The Experts below are selected from a list of 406986 Experts worldwide ranked by ideXlab platform
Sandra Orchard - One of the best experts on this subject based on the ideXlab platform.
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The Minimum Information about a Molecular Interaction Causal Statement (MI2CAST).
Bioinformatics (Oxford England), 2020Co-Authors: Vasundra Touré, Sandra Orchard, Steven Vercruysse, Marcio Luis Acencio, Glyn Bradley, Cristina Casals-casas, Claudine Chaouiya, Noemi Del-toro, Ruth C. Lovering, Åsmund FlobakAbstract:A large variety of Molecular Interactions occurs between bioMolecular components in cells. When a Molecular Interaction results in a regulatory effect, exerted by one component onto a downstream component, a so-called 'causal Interaction' takes place. Causal Interactions constitute the building blocks in our understanding of larger regulatory networks in cells. These causal Interactions and the biological processes they enable (e.g., gene regulation) need to be described with a careful appreciation of the underlying Molecular reactions. A proper description of this information enables archiving, sharing, and reuse by humans and for automated computational processing. Various representations of causal relationships between biological components are currently used in a variety of resources. Here, we propose a checklist that accommodates current representations, called the Minimum Information about a Molecular Interaction CAusal STatement (MI2CAST). This checklist defines both the required core information, as well as a comprehensive set of other contextual details valuable to the end user and relevant for reusing and reproducing causal Molecular Interaction information. The MI2CAST checklist can be used as reporting guidelines when annotating and curating causal statements, while fostering uniformity and interoperability of the data across resources. The checklist together with examples is accessible at https://github.com/MI2CAST/MI2CAST. Supplementary data are available at Bioinformatics online. © The Author(s) 2020. Published by Oxford University Press.
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The Minimum Information about a Molecular Interaction Causal Statement (MI2CAST)
2020Co-Authors: Vasundra Touré, Sandra Orchard, Steven Vercruysse, Marcio Luis Acencio, Ruth Lovering, Glyn Bradley, Cristina Casals-casas, Claudine Chaouiya, Noemi Del-toro, Åsmund FlobakAbstract:A large variety of Molecular Interactions occurs between bioMolecular components in cells. When one or a cascade of Molecular Interactions results in a regulatory effect, by one component onto a downstream component, a so-called ‘causal Interaction’ takes place. Causal Interactions constitute the building blocks in our understanding of larger regulatory networks in cells. These causal Interactions and the biological processes they enable (e.g., gene regulation) need to be described with a careful appreciation of Molecular Interactions that occur between entities. A proper description of this information enables archiving, sharing, and reuse by humans and for computational science. Various representations of causal relationships between biological components are currently used in a variety of resources. Here, we propose a checklist that accommodates current representations, and call it the Minimum Information about a Molecular Interaction CAusal STatement (MI2CAST). This checklist defines both the required core information, as well as a comprehensive set of other contextual details valuable to the end user and relevant for reusing and reproducing causal Molecular Interaction information. The MI2CAST checklist can be used as reporting guidelines when annotating and curating causal statements, while assuring uniformity and interoperability of the data across resources.
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The MIntAct Project and Molecular Interaction Databases.
Methods in molecular biology (Clifton N.J.), 2016Co-Authors: Luana Licata, Sandra OrchardAbstract:Molecular Interaction databases collect, organize, and enable the analysis of the increasing amounts of Molecular Interaction data being produced and published as we move towards a more complete understanding of the interactomes of key model organisms. The organization of these data in a structured format supports analyses such as the modeling of pairwise relationships between interactors into Interaction networks and is a powerful tool for understanding the complex Molecular machinery of the cell. This chapter gives an overview of the principal Molecular Interaction databases, in particular the IMEx databases, and their curation policies, use of standardized data formats and quality control rules. Special attention is given to the MIntAct project, in which IntAct and MINT joined forces to create a single resource to improve curation and software development efforts. This is exemplified as a model for the future of Molecular Interaction data collation and dissemination.
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the mintact project intact as a common curation platform for 11 Molecular Interaction databases
Nucleic Acids Research, 2014Co-Authors: Sandra Orchard, Lionel Breuza, B. Aranda, Carol Chen, Leonardo Briganti, Mais G Ammari, Fiona Broackescarter, Nancy H Campbell, Gayatri Chavali, Noemi DeltoroAbstract:IntAct (freely available at http://www.ebi.ac.uk/intact) is an open-source, open data Molecular Interaction database populated by data either curated from the literature or from direct data depositions. IntAct has developed a sophisticated web-based curation tool, capable of supporting both IMEx- and MIMIx-level curation. This tool is now utilized by multiple additional curation teams, all of whom annotate data directly into the IntAct database. Members of the IntAct team supply appropriate levels of training, perform quality control on entries and take responsibility for long-term data maintenance. Recently, the MINT and IntAct databases decided to merge their separate efforts to make optimal use of limited developer resources and maximize the curation output. All data manually curated by the MINT curators have been moved into the IntAct database at EMBL-EBI and are merged with the existing IntAct dataset. Both IntAct and MINT are active contributors to the IMEx consortium (http://www.imexconsortium.org).
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Molecular Interaction databases.
Proteomics, 2012Co-Authors: Sandra OrchardAbstract:Molecular Interaction databases are playing an ever more important role in our understanding of the biology of the cell. An increasing number of resources exist to provide these data and many of these have adopted the controlled vocabularies and agreed-upon standardised data formats produced by the Molecular Interaction workgroup of the Human Proteome Organization Proteomics Standards Initiative (HUPO PSI-MI). Use of these standards allows each resource to establish PSI Common QUery InterfaCe (PSICQUIC) service, making data from multiple resources available to the user in response to a single query. This cooperation between databases has been taken a stage further, with the establishment of the International Molecular Exchange (IMEx) consortium which aims to maximise the curation power of numerous data resources, and provide the user with a non-redundant, consistently annotated set of Interaction data.
Manu Harju - One of the best experts on this subject based on the ideXlab platform.
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Reconstruction and Validation of RefRec: A Global Model for the Yeast Molecular Interaction Network
PloS one, 2010Co-Authors: Tommi Aho, Henrikki Almusa, Jukka Matilainen, Antti Larjo, Pekka Ruusuvuori, Kaisa-leena Aho, Thomas Wilhelm, Harri Lähdesmäki, Andreas Beyer, Manu HarjuAbstract:Molecular Interaction networks establish all cell biological processes. The networks are under intensive research that is facilitated by new high-throughput measurement techniques for the detection, quantification, and characterization of molecules and their physical Interactions. For the common model organism yeast Saccharomyces cerevisiae, public databases store a significant part of the accumulated information and, on the way to better understanding of the cellular processes, there is a need to integrate this information into a consistent reconstruction of the Molecular Interaction network. This work presents and validates RefRec, the most comprehensive Molecular Interaction network reconstruction currently available for yeast. The reconstruction integrates protein synthesis pathways, a metabolic network, and a protein-protein Interaction network from major biological databases. The core of the reconstruction is based on a reference object approach in which genes, transcripts, and proteins are identified using their primary sequences. This enables their unambiguous identification and non-redundant integration. The obtained total number of different Molecular species and their connecting Interactions is ∼67,000. In order to demonstrate the capacity of RefRec for functional predictions, it was used for simulating the gene knockout damage propagation in the Molecular Interaction network in ∼590,000 experimentally validated mutant strains. Based on the simulation results, a statistical classifier was subsequently able to correctly predict the viability of most of the strains. The results also showed that the usage of different types of Molecular species in the reconstruction is important for accurate phenotype prediction. In general, the findings demonstrate the benefits of global reconstructions of Molecular Interaction networks. With all the Molecular species and their physical Interactions explicitly modeled, our reconstruction is able to serve as a valuable resource in additional analyses involving objects from multiple Molecular -omes. For that purpose, RefRec is freely available in the Systems Biology Markup Language format.
Kurt W. Kohn - One of the best experts on this subject based on the ideXlab platform.
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Chk2 Molecular Interaction Map and Rationale for Chk2 Inhibitors
Clinical cancer research : an official journal of the American Association for Cancer Research, 2006Co-Authors: Yves Pommier, John N. Weinstein, Mirit I. Aladjem, Kurt W. KohnAbstract:To organize the rapidly accumulating information on bioregulatory networks related to the histone gamma-H2AX-ATM-Chk2-p53-Mdm2 pathways in concise and unambiguous diagrams, we used the Molecular Interaction map notation (http://discover.nci.nih.gov/min). Molecular Interaction maps are particularly useful for networks that include protein-protein binding and posttranslational modifications (e.g., phosphorylation). Both are important for nearly all of the proteins involved in DNA double-strand break signaling. Visualizing the regulatory circuits underlying cellular signaling may help identify key regulatory reactions and defects that can serve as targets for anticancer drugs.
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Molecular Interaction maps of bioregulatory networks a general rubric for systems biology
Molecular Biology of the Cell, 2005Co-Authors: Kurt W. Kohn, Mirit I. Aladjem, John N. Weinstein, Yves PommierAbstract:A standard for bioregulatory network diagrams is urgently needed in the same way that circuit diagrams are needed in electronics. Several graphical notations have been proposed, but none has become standard. We have prepared many detailed bioregulatory network diagrams using the Molecular Interaction map (MIM) notation, and we now feel confident that it is suitable as a standard. Here, we describe the MIM notation formally and discuss its merits relative to alternative proposals. We show by simple examples how to denote all of the Molecular Interactions commonly found in bioregulatory networks. There are two forms of MIM diagrams. "Heuristic" MIMs present the repertoire of Interactions possible for molecules that are colocalized in time and place. "Explicit" MIMs define particular models (derived from heuristic MIMs) for computer simulation. We show also how pathways or processes can be highlighted on a canonical heuristic MIM. Drawing a MIM diagram, adhering to the rules of notation, imposes a logical discipline that sharpens one's understanding of the structure and function of a network.
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apoptosis defects and chemotherapy resistance Molecular Interaction maps and networks
Oncogene, 2004Co-Authors: Yves Pommier, Olivier Sordet, Smitha Antony, Richard L Hayward, Kurt W. KohnAbstract:Intrinsic (innate) and acquired (adaptive) resistance to chemotherapy critically limits the outcome of cancer treatments. For many years, it was assumed that the Interaction of a drug with its Molecular target would yield a lethal lesion, and that determinants of intrinsic drug resistance should therefore be sought either at the target level (quantitative changes or/and mutations) or upstream of this Interaction, in drug metabolism or drug transport mechanisms. It is now apparent that independent of the factors above, cellular responses to a Molecular lesion can determine the outcome of therapy. This review will focus on programmed cell death (apoptosis) and on survival pathways (Bcl-2, Apaf-1, AKT, NF-kappaB) involved in multidrug resistance. We will present our Molecular Interaction mapping conventions to summarize the AKT and IkappaB/NF-kappaB networks. They complement the p53, Chk2 and c-Abl maps published recently. We will also introduce the 'permissive apoptosis-resistance' model for the selection of multidrug-resistant cells.
Yves Pommier - One of the best experts on this subject based on the ideXlab platform.
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Chk2 Molecular Interaction Map and Rationale for Chk2 Inhibitors
Clinical cancer research : an official journal of the American Association for Cancer Research, 2006Co-Authors: Yves Pommier, John N. Weinstein, Mirit I. Aladjem, Kurt W. KohnAbstract:To organize the rapidly accumulating information on bioregulatory networks related to the histone gamma-H2AX-ATM-Chk2-p53-Mdm2 pathways in concise and unambiguous diagrams, we used the Molecular Interaction map notation (http://discover.nci.nih.gov/min). Molecular Interaction maps are particularly useful for networks that include protein-protein binding and posttranslational modifications (e.g., phosphorylation). Both are important for nearly all of the proteins involved in DNA double-strand break signaling. Visualizing the regulatory circuits underlying cellular signaling may help identify key regulatory reactions and defects that can serve as targets for anticancer drugs.
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Molecular Interaction maps of bioregulatory networks a general rubric for systems biology
Molecular Biology of the Cell, 2005Co-Authors: Kurt W. Kohn, Mirit I. Aladjem, John N. Weinstein, Yves PommierAbstract:A standard for bioregulatory network diagrams is urgently needed in the same way that circuit diagrams are needed in electronics. Several graphical notations have been proposed, but none has become standard. We have prepared many detailed bioregulatory network diagrams using the Molecular Interaction map (MIM) notation, and we now feel confident that it is suitable as a standard. Here, we describe the MIM notation formally and discuss its merits relative to alternative proposals. We show by simple examples how to denote all of the Molecular Interactions commonly found in bioregulatory networks. There are two forms of MIM diagrams. "Heuristic" MIMs present the repertoire of Interactions possible for molecules that are colocalized in time and place. "Explicit" MIMs define particular models (derived from heuristic MIMs) for computer simulation. We show also how pathways or processes can be highlighted on a canonical heuristic MIM. Drawing a MIM diagram, adhering to the rules of notation, imposes a logical discipline that sharpens one's understanding of the structure and function of a network.
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apoptosis defects and chemotherapy resistance Molecular Interaction maps and networks
Oncogene, 2004Co-Authors: Yves Pommier, Olivier Sordet, Smitha Antony, Richard L Hayward, Kurt W. KohnAbstract:Intrinsic (innate) and acquired (adaptive) resistance to chemotherapy critically limits the outcome of cancer treatments. For many years, it was assumed that the Interaction of a drug with its Molecular target would yield a lethal lesion, and that determinants of intrinsic drug resistance should therefore be sought either at the target level (quantitative changes or/and mutations) or upstream of this Interaction, in drug metabolism or drug transport mechanisms. It is now apparent that independent of the factors above, cellular responses to a Molecular lesion can determine the outcome of therapy. This review will focus on programmed cell death (apoptosis) and on survival pathways (Bcl-2, Apaf-1, AKT, NF-kappaB) involved in multidrug resistance. We will present our Molecular Interaction mapping conventions to summarize the AKT and IkappaB/NF-kappaB networks. They complement the p53, Chk2 and c-Abl maps published recently. We will also introduce the 'permissive apoptosis-resistance' model for the selection of multidrug-resistant cells.
Luana Licata - One of the best experts on this subject based on the ideXlab platform.
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The MIntAct Project and Molecular Interaction Databases.
Methods in molecular biology (Clifton N.J.), 2016Co-Authors: Luana Licata, Sandra OrchardAbstract:Molecular Interaction databases collect, organize, and enable the analysis of the increasing amounts of Molecular Interaction data being produced and published as we move towards a more complete understanding of the interactomes of key model organisms. The organization of these data in a structured format supports analyses such as the modeling of pairwise relationships between interactors into Interaction networks and is a powerful tool for understanding the complex Molecular machinery of the cell. This chapter gives an overview of the principal Molecular Interaction databases, in particular the IMEx databases, and their curation policies, use of standardized data formats and quality control rules. Special attention is given to the MIntAct project, in which IntAct and MINT joined forces to create a single resource to improve curation and software development efforts. This is exemplified as a model for the future of Molecular Interaction data collation and dissemination.
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MINT, the Molecular Interaction database: 2012 update
Nucleic Acids Research, 2011Co-Authors: Luana Licata, Leonardo Briganti, Daniele Peluso, Livia Perfetto, Marta Iannuccelli, Eugenia Galeota, Francesca Sacco, A. Palma, Aurelio Pio Nardozza, Elena SantonicoAbstract:The Molecular Interaction Database (MINT, http://mint.bio.uniroma2.it/mint/) is a public repository for protein-protein Interactions (PPI) reported in peer-reviewed journals. The database grows steadily over the years and at September 2011 contains approximately 235,000 binary Interactions captured from over 4750 publications. The web interface allows the users to search, visualize and download Interactions data. MINT is one of the members of the International Molecular Exchange consortium (IMEx) and adopts the Molecular Interaction Ontology of the Proteomics Standard Initiative (PSI-MI) standards for curation and data exchange. MINT data are freely accessible and downloadable at http://mint.bio.uniroma2.it/mint/download.do. We report here the growth of the database, the major changes in curation policy and a new algorithm to assign a confidence to each Interaction.
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MINT, the Molecular Interaction database: 2009 update.
Nucleic acids research, 2009Co-Authors: Arnaud Ceol, Andrew Chatr-aryamontri, Luisa Castagnoli, Luana Licata, Leonardo Briganti, Daniele Peluso, Livia Perfetto, Gianni CesareniAbstract:MINT (http://mint.bio.uniroma2.it/mint) is a public repository for Molecular Interactions reported in peer-reviewed journals. Since its last report, MINT has grown considerably in size and evolved in scope to meet the requirements of its users. The main changes include a more precise definition of the curation policy and the development of an enhanced and user-friendly interface to facilitate the analysis of the ever-growing Interaction dataset. MINT has adopted the PSI-MI standards for the annotation and for the representation of Molecular Interactions and is a member of the IMEx consortium.
