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  1. Article ; Online: Data quality-aware genomic data integration

    Anna Bernasconi

    Computer Methods and Programs in Biomedicine Update, Vol 1, Iss , Pp 100009- (2021)

    2021  

    Abstract: Genomic data are growing at unprecedented pace, along with new protocols, update polices, formats and guidelines, terminologies and ontologies, which are made available every day by data providers. In this continuously evolving universe, enforcing ... ...

    Abstract Genomic data are growing at unprecedented pace, along with new protocols, update polices, formats and guidelines, terminologies and ontologies, which are made available every day by data providers. In this continuously evolving universe, enforcing quality on data and metadata is increasingly critical. While many aspects of data quality are addressed at each individual source, we focus on the need for a systematic approach when data from several sources are integrated, as such integration is an essential aspect for modern genomic data analysis. Data quality must be assessed from many perspectives, including accessibility, currency, representational consistency, specificity, and reliability.In this article we review relevant literature and, based on the analysis of many datasets and platforms, we report on methods used for guaranteeing data quality while integrating heterogeneous data sources. We explore several real-world cases that are exemplary of more general underlying data quality problems and we illustrate how they can be resolved with a structured method, sensibly applicable also to other biomedical domains. The overviewed methods are implemented in a large framework for the integration of processed genomic data, which is made available to the research community for supporting tertiary data analysis over Next Generation Sequencing datasets, continuously loaded from many open data sources, bringing considerable added value to biological knowledge discovery.
    Keywords Data quality ; Data integration ; Data curation ; Genomic datasets ; Metadata ; Interoperability ; Computer applications to medicine. Medical informatics ; R858-859.7
    Subject code 004
    Language English
    Publishing date 2021-01-01T00:00:00Z
    Publisher Elsevier
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Editorial

    Elizabeth A. Heron / Giorgio Valle / Anna Bernasconi

    Frontiers in Bioinformatics, Vol

    Identification of phenotypically important genomic variants

    2023  Volume 3

    Keywords next-generation sequencing (NGS) ; genomic variant ; prioritisation ; interpretation ; annotation ; Computer applications to medicine. Medical informatics ; R858-859.7
    Language English
    Publishing date 2023-11-01T00:00:00Z
    Publisher Frontiers Media S.A.
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: Semantic interoperability

    Anna Bernasconi / Giancarlo Guizzardi / Oscar Pastor / Veda C. Storey

    BMC Bioinformatics, Vol 23, Iss S11, Pp 1-

    ontological unpacking of a viral conceptual model

    2022  Volume 22

    Abstract: Abstract Background Genomics and virology are unquestionably important, but complex, domains being investigated by a large number of scientists. The need to facilitate and support work within these domains requires sharing of databases, although it is ... ...

    Abstract Abstract Background Genomics and virology are unquestionably important, but complex, domains being investigated by a large number of scientists. The need to facilitate and support work within these domains requires sharing of databases, although it is often difficult to do so because of the different ways in which data is represented across the databases. To foster semantic interoperability, models are needed that provide a deep understanding and interpretation of the concepts in a domain, so that the data can be consistently interpreted among researchers. Results In this research, we propose the use of conceptual models to support semantic interoperability among databases and assess their ontological clarity to support their effective use. This modeling effort is illustrated by its application to the Viral Conceptual Model (VCM) that captures and represents the sequencing of viruses, inspired by the need to understand the genomic aspects of the virus responsible for COVID-19. For achieving semantic clarity on the VCM, we leverage the “ontological unpacking” method, a process of ontological analysis that reveals the ontological foundation of the information that is represented in a conceptual model. This is accomplished by applying the stereotypes of the OntoUML ontology-driven conceptual modeling language.As a result, we propose a new OntoVCM, an ontologically grounded model, based on the initial VCM, but with guaranteed interoperability among the data sources that employ it. Conclusions We propose and illustrate how the unpacking of the Viral Conceptual Model resolves several issues related to semantic interoperability, the importance of which is recognized by the “I” in FAIR principles. The research addresses conceptual uncertainty within the domain of SARS-CoV-2 data and knowledge.The method employed provides the basis for further analyses of complex models currently used in life science applications, but lacking ontological grounding, subsequently hindering the interoperability needed for scientists to ...
    Keywords Ontological analysis ; Conceptual modeling ; OntoUML ; COVID-19 ; SARS-CoV-2 ; Viral genome ; Computer applications to medicine. Medical informatics ; R858-859.7 ; Biology (General) ; QH301-705.5
    Language English
    Publishing date 2022-11-01T00:00:00Z
    Publisher BMC
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article ; Online: CoV2K model, a comprehensive representation of SARS-CoV-2 knowledge and data interplay

    Tommaso Alfonsi / Ruba Al Khalaf / Stefano Ceri / Anna Bernasconi

    Scientific Data, Vol 9, Iss 1, Pp 1-

    2022  Volume 12

    Abstract: Abstract Since the outbreak of the COVID-19 pandemic, many research organizations have studied the genome of the SARS-CoV-2 virus; a body of public resources have been published for monitoring its evolution. While we experience an unprecedented richness ... ...

    Abstract Abstract Since the outbreak of the COVID-19 pandemic, many research organizations have studied the genome of the SARS-CoV-2 virus; a body of public resources have been published for monitoring its evolution. While we experience an unprecedented richness of information in this domain, we also ascertained the presence of several information quality issues. We hereby propose CoV2K, an abstract model for explaining SARS-CoV-2-related concepts and interactions, focusing on viral mutations, their co-occurrence within variants, and their effects. CoV2K provides a clear and concise route map for understanding different connected types of information related to the virus; it thus drives a process of data and knowledge integration that aggregates information from several current resources, harmonizing their content and overcoming incompleteness and inconsistency issues. CoV2K is available for exploration as a graph that can be queried through a RESTful API addressing single entities or paths through their relationships. Practical use cases demonstrate its application to current knowledge inquiries.
    Keywords Science ; Q
    Language English
    Publishing date 2022-06-01T00:00:00Z
    Publisher Nature Portfolio
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: Data-driven analysis of amino acid change dynamics timely reveals SARS-CoV-2 variant emergence

    Anna Bernasconi / Lorenzo Mari / Renato Casagrandi / Stefano Ceri

    Scientific Reports, Vol 11, Iss 1, Pp 1-

    2021  Volume 10

    Abstract: Abstract Since its emergence in late 2019, the diffusion of SARS-CoV-2 is associated with the evolution of its viral genome. The co-occurrence of specific amino acid changes, collectively named ‘virus variant’, requires scrutiny (as variants may hugely ... ...

    Abstract Abstract Since its emergence in late 2019, the diffusion of SARS-CoV-2 is associated with the evolution of its viral genome. The co-occurrence of specific amino acid changes, collectively named ‘virus variant’, requires scrutiny (as variants may hugely impact the agent’s transmission, pathogenesis, or antigenicity); variant evolution is studied using phylogenetics. Yet, never has this problem been tackled by digging into data with ad hoc analysis techniques. Here we show that the emergence of variants can in fact be traced through data-driven methods, further capitalizing on the value of large collections of SARS-CoV-2 sequences. For all countries with sufficient data, we compute weekly counts of amino acid changes, unveil time-varying clusters of changes with similar—rapidly growing—dynamics, and then follow their evolution. Our method succeeds in timely associating clusters to variants of interest/concern, provided their change composition is well characterized. This allows us to detect variants’ emergence, rise, peak, and eventual decline under competitive pressure of another variant. Our early warning system, exclusively relying on deposited sequences, shows the power of big data in this context, and concurs to calling for the wide spreading of public SARS-CoV-2 genome sequencing for improved surveillance and control of the COVID-19 pandemic.
    Keywords Medicine ; R ; Science ; Q
    Language English
    Publishing date 2021-10-01T00:00:00Z
    Publisher Nature Portfolio
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Article ; Online: Empowering Virus Sequences Research through Conceptual Modeling

    Anna Bernasconi / Arif Cankoglu / Pietro Pinoli / Stefano Ceri

    Abstract: AbstractThe pandemic outbreak of the coronavirus disease has attracted attention towards the genetic mechanisms of viruses. We hereby present the Viral Conceptual Model (VCM), centered on the virus sequence and described from four perspectives: ... ...

    Abstract AbstractThe pandemic outbreak of the coronavirus disease has attracted attention towards the genetic mechanisms of viruses. We hereby present the Viral Conceptual Model (VCM), centered on the virus sequence and described from four perspectives: biological (virus type and hosts/sample), analytical (annotations and variants), organizational (sequencing project) and technical (experimental technology).VCM is inspired by GCM, our previously developed Genomic Conceptual Model, but it introduces many novel concepts, as viral sequences significantly differ from human genomes. When applied to SARS-CoV2 virus, complex conceptual queries upon VCM are able to replicate the search results of recent articles, hence demonstrating huge potential in supporting virology research.In addition to VCM, we also illustrate the data dictionary for patient’s phenotype used by the COVID-19 Host Genetic Initiative. Our effort is part of a broad vision: availability of conceptual models for both human genomics and viruses will provide important opportunities for research, especially if interconnected by the same human being, playing the role of virus host as well as provider of genomic and phenotype information.
    Keywords covid19
    Publisher biorxiv
    Document type Article ; Online
    DOI 10.1101/2020.04.29.067637
    Database COVID19

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  7. Article ; Online: OpenGDC

    Eleonora Cappelli / Fabio Cumbo / Anna Bernasconi / Arif Canakoglu / Stefano Ceri / Marco Masseroli / Emanuel Weitschek

    Applied Sciences, Vol 10, Iss 6367, p

    Unifying, Modeling, Integrating Cancer Genomic Data and Clinical Metadata

    2020  Volume 6367

    Abstract: Next Generation Sequencing technologies have produced a substantial increase of publicly available genomic data and related clinical/biospecimen information. New models and methods to easily access, integrate and search them effectively are needed. An ... ...

    Abstract Next Generation Sequencing technologies have produced a substantial increase of publicly available genomic data and related clinical/biospecimen information. New models and methods to easily access, integrate and search them effectively are needed. An effort was made by the Genomic Data Commons (GDC), which defined strict procedures for harmonizing genomic and clinical data of cancer, and created the GDC data portal with its application programming interface (API). In this work, we enhance GDC harmonization by applying a state of the art data model (called Genomic Data Model) made of two components: the genomic data, in Browser Extensible Data (BED) format, and the related metadata, in a tab-delimited key-value format. Furthermore, we extend the GDC genomic data with information extracted from other public genomic databases (e.g., GENCODE, HGNC and miRBase). For metadata, we implemented automatic procedures to extract and normalize them, recognizing and eliminating redundant ones, from both Clinical/Biospecimen Supplements and GDC Data Model, that are present on the two sources of GDC (i.e., data portal and API). We developed and released the OpenGDC software, which is able to extract, integrate, extend, and standardize genomic and clinical data of The Cancer Genome Atlas (TCGA) from the GDC. Additionally, we created a publicly accessible repository, containing such homogenized and enhanced TCGA data (resulting in about 1.3 TB). Our approach, implemented in the OpenGDC software, provides a step forward to the effective and efficient management of big genomic and clinical data of cancer. The strong usability of our data model and utility of our work is demonstrated through the application of the GenoMetric Query Language (GMQL) on the transformed TCGA data from the GDC, achieving promising results, facilitating information retrieval and knowledge discovery analyses.
    Keywords data modeling ; data integration ; next generation sequencing ; cancer ; knowledge extraction ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
    Subject code 310
    Language English
    Publishing date 2020-09-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Article ; Online: SARS-CoV-2 viremia and COVID-19 mortality

    Andrea Giacomelli / Elena Righini / Valeria Micheli / Pietro Pinoli / Anna Bernasconi / Alberto Rizzo / Letizia Oreni / Anna Lisa Ridolfo / Spinello Antinori / Stefano Ceri / Giuliano Rizzardini

    PLoS ONE, Vol 18, Iss 4, p e

    A prospective observational study.

    2023  Volume 0281052

    Abstract: Background SARS-CoV-2 viremia has been found to be a potential prognostic factor in patients hospitalized for COVID-19. Objective We aimed to assess the association between SARS-CoV-2 viremia and mortality in COVID-19 hospitalized patients during ... ...

    Abstract Background SARS-CoV-2 viremia has been found to be a potential prognostic factor in patients hospitalized for COVID-19. Objective We aimed to assess the association between SARS-CoV-2 viremia and mortality in COVID-19 hospitalized patients during different epidemic periods. Methods A prospective COVID-19 registry was queried to extract all COVID-19 patients with an available SARS-CoV-2 viremia performed at hospital admission between March 2020 and January 2022. SARS-CoV-2 viremia was assessed by means of GeneFinderTM COVID-19 Plus RealAmp Kit assay and SARS-CoV-2 ELITe MGB® Kit using <45 cycle threshold to define positivity. Uni and multivariable logistic regression model were built to assess the association between SARS-CoV-2 positive viremia and death. Results Four hundred and forty-five out of 2,822 COVID-19 patients had an available SARS-CoV-2 viremia, prevalently males (64.9%) with a median age of 65 years (IQR 55-75). Patients with a positive SARS-CoV-2 viremia (86/445; 19.3%) more frequently presented with a severe or critical disease (67.4% vs 57.1%) when compared to those with a negative SARS-CoV-2 viremia. Deceased subjects (88/445; 19.8%) were older [75 (IQR 68-82) vs 63 (IQR 54-72)] and showed more frequently a detectable SARS-CoV-2 viremia at admission (60.2% vs 22.7%) when compared to survivors. In univariable analysis a positive SARS-CoV-2 viremia was associated with a higher odd of death [OR 5.16 (95% CI 3.15-8.45)] which was confirmed in the multivariable analysis adjusted for age, biological sex and, disease severity [AOR 6.48 (95% CI 4.05-10.45)]. The association between positive SARS-CoV-2 viremia and death was consistent in the period 1 February 2021-31 January 2022 [AOR 5.86 (95% CI 3.43-10.16)] and in subgroup analysis according to disease severity: mild/moderate [AOR 6.45 (95% CI 2.84-15.17)] and severe/critical COVID-19 patients [AOR 6.98 (95% CI 3.68-13.66)]. Conclusions SARS-CoV-2 viremia resulted associated to COVID-19 mortality and should be considered in the initial assessment of ...
    Keywords Medicine ; R ; Science ; Q
    Subject code 610
    Language English
    Publishing date 2023-01-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Article ; Online: On a hierarchy of Booleanfunctions hard to compute in constant depth

    Anna Bernasconi

    Discrete Mathematics & Theoretical Computer Science, Vol 4, Iss

    2001  Volume 2

    Abstract: Any attempt to find connections between mathematical properties and complexity has a strong relevance to the field of Complexity Theory. This is due to the lack of mathematical techniques to prove lower bounds for general models of computation. This work ...

    Abstract Any attempt to find connections between mathematical properties and complexity has a strong relevance to the field of Complexity Theory. This is due to the lack of mathematical techniques to prove lower bounds for general models of computation. This work represents a step in this direction: we define a combinatorial property that makes Boolean functions `` hard '' to compute in constant depth and show how the harmonic analysis on the hypercube can be applied to derive new lower bounds on the size complexity of previously unclassified Boolean functions.
    Keywords Electronic computers. Computer science ; QA75.5-76.95 ; Instruments and machines ; QA71-90 ; Mathematics ; QA1-939 ; Science ; Q ; DOAJ:Computer Science ; DOAJ:Technology and Engineering ; DOAJ:Mathematics ; DOAJ:Mathematics and Statistics
    Language English
    Publishing date 2001-12-01T00:00:00Z
    Publisher Discrete Mathematics & Theoretical Computer Science
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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