Online citations, reference lists, and bibliographies.
← Back to Search

A Pseudo-Temporal Causality Approach To Identifying MiRNA-mRNA Interactions During Biological Processes

Andres M. Cifuentes-Bernal, Vu VH Pham, Xiaomei Li, Lin Liu, Jiuyong Li, Thuc Duy Le

Save to my Library
Download PDF
Analyze on Scholarcy
Share
AbstractMotivationmicroRNAs (miRNAs) are important gene regulators and they are involved in many biological processes, including cancer progression. Therefore, correctly identifying miRNA-mRNA interactions is a crucial task. To this end, a huge number of computational methods has been developed, but they mainly use the data at one snapshot and ignore the dynamics of a biological process. The recent development of single cell data and the booming of the exploration of cell trajectories using “pseudo-time” concept have inspired us to develop a pseudo-time based method to infer the miRNA-mRNA relationships characterising a biological process by taking into account the temporal aspect of the process.ResultsWe have developed a novel approach, called pseudo-time causality (PTC), to find the causal relationships between miRNAs and mRNAs during a biological process. We have applied the proposed method to both single cell and bulk sequencing datasets for Epithelia to Mesenchymal Transition (EMT), a key process in cancer metastasis. The evaluation results show that our method significantly outperforms existing methods in finding miRNA-mRNA interactions in both single cell and bulk data. The results suggest that utilising the pseudo-temporal information from the data helps reveal the gene regulation in a biological process much better than using the static information.AvailabilityR scripts and datasets can be found at https://github.com/AndresMCB/PTC