Paolo Romano
Research interests
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InterestsWeb Services, Semantic Web, Data Integration
Other
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Scientific MembershipsInternational Society for Computational Biology (ISCB)
Bioinformatics Italian Society (BITS) -
Journal RefereeBioinformatics
BMC Bioinformatics
Briefings in Bioinformatics
Database
Nucleic Acids Research -
Other InterestsBioinformatics Italian Society (BITS)
Publications
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3.43Impact points
Semantic Web Applications and Tools for the Life Sciences: SWAT4LS 2010.
BMC bioinformatics. 01/2012; 13 Suppl 1:S1.
As Semantic Web technologies mature and new releases of key elements, such as SPARQL 1.1 and OWL 2.0, become available, the Life Sciences continue to push the boundaries of these technologies with ever more sophisticated tools and applications. Unsurprisingly, therefore, interest in the SWAT4LS (Sem... [more] As Semantic Web technologies mature and new releases of key elements, such as SPARQL 1.1 and OWL 2.0, become available, the Life Sciences continue to push the boundaries of these technologies with ever more sophisticated tools and applications. Unsurprisingly, therefore, interest in the SWAT4LS (Semantic Web Applications and Tools for the Life Sciences) activities have remained high, as was evident during the third international SWAT4LS workshop held in Berlin in December 2010. Contributors to this workshop were invited to submit extended versions of their papers, the best of which are now made available in the special supplement of BMC Bioinformatics. The papers reflect the wide range of work in this area, covering the storage and querying of Life Sciences data in RDF triple stores, tools for the development of biomedical ontologies and the semantics-based integration of Life Sciences as well as clinicial data.
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3.43Impact points
Towards linked open gene mutations data.
BMC bioinformatics. 01/2012; 13 Suppl 4:S7.
With the advent of high-throughput technologies, a great wealth of variation data is being produced. Such information may constitute the basis for correlation analyses between genotypes and phenotypes and, in the future, for personalized medicine. Several databases on gene variation exist, but this ... [more] With the advent of high-throughput technologies, a great wealth of variation data is being produced. Such information may constitute the basis for correlation analyses between genotypes and phenotypes and, in the future, for personalized medicine. Several databases on gene variation exist, but this kind of information is still scarce in the Semantic Web framework.In this paper, we discuss issues related to the integration of mutation data in the Linked Open Data infrastructure, part of the Semantic Web framework. We present the development of a mapping from the IARC TP53 Mutation database to RDF and the implementation of servers publishing this data. A version of the IARC TP53 Mutation database implemented in a relational database was used as first test set. Automatic mappings to RDF were first created by using D2RQ and later manually refined by introducing concepts and properties from domain vocabularies and ontologies, as well as links to Linked Open Data implementations of various systems of biomedical interest.Since D2RQ query performances are lower than those that can be achieved by using an RDF archive, generated data was also loaded into a dedicated system based on tools from the Jena software suite. We have implemented a D2RQ Server for TP53 mutation data, providing data on a subset of the IARC database, including gene variations, somatic mutations, and bibliographic references. The server allows to browse the RDF graph by using links both between classes and to external systems. An alternative interface offers improved performances for SPARQL queries. The resulting data can be explored by using any Semantic Web browser or application. This has been the first case of a mutation database exposed as Linked Data. A revised version of our prototype, including further concepts and IARC TP53 Mutation database data sets, is under development.The publication of variation information as Linked Data opens new perspectives: the exploitation of SPARQL searches on mutation data and other biological databases may support data retrieval which is presently not possible. Moreover, reasoning on integrated variation data may support discoveries towards personalized medicine.
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7.33Impact points
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7.33Impact points
Tools and collaborative environments for bioinformatics research.
Briefings in bioinformatics. 11/2011; 12(6):549-61.
Advanced research requires intensive interaction among a multitude of actors, often possessing different expertise and usually working at a distance from each other. The field of collaborative research aims to establish suitable models and technologies to properly support these interactions. In this... [more] Advanced research requires intensive interaction among a multitude of actors, often possessing different expertise and usually working at a distance from each other. The field of collaborative research aims to establish suitable models and technologies to properly support these interactions. In this article, we first present the reasons for an interest of Bioinformatics in this context by also suggesting some research domains that could benefit from collaborative research. We then review the principles and some of the most relevant applications of social networking, with a special attention to networks supporting scientific collaboration, by also highlighting some critical issues, such as identification of users and standardization of formats. We then introduce some systems for collaborative document creation, including wiki systems and tools for ontology development, and review some of the most interesting biological wikis. We also review the principles of Collaborative Development Environments for software and show some examples in Bioinformatics. Finally, we present the principles and some examples of Learning Management Systems. In conclusion, we try to devise some of the goals to be achieved in the short term for the exploitation of these technologies.
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Biomedical semantics in the Semantic Web.
Journal of biomedical semantics. 01/2011; 2 Suppl 1:S1.
The Semantic Web offers an ideal platform for representing and linking biomedical information, which is a prerequisite for the development and application of analytical tools to address problems in data-intensive areas such as systems biology and translational medicine. As for any new paradigm, the ... [more] The Semantic Web offers an ideal platform for representing and linking biomedical information, which is a prerequisite for the development and application of analytical tools to address problems in data-intensive areas such as systems biology and translational medicine. As for any new paradigm, the adoption of the Semantic Web offers opportunities and poses questions and challenges to the life sciences scientific community: which technologies in the Semantic Web stack will be more beneficial for the life sciences? Is biomedical information too complex to benefit from simple interlinked representations? What are the implications of adopting a new paradigm for knowledge representation? What are the incentives for the adoption of the Semantic Web, and who are the facilitators? Is there going to be a Semantic Web revolution in the life sciences?We report here a few reflections on these questions, following discussions at the SWAT4LS (Semantic Web Applications and Tools for Life Sciences) workshop series, of which this Journal of Biomedical Semantics special issue presents selected papers from the 2009 edition, held in Amsterdam on November 20th.
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7.48Impact points
IBWS: IST Bioinformatics Web Services.
Nucleic acids research. 07/2010; 38(Web Server issue):W712-8.
The Bioinformatics group at the National Cancer Research Institute (IST) of Genoa has been involved since many years in the development and maintenance of biomedical information systems. Among them, the Common Access to Biological Resources and Information network services offer access to more than ... [more] The Bioinformatics group at the National Cancer Research Institute (IST) of Genoa has been involved since many years in the development and maintenance of biomedical information systems. Among them, the Common Access to Biological Resources and Information network services offer access to more than 130,000 biological resources, like strains of micro-organisms and human and animal cell lines, included in 29 collections from some of the most known European Biological Resource Centers. An Sequence Retrieval System (SRS) implementation of the TP53 Mutation Database of the International Agency for Research on Cancer (Lyon) was made available in order to improve interoperability of this data with other molecular biology databases. 'SRS by WS (SWS)', a system for retrieving information on public SRS sites and for directly querying them, was also implemented. In order to make this information available through application programming interfaces, we implemented a suite of free web services (WS), called the 'IST Bioinformatics Web Services (IBWS)'. A support web site, including a description of the system, a list of available WS together with help pages, links to corresponding WSDLs and forms for testing services, is available at http://bioinformatics.istge.it/ibws/. WSDL definitions can also be retrieved directly at http://bioinformatics.istge.it:8080/axis/services.
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Complex Search, Ranks, and Biological Discovery: A User's Perspective.
Search Computing - Trends and Developments [outcome of the second SeCO Workshop on Search Computing, Como/Milan, Italy, May 25-31, 2010]; 01/2010
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3.43Impact points
Trends in modeling Biomedical Complex Systems.
BMC bioinformatics. 01/2009; 10 Suppl 12:I1.
In this paper we provide an introduction to the techniques for multi-scale complex biological systems, from the single bio-molecule to the cell, combining theoretical modeling, experiments, informatics tools and technologies suitable for biological and biomedical research, which are becoming increas... [more] In this paper we provide an introduction to the techniques for multi-scale complex biological systems, from the single bio-molecule to the cell, combining theoretical modeling, experiments, informatics tools and technologies suitable for biological and biomedical research, which are becoming increasingly multidisciplinary, multidimensional and information-driven. The most important concepts on mathematical modeling methodologies and statistical inference, bioinformatics and standards tools to investigate complex biomedical systems are discussed and the prominent literature useful to both the practitioner and the theoretician are presented.
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3.43Impact points
Survival Online: a web-based service for the analysis of correlations between gene expression and clinical and follow-up data.
BMC bioinformatics. 01/2009; 10 Suppl 12:S10.
BACKGROUND : Complex microarray gene expression datasets can be used for many independent analyses and are particularly interesting for the validation of potential biomarkers and multi-gene classifiers. This article presents a novel method to perform correlations between microarray gene expression d... [more] BACKGROUND : Complex microarray gene expression datasets can be used for many independent analyses and are particularly interesting for the validation of potential biomarkers and multi-gene classifiers. This article presents a novel method to perform correlations between microarray gene expression data and clinico-pathological data through a combination of available and newly developed processing tools. RESULTS : We developed Survival Online (available at http://ada.dist.unige.it:8080/enginframe/bioinf/bioinf.xml), a Web-based system that allows for the analysis of Affymetrix GeneChip microarrays by using a parallel version of dChip. The user is first enabled to select pre-loaded datasets or single samples thereof, as well as single genes or lists of genes. Expression values of selected genes are then correlated with sample annotation data by uni- or multi-variate Cox regression and survival analyses. The system was tested using publicly available breast cancer datasets and GO (Gene Ontology) derived gene lists or single genes for survival analyses. CONCLUSION : The system can be used by bio-medical researchers without specific computation skills to validate potential biomarkers or multi-gene classifiers. The design of the service, the parallelization of pre-processing tasks and the implementation on an HPC (High Performance Computing) environment make this system a useful tool for validation on several independent datasets.
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Semantic Web Applications and Tools for Life Sciences, 2008 - Introduction.
BMC Bioinformatics. 01/2009; 10:1.
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Survival Online: a web-based service for the analysis of correlations between gene expression and clinical and follow-up data.
BMC Bioinformatics. 01/2009; 10:10.
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3.43Impact points
Semantic Web Applications and Tools for Life Sciences, 2008--preface.
BMC bioinformatics. 01/2009; 10 Suppl 10:S1.
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Trends in modeling Biomedical Complex Systems
BMC Bioinformatics. 01/2009;
Abstract In this paper we provide an introduction to the techniques for multi-scale complex biological systems, from the single bio-molecule to the cell, combining theoretical modeling, experiments, informatics tools and technologies suitable for biological and biomedical research, which are becomi... [more] Abstract In this paper we provide an introduction to the techniques for multi-scale complex biological systems, from the single bio-molecule to the cell, combining theoretical modeling, experiments, informatics tools and technologies suitable for biological and biomedical research, which are becoming increasingly multidisciplinary, multidimensional and information-driven. The most important concepts on mathematical modeling methodologies and statistical inference, bioinformatics and standards tools to investigate complex biomedical systems are discussed and the prominent literature useful to both the practitioner and the theoretician are presented.
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7.48Impact points
Cell Line Data Base: structure and recent improvements towards molecular authentication of human cell lines.
Nucleic acids research. 11/2008;
The Cell Line Data Base (CLDB) is a well-known reference information source on human and animal cell lines including information on more than 6000 cell lines. Main biological features are coded according to controlled vocabularies derived from international lists and taxonomies. HyperCLDB (http://bi... [more] The Cell Line Data Base (CLDB) is a well-known reference information source on human and animal cell lines including information on more than 6000 cell lines. Main biological features are coded according to controlled vocabularies derived from international lists and taxonomies. HyperCLDB (http://bioinformatics.istge.it/hypercldb/) is a hypertext version of CLDB that improves data accessibility by also allowing information retrieval through web spiders. Access to HyperCLDB is provided through indexes of biological characteristics and navigation in the hypertext is granted by many internal links. HyperCLDB also includes links to external resources. Recently, an interest was raised for a reference nomenclature for cell lines and CLDB was seen as an authoritative system. Furthermore, to overcome the cell line misidentification problem, molecular authentication methods, such as fingerprinting, single-locus short tandem repeat (STR) profile and single nucleotide polymorphisms validation, were proposed. Since this data is distributed, a reference portal on authentication of human cell lines is needed. We present here the architecture and contents of CLDB, its recent enhancements and perspectives. We also present a new related database, the Cell Line Integrated Molecular Authentication (CLIMA) database (http://bioinformatics.istge.it/clima/), that allows to link authentication data to actual cell lines.
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3.43Impact points
A Semantic Web for bioinformatics: goals, tools, systems, applications.
BMC bioinformatics. 02/2008; 9 Suppl 4:S1.
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3.43Impact points
SWS: accessing SRS sites contents through Web Services.
BMC bioinformatics. 02/2008; 9 Suppl 2:S15.
BACKGROUND: Web Services and Workflow Management Systems can support creation and deployment of network systems, able to automate data analysis and retrieval processes in biomedical research. Web Services have been implemented at bioinformatics centres and workflow systems have been proposed for bio... [more] BACKGROUND: Web Services and Workflow Management Systems can support creation and deployment of network systems, able to automate data analysis and retrieval processes in biomedical research. Web Services have been implemented at bioinformatics centres and workflow systems have been proposed for biological data analysis.New databanks are often developed by taking into account these technologies, but many existing databases do not allow a programmatic access. Only a fraction of available databanks can thus be queried through programmatic interfaces. SRS is a well know indexing and search engine for biomedical databanks offering public access to many databanks and analysis tools. Unfortunately, these data are not easily and efficiently accessible through Web Services. RESULTS: We have developed 'SRS by WS' (SWS), a tool that makes information available in SRS sites accessible through Web Services. Information on known sites is maintained in a database, srsdb. SWS consists in a suite of WS that can query both srsdb, for information on sites and databases, and SRS sites. SWS returns results in a text-only format and can be accessed through a WSDL compliant client. SWS enables interoperability between workflow systems and SRS implementations, by also managing access to alternative sites, in order to cope with network and maintenance problems, and selecting the most up-to-date among available systems. CONCLUSIONS: Development and implementation of Web Services, allowing to make a programmatic access to an exhaustive set of biomedical databases can significantly improve automation of in-silico analysis. SWS supports this activity by making biological databanks that are managed in public SRS sites available through a programmatic interface.
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7.33Impact points
Automation of in-silico data analysis processes through workflow management systems.
Briefings in bioinformatics. 02/2008; 9(1):57-68.
Data integration is needed in order to cope with the huge amounts of biological information now available and to perform data mining effectively. Current data integration systems have strict limitations, mainly due to the number of resources, their size and frequency of updates, their heterogeneity ... [more] Data integration is needed in order to cope with the huge amounts of biological information now available and to perform data mining effectively. Current data integration systems have strict limitations, mainly due to the number of resources, their size and frequency of updates, their heterogeneity and distribution on the Internet. Integration must therefore be achieved by accessing network services through flexible and extensible data integration and analysis network tools. EXtensible Markup Language (XML), Web Services and Workflow Management Systems (WMS) can support the creation and deployment of such systems. Many XML languages and Web Services for bioinformatics have already been designed and implemented and some WMS have been proposed. In this article, we review a methodology for data integration in biomedical research that is based on these technologies. We also briefly describe some of the available WMS and discuss the current limitations of this methodology and the ways in which they can be overcome.
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Applications of Semantic Web Methodologies and Techniques to Biology and Bioinformatics.
Reasoning Web, 4th International Summer School 2008, Venice, Italy, September 7-11, 2008, Tutorial Lectures; 01/2008
Following (9)
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Pierre Lindenbaum
Inserm -
Paolo Bouquet
Università degli Studi di Trento -
Mario Cannataro
Universita' degli Studi "Magna Græcia" di Catanzaro -
Graziano Pesole
Università degli Studi di Bari Aldo Moro