ArticleAdvances in experimental medicine and biology2022
Bioinformatics Methods for Modeling microRNA Regulatory Networks in Cancer.
Article in Advances in experimental medicine and biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed, 3 citations in OpenAlex.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
MicroRNAs (miRNAs) play important roles in the physiology and development of cancers. The increase of multidimensional molecular profiles of tumor patients generated by high-throughput sequencing technologies has enabled computational analysis of miRNA regulatory networks in cancer. In this chapter, we first summarized currently widely used computational methods for identifying miRNA-gene interactions. In addition, crosstalk among miRNAs and competitive endogenous RNAs (ceRNAs) represent novel layers of gene regulation mediated by miRNAs, which also play important roles in cancer. We next reviewed computational methods for modeling miRNA-miRNA crosstalk and ceRNA-ceRNA interactions in cancer. These methods integrate multi-omics data and range from genomics to phenomics. MiRNA-miRNA networks are generally constructed based on genomic sequences, transcriptomes, miRNA-gene regulation, and functional pathways. Moreover, five types of computational methods for identifying ceRNA-ceRNA interactions are summarized in this chapter. Among these methods, two types of global ceRNA regulation and three types of context-specific methods are included. The application of these computational methods focused on miRNA regulation in cancer provides valuable functional insights into the underlying mechanism of cancer, as well as future precision medicine.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.