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MODIMO: Workshop on Multi-Omics Data Integration for Modelling Biological Systems

Published: 21 October 2023 Publication History

Abstract

Multi-omics analysis aims at extracting previously uncovered biological knowledge by integrating information across multiple single-omic sources. Past approaches have focused on the simultaneous analysis of a small number of omic data sets. Current challenges face the problem of integrating multiple omic sources into a unified complex model, or of combining already available tools for two-by-two omics analyses and merging their outcomes. By doing so and leveraging integrated system-level knowledge, multi-omic approaches ought to enable the development of better qualitative and quantitative models for descriptive and predictive analyses. To move this area forward, new statistical and algorithmic frameworks are needed, for example for generalizing classical graph theory results to heterogeneous networks, and applying them to diverse problems such as drug repurposing or understanding the immune response to infections. Thus, in short, this workshop aims at investigating novel methodologies for providing crucial insights into multi-omics data management, integration, and analysis to enable biological discoveries. The workshop will be sponsored by the InfoLife CINI National Laboratory (https://www.consorzio-cini.it/index.php/en/ ).

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  1. MODIMO: Workshop on Multi-Omics Data Integration for Modelling Biological Systems

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        cover image ACM Conferences
        CIKM '23: Proceedings of the 32nd ACM International Conference on Information and Knowledge Management
        October 2023
        5508 pages
        ISBN:9798400701245
        DOI:10.1145/3583780
        This work is licensed under a Creative Commons Attribution International 4.0 License.

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        Association for Computing Machinery

        New York, NY, United States

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        Published: 21 October 2023

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        Author Tags

        1. bioinformatics
        2. data integration
        3. modelling
        4. multi-omics data analysis

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