBMRI-ERIC Colorectal Cancer Cohort, the federated European Genome-phenome Archive, the Observational Medical Outcomes Partnership/OHDSI network and the EBRAINS Medical Informatics Platform. Our analysis indicates that centralized models facilitate data linkage, harmonization and interoperability, while federated models facilitate scaling up and legal compliance, as the data typically reside on the data generator's premises, allowing for better control of how data are shared. This comparative study thus offers guidance on the selection of the most appropriate sharing strategy for sensitive datasets and provides key insights for informed decision-making in data sharing efforts.
Maria Alexandra Rujano, Jan-Willem Boiten, Christian Ohmann, Steve Canham, Sergio Contrino, Romain David 0001, Jonathan Ewbank, Claudia Filippone, Claire Connellan, Ilse Custers, Rick van Nuland, Michaela Theresia Mayrhofer, Petr Holub, Eva García Álvarez, Emmanuel Bacry, Nigel Hughes, Mallory Ann Freeberg, Birgit Schaffhauser, Harald Wagener, Alex Sánchez-Pla, Guido Bertolini, Maria Panagiotopoulou
Briefings Bioinform.5
2012 InterMine: a flexible data warehouse system for the integration and analysis of heterogeneous biological data
abstract
SUMMARY: InterMine is an open-source data warehouse system that facilitates the building of databases with complex data integration requirements and a need for a fast customizable query facility. Using InterMine, large biological databases can be created from a range of heterogeneous data sources, and the extensible data model allows for easy integration of new data types. The analysis tools include a flexible query builder, genomic region search and a library of 'widgets' performing various statistical analyses. The results can be exported in many commonly used formats. InterMine is a fully extensible framework where developers can add new tools and functionality. Additionally, there is a comprehensive set of web services, for which client libraries are provided in five commonly used programming languages. AVAILABILITY: Freely available from http://www.intermine.org under the LGPL license. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Richard N. Smith, Jelena Aleksic, Daniela Butano, Adrian Carr, Sergio Contrino, Fengyuan Hu, Mike Lyne, Rachel Lyne, Alex Kalderimis, Kim Rutherford, Radek Stepan, Julie M. Sullivan, Matthew Wakeling, Xavier Watkins, Gos Micklem
Bioinform.5
2005 The ArrayExpress gene expression database: a software engineering and implementation perspective
abstract
MOTIVATION: The lack of microarray data management systems and databases is still one of the major problems faced by many life sciences laboratories. While developing the public repository for microarray data ArrayExpress we had to find novel solutions to many non-trivial software engineering problems. Our experience will be both relevant and useful for most bioinformaticians involved in developing information systems for a wide range of high-throughput technologies. RESULTS: ArrayExpress has been online since February 2002, growing exponentially to well over 10,000 hybridizations (as of September 2004). It has been demonstrated that our chosen design and implementation works for databases aimed at storage, access and sharing of high-throughput data. AVAILABILITY: The ArrayExpress database is available at http://www.ebi.ac.uk/arrayexpress/. The software is open source. CONTACT: [email protected].
Ugis Sarkans, Helen E. Parkinson, Gonzalo Garcia Lara, Ahmet Oezcimen, Anjan Sharma, Niran Abeygunawardena, Sergio Contrino, Ele Holloway, Philippe Rocca-Serra, Gaurab Mukherjee, Mohammadreza Shojatalab, Misha Kapushesky, Susanna-Assunta Sansone, Anna Farne, Tim F. Rayner, Alvis Brazma
Bioinform.7
1997 Protein Sequence Annotation in the Genome Era: The Annotation Concept of SWISS-PROT + TREMBL
Rolf Apweiler, Alain Gateau, Sergio Contrino, Maria Jesus Martin, Vivien Junker, Claire O'Donovan, Fiona Lang, Nicoletta Mitaritonna, Stephanie Kappus, Amos Bairoch
ISMB3