Literature DB >> 30990192

MCNF: A Novel Method for Cancer Subtyping by Integrating Multi-Omics and Clinical Data.

Lan Zhao, Hong Yan.   

Abstract

In the age of personalized medicine, there is a great need to classify cancer (from the same organ site) into homogeneous subtypes. Recent technology advancements in genome-wide molecular profiling have made it possible to profiling multiple molecular datasets to characterize the genomic changes in various cancer types. How to take full advantage of the availability of these omics data? And how to integrate these molecular data with patient clinical data to do a more systematic subtyping of cancer are the focuses of the paper. We proposed a new method called Molecular and Clinical Networks Fusion (MCNF) to classify cancer into homogeneous subtypes. Our method has two highlights: one is that it can integrate both numerical and non-numerical data into the fused network; the next highlight is that it is unsupervised, which means it can automatically determine the optimal number of clusters.

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Year:  2019        PMID: 30990192     DOI: 10.1109/TCBB.2019.2910515

Source DB:  PubMed          Journal:  IEEE/ACM Trans Comput Biol Bioinform        ISSN: 1545-5963            Impact factor:   3.710


  2 in total

1.  MultiGATAE: A Novel Cancer Subtype Identification Method Based on Multi-Omics and Attention Mechanism.

Authors:  Ge Zhang; Zhen Peng; Chaokun Yan; Jianlin Wang; Junwei Luo; Huimin Luo
Journal:  Front Genet       Date:  2022-03-21       Impact factor: 4.599

2.  Integrative Network Fusion: A Multi-Omics Approach in Molecular Profiling.

Authors:  Marco Chierici; Nicole Bussola; Alessia Marcolini; Margherita Francescatto; Alessandro Zandonà; Lucia Trastulla; Claudio Agostinelli; Giuseppe Jurman; Cesare Furlanello
Journal:  Front Oncol       Date:  2020-06-30       Impact factor: 6.244

  2 in total

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