Algorithms for Detecting Significantly Mutated Pathways in Cancer

By Fabio Vandin, Eli Upfal, Benjamin J. Raphael. Annual International Conference on Research in Computational Molecular Biology, 2010

448 citations recorded by the source corpus.

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/d62415366889696d27480ed1954b6a46c59adc6c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Genetics

In Molecular Biology

Citations in the corpus

Network-based machine learning and graph theory algorithms for precision oncology (2017, methodology): “HotNet 53 ﬁ rst maps gene alterations in a gene network and then employs a diffusion kernel 54 to build an in ﬂ uence graph with the edges weighted by the in ﬂ uence between each pair of genes.”
Methods for the integration of multi-omics data: mathematical aspects (2016, methodology): “For example Vandin and Upfal [45] presented a computationally efficient strategy for the identification of sub-networks considering the hydrodynamic model introduced by Qi et al. [46]: fluid is pumped into the source node s at a constant rate, diffuses through the graph along the edges, and is lost…”
Network propagation: a universal amplifier of genetic associations (2017, methodology): “This approach was used by the HotNet 86 and HotNet2 (REF.”
Pathway and Network Analysis of Cancer Genomes (2015, unknown): “The HotNet 55 tool treats the gene network as a metallic lattice, and then uses the physics of heat diffusion to model the effects of gene alterations.”
Mutual exclusivity analysis identifies oncogenic network modules. (2012, methodology): “have used a network diffusion algorithm to identify subnetworks enriched for mutations within a large gene interaction network (Vandin et al. 2010).”
Integrative approaches for finding modular structure in biological networks (2013, methodology): “Recently, network propagation methods such as those implemented in the bioinformatics tools HotNet and TieDIE (TABLE 1) have been used for network mapping of cancer mutations.”
Computational solutions for omics data (2013, methodology): “In the context of analysing cancer genomes, approaches based on diffusion 148 and shortest paths 149 (Hotnet and Netbox) have been applied to identify subnetworks enriched in recurrently mutated proteins across patients.”
Network-based stratification of tumor mutations (2013, background): “An increasing number of studies have successfully integrated these network databases with tumor molecular profiles to map the molecular pathways of cancer 23–27 .”