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  1. Article ; Online: BioKC: a collaborative platform for curation and annotation of molecular interactions.

    Vega, Carlos / Ostaszewski, Marek / Grouès, Valentin / Schneider, Reinhard / Satagopam, Venkata

    Database : the journal of biological databases and curation

    2024  Volume 2024

    Abstract: Curation of biomedical knowledge into systems biology diagrammatic or computational models is essential for studying complex biological processes. However, systems-level curation is a laborious manual process, especially when facing ever-increasing ... ...

    Abstract Curation of biomedical knowledge into systems biology diagrammatic or computational models is essential for studying complex biological processes. However, systems-level curation is a laborious manual process, especially when facing ever-increasing growth of domain literature. New findings demonstrating elaborate relationships between multiple molecules, pathways and cells have to be represented in a format suitable for systems biology applications. Importantly, curation should capture the complexity of molecular interactions in such a format together with annotations of the involved elements and support stable identifiers and versioning. This challenge calls for novel collaborative tools and platforms allowing to improve the quality and the output of the curation process. In particular, community-based curation, an important source of curated knowledge, requires support in role management, reviewing features and versioning. Here, we present Biological Knowledge Curation (BioKC), a web-based collaborative platform for the curation and annotation of biomedical knowledge following the standard data model from Systems Biology Markup Language (SBML). BioKC offers a graphical user interface for curation of complex molecular interactions and their annotation with stable identifiers and supporting sentences. With the support of collaborative curation and review, it allows to construct building blocks for systems biology diagrams and computational models. These building blocks can be published under stable identifiers and versioned and used as annotations, supporting knowledge building for modelling activities.
    MeSH term(s) Software ; Systems Biology ; Data Curation
    Language English
    Publishing date 2024-03-27
    Publishing country England
    Document type Journal Article
    ZDB-ID 2496706-3
    ISSN 1758-0463 ; 1758-0463
    ISSN (online) 1758-0463
    ISSN 1758-0463
    DOI 10.1093/database/baae013
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Exploration and comparison of molecular mechanisms across diseases using MINERVA Net.

    Gawron, Piotr / Smula, Ewa / Schneider, Reinhard / Ostaszewski, Marek

    Protein science : a publication of the Protein Society

    2023  Volume 32, Issue 2, Page(s) e4565

    Abstract: Protein function is often interpreted using molecular interaction diagrams, encoding roles a given protein plays in various molecular mechanisms. Information about disease-related mechanisms can be inferred from disease maps, knowledge repositories ... ...

    Abstract Protein function is often interpreted using molecular interaction diagrams, encoding roles a given protein plays in various molecular mechanisms. Information about disease-related mechanisms can be inferred from disease maps, knowledge repositories containing manually constructed systems biology diagrams. Disease maps hosted on the Molecular Interaction Network VisuAlization (MINERVA) Platform are individually accessible through a REST API interface of each instance, making it challenging to systematically explore their contents. To address this challenge, we introduce the MINERVA Net web service, a repository of open-access disease maps allowing users to publicly share minimal information about their maps. The MINERVA Net repository provides REST API endpoints of particular disease maps, which then can be individually queried for content. In this article, we describe the concept of MINERVA Net and illustrate its use by comparing proteins and their interactions in three different disease maps.
    MeSH term(s) Systems Biology ; Proteins/genetics ; Software
    Chemical Substances Proteins
    Language English
    Publishing date 2023-01-16
    Publishing country United States
    Document type Journal Article
    ZDB-ID 1106283-6
    ISSN 1469-896X ; 0961-8368
    ISSN (online) 1469-896X
    ISSN 0961-8368
    DOI 10.1002/pro.4565
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Applications of Boolean modeling to study the dynamics of a complex disease and therapeutics responses.

    Hemedan, Ahmed Abdelmonem / Schneider, Reinhard / Ostaszewski, Marek

    Frontiers in bioinformatics

    2023  Volume 3, Page(s) 1189723

    Abstract: Computational modeling has emerged as a critical tool in investigating the complex molecular processes involved in biological systems and diseases. In this study, we apply Boolean modeling to uncover the molecular mechanisms underlying Parkinson's ... ...

    Abstract Computational modeling has emerged as a critical tool in investigating the complex molecular processes involved in biological systems and diseases. In this study, we apply Boolean modeling to uncover the molecular mechanisms underlying Parkinson's disease (PD), one of the most prevalent neurodegenerative disorders. Our approach is based on the PD-map, a comprehensive molecular interaction diagram that captures the key mechanisms involved in the initiation and progression of PD. Using Boolean modeling, we aim to gain a deeper understanding of the disease dynamics, identify potential drug targets, and simulate the response to treatments. Our analysis demonstrates the effectiveness of this approach in uncovering the intricacies of PD. Our results confirm existing knowledge about the disease and provide valuable insights into the underlying mechanisms, ultimately suggesting potential targets for therapeutic intervention. Moreover, our approach allows us to parametrize the models based on omics data for further disease stratification. Our study highlights the value of computational modeling in advancing our understanding of complex biological systems and diseases, emphasizing the importance of continued research in this field. Furthermore, our findings have potential implications for the development of novel therapies for PD, which is a pressing public health concern. Overall, this study represents a significant step forward in the application of computational modeling to the investigation of neurodegenerative diseases, and underscores the power of interdisciplinary approaches in tackling challenging biomedical problems.
    Language English
    Publishing date 2023-06-01
    Publishing country Switzerland
    Document type Journal Article
    ISSN 2673-7647
    ISSN (online) 2673-7647
    DOI 10.3389/fbinf.2023.1189723
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Applications of Boolean modeling to study the dynamics of a complex disease and therapeutics responses

    Ahmed Abdelmonem Hemedan / Reinhard Schneider / Marek Ostaszewski

    Frontiers in Bioinformatics, Vol

    2023  Volume 3

    Abstract: Computational modeling has emerged as a critical tool in investigating the complex molecular processes involved in biological systems and diseases. In this study, we apply Boolean modeling to uncover the molecular mechanisms underlying Parkinson’s ... ...

    Abstract Computational modeling has emerged as a critical tool in investigating the complex molecular processes involved in biological systems and diseases. In this study, we apply Boolean modeling to uncover the molecular mechanisms underlying Parkinson’s disease (PD), one of the most prevalent neurodegenerative disorders. Our approach is based on the PD-map, a comprehensive molecular interaction diagram that captures the key mechanisms involved in the initiation and progression of PD. Using Boolean modeling, we aim to gain a deeper understanding of the disease dynamics, identify potential drug targets, and simulate the response to treatments. Our analysis demonstrates the effectiveness of this approach in uncovering the intricacies of PD. Our results confirm existing knowledge about the disease and provide valuable insights into the underlying mechanisms, ultimately suggesting potential targets for therapeutic intervention. Moreover, our approach allows us to parametrize the models based on omics data for further disease stratification. Our study highlights the value of computational modeling in advancing our understanding of complex biological systems and diseases, emphasizing the importance of continued research in this field. Furthermore, our findings have potential implications for the development of novel therapies for PD, which is a pressing public health concern. Overall, this study represents a significant step forward in the application of computational modeling to the investigation of neurodegenerative diseases, and underscores the power of interdisciplinary approaches in tackling challenging biomedical problems.
    Keywords Boolean modelling ; molecular mechanisms ; systems biology ; drug target ; Parkinsion’s disease ; Computer applications to medicine. Medical informatics ; R858-859.7
    Subject code 006
    Language English
    Publishing date 2023-06-01T00:00:00Z
    Publisher Frontiers Media S.A.
    Document type Article ; Online
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  5. Article: Boolean modelling as a logic-based dynamic approach in systems medicine.

    Hemedan, Ahmed Abdelmonem / Niarakis, Anna / Schneider, Reinhard / Ostaszewski, Marek

    Computational and structural biotechnology journal

    2022  Volume 20, Page(s) 3161–3172

    Abstract: Molecular mechanisms of health and disease are often represented as systems biology diagrams, and the coverage of such representation constantly increases. These static diagrams can be transformed into dynamic models, allowing ... ...

    Abstract Molecular mechanisms of health and disease are often represented as systems biology diagrams, and the coverage of such representation constantly increases. These static diagrams can be transformed into dynamic models, allowing for
    Language English
    Publishing date 2022-06-17
    Publishing country Netherlands
    Document type Journal Article ; Review
    ZDB-ID 2694435-2
    ISSN 2001-0370
    ISSN 2001-0370
    DOI 10.1016/j.csbj.2022.06.035
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  6. Article ; Online: Boolean modelling as a logic-based dynamic approach in systems medicine

    Ahmed Abdelmonem Hemedan / Anna Niarakis / Reinhard Schneider / Marek Ostaszewski

    Computational and Structural Biotechnology Journal, Vol 20, Iss , Pp 3161-

    2022  Volume 3172

    Abstract: Molecular mechanisms of health and disease are often represented as systems biology diagrams, and the coverage of such representation constantly increases. These static diagrams can be transformed into dynamic models, allowing for in silico simulations ... ...

    Abstract Molecular mechanisms of health and disease are often represented as systems biology diagrams, and the coverage of such representation constantly increases. These static diagrams can be transformed into dynamic models, allowing for in silico simulations and predictions. Boolean modelling is an approach based on an abstract representation of the system. It emphasises the qualitative modelling of biological systems in which each biomolecule can take two possible values: zero for absent or inactive, one for present or active. Because of this approximation, Boolean modelling is applicable to large diagrams, allowing to capture their dynamic properties. We review Boolean models of disease mechanisms and compare a range of methods and tools used for analysis processes. We explain the methodology of Boolean analysis focusing on its application in disease modelling. Finally, we discuss its practical application in analysing signal transduction and gene regulatory pathways in health and disease.
    Keywords Logical modelling ; Boolean networks ; Modelling formats ; Systems Biology standards ; Biotechnology ; TP248.13-248.65
    Subject code 530
    Language English
    Publishing date 2022-01-01T00:00:00Z
    Publisher Elsevier
    Document type Article ; Online
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  7. Article ; Online: Closing the gap between formats for storing layout information in systems biology.

    Hoksza, David / Gawron, Piotr / Ostaszewski, Marek / Hasenauer, Jan / Schneider, Reinhard

    Briefings in bioinformatics

    2020  Volume 22, Issue 1, Page(s) 608

    Language English
    Publishing date 2020-02-20
    Publishing country England
    Document type Journal Article ; Published Erratum
    ZDB-ID 2068142-2
    ISSN 1477-4054 ; 1467-5463
    ISSN (online) 1477-4054
    ISSN 1467-5463
    DOI 10.1093/bib/bbaa030
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: SnapShot: The Expobiome Map.

    Aho, Velma T E / Ostaszewski, Marek / Martin-Gallausiaux, Camille / Laczny, Cédric C / Schneider, Jochen G / Wilmes, Paul

    Cell host & microbe

    2022  Volume 30, Issue 9, Page(s) 1340–1340.e1

    Abstract: The human gut microbiome is intricately connected to health and disease. Microbiome-derived molecules are implicated in many chronic diseases involving inflammation. Herein, we summarize the diverse complex of such immunogenic molecules, including ... ...

    Abstract The human gut microbiome is intricately connected to health and disease. Microbiome-derived molecules are implicated in many chronic diseases involving inflammation. Herein, we summarize the diverse complex of such immunogenic molecules, including nucleic acids, (poly)peptides, structural molecules, and metabolites. The interactions between this "expobiome" and human immune pathways are specifically illustrated in the context of chronic diseases. To view this SnapShot, open or download the PDF.
    MeSH term(s) Gastrointestinal Microbiome ; Humans ; Inflammation ; Microbiota
    Language English
    Publishing date 2022-08-27
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2278004-X
    ISSN 1934-6069 ; 1931-3128
    ISSN (online) 1934-6069
    ISSN 1931-3128
    DOI 10.1016/j.chom.2022.08.015
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: The gut microbiome molecular complex in human health and disease.

    Wilmes, Paul / Martin-Gallausiaux, Camille / Ostaszewski, Marek / Aho, Velma T E / Novikova, Polina V / Laczny, Cédric C / Schneider, Jochen G

    Cell host & microbe

    2022  Volume 30, Issue 9, Page(s) 1201–1206

    Abstract: The human gut microbiome produces a functional complex of biomolecules, including nucleic acids, (poly)peptides, structural molecules, and metabolites. This impacts human physiology in multiple ways, especially by triggering inflammatory pathways in ... ...

    Abstract The human gut microbiome produces a functional complex of biomolecules, including nucleic acids, (poly)peptides, structural molecules, and metabolites. This impacts human physiology in multiple ways, especially by triggering inflammatory pathways in disease. At present, much remains to be learned about the identity of key effectors and their causal roles.
    MeSH term(s) Gastrointestinal Microbiome ; Humans ; Microbiota/physiology ; Nucleic Acids
    Chemical Substances Nucleic Acids
    Language English
    Publishing date 2022-09-08
    Publishing country United States
    Document type Journal Article ; Comment
    ZDB-ID 2278004-X
    ISSN 1934-6069 ; 1931-3128
    ISSN (online) 1934-6069
    ISSN 1931-3128
    DOI 10.1016/j.chom.2022.08.016
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Machine Learning to Support the Presentation of Complex Pathway Graphs.

    Nielsen, Sune S / Ostaszewski, Marek / McGee, Fintan / Hoksza, David / Zorzan, Simone

    IEEE/ACM transactions on computational biology and bioinformatics

    2021  Volume 18, Issue 3, Page(s) 1130–1141

    Abstract: Visualization of biological mechanisms by means of pathway graphs is necessary to better understand the often complex underlying system. Manual layout of such pathways or maps of knowledge is a difficult and time consuming process. Node duplication is a ... ...

    Abstract Visualization of biological mechanisms by means of pathway graphs is necessary to better understand the often complex underlying system. Manual layout of such pathways or maps of knowledge is a difficult and time consuming process. Node duplication is a technique that makes layouts with improved readability possible by reducing edge crossings and shortening edge lengths in drawn diagrams. In this article, we propose an approach using Machine Learning (ML) to facilitate parts of this task by training a Support Vector Machine (SVM) with actions taken during manual biocuration. Our training input is a series of incremental snapshots of a diagram describing mechanisms of a disease, progressively curated by a human expert employing node duplication in the process. As a test of the trained SVM models, they are applied to a single large instance and 25 medium-sized instances of hand-curated biological pathways. Finally, in a user validation study, we compare the model predictions to the outcome of a node duplication questionnaire answered by users of biological pathways with varying experience. We successfully predicted nodes for duplication and emulated human choices, demonstrating that our approach can effectively learn human-like node duplication preferences to support curation of pathway diagrams in various contexts.
    MeSH term(s) Computational Biology/methods ; Data Display ; Humans ; Machine Learning ; Models, Biological ; Signal Transduction ; Support Vector Machine
    Language English
    Publishing date 2021-06-03
    Publishing country United States
    Document type Journal Article
    ISSN 1557-9964
    ISSN (online) 1557-9964
    DOI 10.1109/TCBB.2019.2938501
    Database MEDical Literature Analysis and Retrieval System OnLINE

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