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  1. Article: Missing Links Between Gene Function and Physiology in Genomics.

    Collado-Vides, Julio / Gaudet, Pascale / de Lorenzo, Víctor

    Frontiers in physiology

    2022  Volume 13, Page(s) 815874

    Abstract: Knowledge of biological organisms at the molecular level that has been gathered is now organized into databases, often within ontological frameworks. To enable computational comparisons of annotations across different genomes and organisms, controlled ... ...

    Abstract Knowledge of biological organisms at the molecular level that has been gathered is now organized into databases, often within ontological frameworks. To enable computational comparisons of annotations across different genomes and organisms, controlled vocabularies have been essential, as is the case in the functional annotation classifications used for bacteria, such as MultiFun and the more widely used Gene Ontology. The function of individual gene products as well as the processes in which collections of them participate constitute a wealth of classes that describe the biological role of gene products in a large number of organisms in the three kingdoms of life. In this contribution, we highlight from a qualitative perspective some limitations of these frameworks and discuss challenges that need to be addressed to bridge the gap between annotation as currently captured by ontologies and databases and our understanding of the basic principles in the organization and functioning of organisms; we illustrate these challenges with some examples in bacteria. We hope that raising awareness of these issues will encourage users of Gene Ontology and similar ontologies to be careful about data interpretation and lead to improved data representation.
    Language English
    Publishing date 2022-02-28
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2564217-0
    ISSN 1664-042X
    ISSN 1664-042X
    DOI 10.3389/fphys.2022.815874
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article: Kinases and Cancer.

    Cicenas, Jonas / Zalyte, Egle / Bairoch, Amos / Gaudet, Pascale

    Cancers

    2018  Volume 10, Issue 3

    Abstract: Protein kinases are a large family of enzymes catalyzing protein phosphorylation. The human genome contains 518 protein kinase genes, 478 of which belong to the classical protein kinase family and 40 are atypical protein kinases [ ... ]. ...

    Abstract Protein kinases are a large family of enzymes catalyzing protein phosphorylation. The human genome contains 518 protein kinase genes, 478 of which belong to the classical protein kinase family and 40 are atypical protein kinases [...].
    Language English
    Publishing date 2018-03-01
    Publishing country Switzerland
    Document type Editorial
    ZDB-ID 2527080-1
    ISSN 2072-6694
    ISSN 2072-6694
    DOI 10.3390/cancers10030063
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Gene Ontology: Pitfalls, Biases, and Remedies.

    Gaudet, Pascale / Dessimoz, Christophe

    Methods in molecular biology (Clifton, N.J.)

    2016  Volume 1446, Page(s) 189–205

    Abstract: The Gene Ontology (GO) is a formidable resource, but there are several considerations about it that are essential to understand the data and interpret it correctly. The GO is sufficiently simple that it can be used without deep understanding of its ... ...

    Abstract The Gene Ontology (GO) is a formidable resource, but there are several considerations about it that are essential to understand the data and interpret it correctly. The GO is sufficiently simple that it can be used without deep understanding of its structure or how it is developed, which is both a strength and a weakness. In this chapter, we discuss some common misinterpretations of the ontology and the annotations. A better understanding of the pitfalls and the biases in the GO should help users make the most of this very rich resource. We also review some of the misconceptions and misleading assumptions commonly made about GO, including the effect of data incompleteness, the importance of annotation qualifiers, and the transitivity or lack thereof associated with different ontology relations. We also discuss several biases that can confound aggregate analyses such as gene enrichment analyses. For each of these pitfalls and biases, we suggest remedies and best practices.
    MeSH term(s) Animals ; Data Mining/methods ; Databases, Genetic ; Gene Ontology ; Humans ; Molecular Sequence Annotation/methods ; Proteins/genetics ; Species Specificity
    Chemical Substances Proteins
    Language English
    Publishing date 2016-10-12
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
    ISSN 1940-6029
    ISSN (online) 1940-6029
    DOI 10.1007/978-1-4939-3743-1_14
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Best Practices in Manual Annotation with the Gene Ontology.

    Poux, Sylvain / Gaudet, Pascale

    Methods in molecular biology (Clifton, N.J.)

    2016  Volume 1446, Page(s) 41–54

    Abstract: The Gene Ontology (GO) is a framework designed to represent biological knowledge about gene products' biological roles and the cellular location in which they act. Biocuration is a complex process: the body of scientific literature is large and selection ...

    Abstract The Gene Ontology (GO) is a framework designed to represent biological knowledge about gene products' biological roles and the cellular location in which they act. Biocuration is a complex process: the body of scientific literature is large and selection of appropriate GO terms can be challenging. Both these issues are compounded by the fact that our understanding of biology is still incomplete; hence it is important to appreciate that GO is inherently an evolving model. In this chapter, we describe how biocurators create GO annotations from experimental findings from research articles. We describe the current best practices for high-quality literature curation and how GO curators succeed in modeling biology using a relatively simple framework. We also highlight a number of difficulties when translating experimental assays into GO annotations.
    MeSH term(s) Animals ; Computational Biology/methods ; Databases, Protein ; Gene Ontology ; Humans ; Molecular Sequence Annotation/methods ; Phenotype ; Proteins/genetics ; Proteins/metabolism
    Chemical Substances Proteins
    Language English
    Publishing date 2016-10-12
    Publishing country United States
    Document type Journal Article
    ISSN 1940-6029
    ISSN (online) 1940-6029
    DOI 10.1007/978-1-4939-3743-1_4
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Gene Ontology representation for transcription factor functions.

    Gaudet, Pascale / Logie, Colin / Lovering, Ruth C / Kuiper, Martin / Lægreid, Astrid / Thomas, Paul D

    Biochimica et biophysica acta. Gene regulatory mechanisms

    2021  Volume 1864, Issue 11-12, Page(s) 194752

    Abstract: Transcription plays a central role in defining the identity and functionalities of cells, as well as in their responses to changes in the cellular environment. The Gene Ontology (GO) provides a rigorously defined set of concepts that describe the ... ...

    Abstract Transcription plays a central role in defining the identity and functionalities of cells, as well as in their responses to changes in the cellular environment. The Gene Ontology (GO) provides a rigorously defined set of concepts that describe the functions of gene products. A GO annotation is a statement about the function of a particular gene product, represented as an association between a gene product and the biological concept a GO term defines. Critically, each GO annotation is based on traceable scientific evidence. Here, we describe the different GO terms that are associated with proteins involved in transcription and its regulation, focusing on the standard of evidence required to support these associations. This article is intended to help users of GO annotations understand how to interpret the annotations and can contribute to the consistency of GO annotations. We distinguish between three classes of activities involved in transcription or directly regulating it - general transcription factors, DNA-binding transcription factors, and transcription co-regulators.
    MeSH term(s) Computational Biology/methods ; Databases, Genetic/statistics & numerical data ; Gene Expression Regulation ; Gene Ontology/statistics & numerical data ; Molecular Sequence Annotation/statistics & numerical data ; Transcription Factors/classification
    Chemical Substances Transcription Factors
    Language English
    Publishing date 2021-08-28
    Publishing country Netherlands
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
    ZDB-ID 2918786-2
    ISSN 1876-4320 ; 1874-9399
    ISSN (online) 1876-4320
    ISSN 1874-9399
    DOI 10.1016/j.bbagrm.2021.194752
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Target discovery from protein databases: challenges for curation.

    Chichester, Christine / Gaudet, Pascale

    Drug discovery today. Technologies

    2015  Volume 14, Page(s) 11–16

    Abstract: Protein databases are a gold mine of potential new drug targets. The ready access to a complete overview of all aspects of protein biology provides the most benefit at the outset of drug discovery pipelines. Ideally, curation strategies used to move from ...

    Abstract Protein databases are a gold mine of potential new drug targets. The ready access to a complete overview of all aspects of protein biology provides the most benefit at the outset of drug discovery pipelines. Ideally, curation strategies used to move from the raw data to the validated knowledge should contain the checks and balances necessary for accuracy. The neXtProt human protein knowledgebase is used here as an example to give insight into these methods.
    MeSH term(s) Data Mining ; Databases, Protein ; Drug Discovery ; Humans ; Protein Conformation
    Language English
    Publishing date 2015-07
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't ; Review
    ISSN 1740-6749
    ISSN (online) 1740-6749
    DOI 10.1016/j.ddtec.2015.01.003
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Biocuration Virtual Issue 2012.

    Gaudet, Pascale / Mazumder, Raja

    Database : the journal of biological databases and curation

    2012  Volume 2012, Page(s) bas011

    MeSH term(s) Biomedical Research ; Database Management Systems ; Databases, Genetic ; Genomics
    Language English
    Publishing date 2012-03-20
    Publishing country England
    Document type Editorial
    ZDB-ID 2496706-3
    ISSN 1758-0463 ; 1758-0463
    ISSN (online) 1758-0463
    ISSN 1758-0463
    DOI 10.1093/database/bas011
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: The Feature-Viewer: a visualization tool for positional annotations on a sequence.

    Paladin, Lisanna / Schaeffer, Mathieu / Gaudet, Pascale / Zahn-Zabal, Monique / Michel, Pierre-André / Piovesan, Damiano / Tosatto, Silvio C E / Bairoch, Amos

    Bioinformatics (Oxford, England)

    2020  Volume 36, Issue 10, Page(s) 3244–3245

    Abstract: Summary: The Feature-Viewer is a lightweight library for the visualization of biological data mapped to a protein or nucleotide sequence. It is designed for ease of use while allowing for a full customization. The library is already used by several ... ...

    Abstract Summary: The Feature-Viewer is a lightweight library for the visualization of biological data mapped to a protein or nucleotide sequence. It is designed for ease of use while allowing for a full customization. The library is already used by several biological data resources and allows intuitive visual mapping of a full spectra of sequence features for different usages.
    Availability and implementation: The Feature-Viewer is open source, compatible with state-of-the-art development technologies and responsive, also for mobile viewing. Documentation and usage examples are available online.
    MeSH term(s) Computers ; Software
    Language English
    Publishing date 2020-01-22
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 1422668-6
    ISSN 1367-4811 ; 1367-4803
    ISSN (online) 1367-4811
    ISSN 1367-4803
    DOI 10.1093/bioinformatics/btaa055
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 2374: Show issues Location:
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  9. Article ; Online: Fibrinogen-Like Protein 2-Associated Transcriptional and Histopathological Features of Immunological Preeclampsia.

    Robineau-Charette, Pascale / Grynspan, David / Benton, Samantha J / Gaudet, Jeremiah / Cox, Brian J / Vanderhyden, Barbara C / Bainbridge, Shannon A

    Hypertension (Dallas, Tex. : 1979)

    2020  Volume 76, Issue 3, Page(s) 910–921

    Abstract: Preeclampsia is a multifactorial hypertensive disorder of pregnancy, with variable presentation in both maternal and fetal factors, such that no treatment or marker is currently universal to all cases. Here, we demonstrate that the prothrombinase and ... ...

    Abstract Preeclampsia is a multifactorial hypertensive disorder of pregnancy, with variable presentation in both maternal and fetal factors, such that no treatment or marker is currently universal to all cases. Here, we demonstrate that the prothrombinase and immunomodulatory secreted factor FGL-2 (fibrinogen-like protein 2) is differentially expressed across previously characterized gene expression clusters containing clinically relevant disease subtypes.
    MeSH term(s) Biomarkers/metabolism ; Endoglin/metabolism ; Female ; Fibrinogen/metabolism ; Gene Expression Profiling ; Gene Expression Regulation/immunology ; Humans ; Immunity ; Interferon-gamma/immunology ; Phylogeny ; Placenta/immunology ; Placenta/metabolism ; Placenta Diseases/immunology ; Pre-Eclampsia/diagnosis ; Pre-Eclampsia/immunology ; Pregnancy ; Tumor Necrosis Factor-alpha/immunology ; Vascular Endothelial Growth Factor Receptor-1/metabolism
    Chemical Substances Biomarkers ; Endoglin ; FGL2 protein, human ; Tumor Necrosis Factor-alpha ; Interferon-gamma (82115-62-6) ; Fibrinogen (9001-32-5) ; Vascular Endothelial Growth Factor Receptor-1 (EC 2.7.10.1)
    Language English
    Publishing date 2020-07-27
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 423736-5
    ISSN 1524-4563 ; 0194-911X ; 0362-4323
    ISSN (online) 1524-4563
    ISSN 0194-911X ; 0362-4323
    DOI 10.1161/HYPERTENSIONAHA.120.14807
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 1488: Show issues Location:
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  10. Article ; Online: Primer on the Gene Ontology.

    Gaudet, Pascale / Škunca, Nives / Hu, James C / Dessimoz, Christophe

    Methods in molecular biology (Clifton, N.J.)

    2016  Volume 1446, Page(s) 25–37

    Abstract: The Gene Ontology (GO) project is the largest resource for cataloguing gene function. The combination of solid conceptual underpinnings and a practical set of features have made the GO a widely adopted resource in the research community and an essential ... ...

    Abstract The Gene Ontology (GO) project is the largest resource for cataloguing gene function. The combination of solid conceptual underpinnings and a practical set of features have made the GO a widely adopted resource in the research community and an essential resource for data analysis. In this chapter, we provide a concise primer for all users of the GO. We briefly introduce the structure of the ontology and explain how to interpret annotations associated with the GO.
    MeSH term(s) Animals ; Computational Biology/methods ; DNA/genetics ; Databases, Genetic ; Gene Ontology ; Humans ; Internet ; Proteins/genetics ; RNA/genetics
    Chemical Substances Proteins ; RNA (63231-63-0) ; DNA (9007-49-2)
    Language English
    Publishing date 2016-10-31
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, N.I.H., Extramural
    ISSN 1940-6029
    ISSN (online) 1940-6029
    DOI 10.1007/978-1-4939-3743-1_3
    Database MEDical Literature Analysis and Retrieval System OnLINE

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