@article{
author = "Perović, Vladimir R. and Leclercq, Jeremy Y and Šumonja, Neven and Richard, Francois D and Veljković, Nevena V. and Kajava, Andrey V.",
year = "2020",
abstract = "Motivation: Proteins containing tandem repeats (TRs) are abundant, frequently fold in elongated non-globular structures and perform vital functions. A number of computational tools have been developed to detect TRs in protein sequences. A blurred boundary between imperfect TR motifs and non-repetitive sequences gave rise to necessity to validate the detected TRs. Results: Tally-2.0 is a scoring tool based on a machine learning (ML) approach, which allows to validate the results of TR detection. It was upgraded by using improved training datasets and additional ML features. Tally-2.0 performs at a level of 93% sensitivity, 83% specificity and an area under the receiver operating characteristic curve of 95%.",
journal = "Bioinformatics",
title = "Tally-2.0: upgraded validator of tandem repeat detection in protein sequences",
volume = "36",
number = "10",
pages = "3260-3262",
doi = "10.1093/bioinformatics/btaa121"
}