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%.
CITATION STYLE
Perovic, V., Leclercq, J. Y., Sumonja, N., Richard, F. D., Veljkovic, N., & Kajava, A. V. (2020). Tally-2.0: Upgraded validator of tandem repeat detection in protein sequences. Bioinformatics, 36(10), 3260–3262. https://doi.org/10.1093/bioinformatics/btaa121
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