Footprint-based functional analysis of multiomic data

Current Opinion in Systems Biology
Aurelien Dugourd, Julio Saez-Rodriguez

Abstract

Omic technologies allow us to generate extensive data, including transcriptomic, proteomic, phosphoproteomic and metabolomic. These data can be used to study signal transduction, gene regulation and metabolism. In this review, we summarise resources and methods to analysis these types of data. We focus on methods developed to recover functional insights using footprints. Footprints are signatures defined by the effect of molecules or processes of interest. They integrate information from multiple measurements whose abundances are under the influence of a common regulator. For example, transcripts controlled by a transcription factor or peptides phosphorylated by a kinase. Footprints can also be generalised across multiple types of omic data. Thus, we also present methods to integrate multiple types of omic data and features (such as the ones derived from footprints) together. We highlight some examples of studies that leverage such approaches to discover new biological mechanisms.

Citations

Aug 13, 2020·Current Heart Failure Reports·Jan D LanzerJulio Saez-Rodriguez
Dec 4, 2020·FEBS Letters·Bence Szalai, Julio Saez-Rodriguez
Jan 28, 2021·Molecular Systems Biology·Aurelien DugourdJulio Saez-Rodriguez
Feb 4, 2021·F1000Research·Yael ParanZvi Kam
Jul 7, 2021·Toxicology Letters·Panuwat TrairatphisanJulio Saez-Rodriguez

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Methods Mentioned

BETA
glycosylation

Software Mentioned

STRINGdb
DoRothEA
Pathway Commons
TieDIE
PhosphositePlus
KSEA
PROGENy
Reactome
REcon3D
VIPER

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