Integrated multi-omics analyses in oncology: a review of machine learning methods and tools
In recent years, high-throughput sequencing technologies provide unprecedented
opportunity to depict cancer samples at multiple molecular levels. The integration and …
opportunity to depict cancer samples at multiple molecular levels. The integration and …
Computational approaches for network-based integrative multi-omics analysis
Advances in omics technologies allow for holistic studies into biological systems. These
studies rely on integrative data analysis techniques to obtain a comprehensive view of the …
studies rely on integrative data analysis techniques to obtain a comprehensive view of the …
SourceSet: A graphical model approach to identify primary genes in perturbed biological pathways
E Salviato, V Djordjilović, M Chiogna… - PLoS computational …, 2019 - journals.plos.org
Topological gene-set analysis has emerged as a powerful means for omic data
interpretation. Although numerous methods for identifying dysregulated genes have been …
interpretation. Although numerous methods for identifying dysregulated genes have been …
Searching for a source of difference in Gaussian graphical models
V Djordjilović, M Chiogna - arXiv preprint arXiv:1811.02503, 2018 - arxiv.org
In this work, we look at a two-sample problem within the framework of Gaussian graphical
models. When the global hypothesis of equality of two distributions is rejected, the interest is …
models. When the global hypothesis of equality of two distributions is rejected, the interest is …
Heterogeneous Graphical Models with Applications to Omics Data
I Bussoli - 2019 - research.unipd.it
Thanks to the advances in bioinformatics and high-throughput methodologies of the last
decades, a large unprecedented amount of biological data coming from various experiments …
decades, a large unprecedented amount of biological data coming from various experiments …