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ModulOmics: Integrating Multi-Omics Data to Identify Cancer Driver Modules [article]

Dana Silverbush, Simona Cristea, Gali Yanovich, Tamar Geiger, Niko Beerenwinkel, Roded Sharan
2018 bioRxiv   pre-print
Here, we describe ModulOmics, a method to de novo identify cancer driver pathways, or modules, by integrating multiple data types (protein-protein interactions, mutual exclusivity of mutations or copy  ...  Across several cancer types, ModulOmics identifies highly functionally connected modules enriched with cancer driver genes, outperforming state-of-the-art methods.  ...  We demonstrate the performance of ModulOmics in identifying modules enriched with known cancer driver genes and pathways in three largescale multi-omics TCGA datasets: breast cancer, GBM, and ovarian cancer  ... 
doi:10.1101/288399 fatcat:ly3fd3emjzczfpiishuit2fy4i

MuSA: a graphical user interface for multi-OMICs data integration in radiogenomic studies

Mario Zanfardino, Rossana Castaldo, Katia Pane, Ornella Affinito, Marco Aiello, Marco Salvatore, Monica Franzese
2021 Scientific Reports  
Multi-omics data integration can provide meaningful contribution to early diagnosis and an accurate estimate of prognosis and treatment in cancer.  ...  We proposed to use MultiAssayExperiment (MAE) as an integrated data structure to combine multi-omics data facilitating the exploration of heterogeneous data.  ...  ModulOmics tool is able to identify de novo cancer driver pathways by integrating, into a single probabilistic model, multiple data types such as protein-protein interactions, mutations or copy number  ... 
doi:10.1038/s41598-021-81200-z pmid:33452365 fatcat:6dxxmgduwbdiba7m4vhhufpm2e

SUBATOMIC: a SUbgraph BAsed mulTi-OMIcs Clustering framework to analyze integrated multi-edge networks [article]

Jens Uwe Loers, Vanessa Vermeirssen
2022 bioRxiv   pre-print
Furthermore, we integrated modules with condition specific expression data to study the influence of hypoxia in three cancer cell lines.  ...  Module detection methods can decompose these networks into smaller interpretable modules. However, these methods are not adapted to deal with multi-omics data nor consider topological features.  ...  Acknowledgements We would like to thank Kenneth Stoop and Pieter Audenaert for their help with running the ISMAGS algorithm.  ... 
doi:10.1101/2022.06.01.494279 fatcat:uwlaxkr4qvexlfzpal6ecpcqte

Performance Assessment of the Network Reconstruction Approaches on Various Interactomes

M. Kaan Arici, Nurcan Tuncbag
2021 Frontiers in Molecular Biosciences  
The main challenge is how to integrate the data together in an accurate way.  ...  Beyond the list of molecules, there is a necessity to collectively consider multiple sets of omic data and to reconstruct the connections between the molecules.  ...  predicted the cancer driver modules.  ... 
doi:10.3389/fmolb.2021.666705 pmid:34676243 pmcid:PMC8523993 fatcat:zqq5wb3xu5f5ncrbpqdmgebkwi

Capturing the Hierarchically Assorted Modules of Protein Interaction in the Organized Nucleome [article]

Shuaijian Dai, Shichang Liu, Chen Zhou, Fengchao Yu, Guang Zhu, Wenhao Zhang, Haiteng Deng, AI Burlingame, Weichuan Yu, Tingliang Wang, Ning Li
2022 bioRxiv   pre-print
The integration of dimethyl-labelling with XL-MS generated a quantitative XL-MS workflow (qXL-MS) that consequently identified 5,340 cross-linked peptides (crosslinks) from nucleome.  ...  To elucidate the global connectivity of nucleomic proteins and to decipher the hierarchically organized modules of protein interaction that are involved in nucleomic organization and nuclear events, both  ...  to identify cancer diver pathways (Silverbush et al., 2019) .  ... 
doi:10.1101/2022.08.14.503837 fatcat:6knopksdsjcdfm3r6patv2b7ci