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Multi-omics analysis and integration

Due to the continuous increase in the number and complexity of genomics and biological data, new computer science techniques are needed to analyze these data and provide valuable insights into the main features.

Consequently, a large amount of heterogeneous complex data related to several diseases and healthy individuals is now available (e.g., RNA-seq, gene expression data, miRNAs expression data, methylation sequencing data, and many others). Each of these data is also called omic, and their integrative study is called multi-omics. In this context, the aim is to integrate multi-omics data involving thousands of features (genes, microRNA) and identify which of them are relevant for a specific biological process.

From a computational point of view, finding the best strategies for multi-omics analysis and relevant features identification is a very open challenge.



1 Lovino, Marta; Randazzo, Vincenzo; Ciravegna, Gabriele; Barbiero, Pietro; Ficarra, Elisa; Cirrincione, Giansalvo "A survey on data integration for multi-omics sample clustering" NEUROCOMPUTING, vol. 488, pp. 494 -508 , 2022 | DOI: 10.1016/j.neucom.2021.11.094 Journal
2 Barbiero, Pietro; Lovino, Marta; Siviero, Mattia; Ciravegna, Gabriele; Randazzo, Vincenzo; Ficarra, Elisa; Cirrincione, Giansalvo "Unsupervised Multi-Omic Data Fusion: the Neural Graph Learning Network" LNCS, vol. 12463, Bari (ita), pp. 172 -182 , Ottobre 2020, 2020 | DOI: 10.1007/978-3-030-60799-9_15 Conference
3 Lovino, Marta; Bontempo, Gianpaolo; Cirrincione, Giansalvo; Ficarra, Elisa "Multi-omics classification on kidney samples exploiting uncertainty-aware models" LNCS, vol. LNCS, Bari (Online), pp. 32 -42 , Oct 10-11th 2020, 2020 | DOI: https://doi.org/10.1007/978-3-030-60802-6_4 Conference
4 Roberti, Ilaria; Lovino, Marta; Di Cataldo, Santa; Ficarra, Elisa; Urgese, Gianvito "Exploiting Gene Expression Profiles for the Automated Prediction of Connectivity between Brain Regions" INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, vol. 20, 2019 | DOI: 10.3390/ijms20082035 Journal

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