Below are a collection of excerpts from biomedical research articles. Excerpts are separated by newlines. Your task is to answer a question based these excerpts. Your response should be formatted as a `json` array.

For instance, given excerpts from articles studying breast cancer, and the question "what are some common genes associated with breast cancer?", an answer might be formatted like: ["BRCA1", "BRCA2", "TP53", ...]. Only include answers that are mentioned in the provided exerpts. The array should always have at least one answer; do not respond with an empty array []. Do not include any text in your response other than the answer array.

Context: Numerous algorithms that are used to detect genome-wide circRNA expression from RNA sequencing (RNA-seq) data have been developed in the past few years, but there is little overlap in their predictions and no clear gold-standard method to assess the accuracy of these algorithms.
We developed the software tandem, DCC and CircTest DCC uses output from the STAR read mapper to systematically detect back-splice junctions in next-generation sequencing data.
Circular RNA profile in gliomas revealed by identification tool UROBORUS.
In this work, we have developed a computational pipeline named UROBORUS to detect circRNAs in total RNA-seq data.
Here, we use common RNAseq datasets to scrutinize and compare the output from five different algorithms; circRNA_finder, find_circ, CIRCexplorer, CIRI, and MapSplice and evaluate the levels of bona fide and false positive circRNAs based on RNase R resistance.
miARma-Seq: a comprehensive tool for miRNA, mRNA and circRNA analysis.
PcircRNA_finder: a software for circRNA prediction in plants.
A circRNA prediction software for plants (termed PcircRNA_finder) was developed that is more sensitive in detecting circRNAs than other frequently used programs (such as find_circ and CIRCexplorer)
Recently, circular RNA (circRNA), a class of endogenous non-protein coding RNAs that contain a circular loop, was found to exhibit multiple biological effects.
RESULTS A circRNA prediction software for plants (termed PcircRNA_finder) was developed that is more sensitive in detecting circRNAs than other frequently used programs (such as find_circ and CIRCexplorer), Based on analysis of simulated and real rRNA-/RNAase R RNA-Seq data from Arabidopsis thaliana and rice PcircRNA_finder provides a more comprehensive sensitive, precise prediction method for plants circRNAs.

Question:
Which are the best methods for the prediction of circular RNA (circRNA)?
["circRNA_finder", "find_circ", "CIRCexplorer", "CIRI", "MapSplice", "UROBORUS", "Circ TEST DCC", "miARma-Seq"]