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Article

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Title

Datasets for Benchmarking RNA Design Algorithms

Authors

[ 1 ] Instytut Informatyki, Wydział Informatyki i Telekomunikacji, Politechnika Poznańska | [ P ] employee

Scientific discipline (Law 2.0)

[2.3] Information and communication technology

Year of publication

2024

Published in

Methods in molecular biology (Clifton, N.J.)

Journal year: 2024 | Journal volume: vol. 2847

Article type

scientific article

Publication language

english

Abstract

EN RNA molecules play vital roles in many biological processes, such as gene regulation or protein synthesis. The adoption of a specific secondary and tertiary structure by RNA is essential to perform these diverse functions, making RNA a popular tool in bioengineering therapeutics. The field of RNA design responds to the need to develop novel RNA molecules that possess specific functional attributes. In recent years, computational tools for predicting RNA sequences with desired folding characteristics have improved and expanded. However, there is still a lack of well-defined and standardized datasets to assess these programs. Here, we present a large dataset of internal and multibranched loops extracted from PDB-deposited RNA structures that encompass a wide spectrum of design difficulties. Furthermore, we conducted benchmarking tests of widely utilized open-source RNA design algorithms employing this dataset.

Date of online publication

24.09.2024

Pages (from - to)

229 - 240

DOI

10.1007/978-1-0716-4079-1_16

URL

https://link.springer.com/protocol/10.1007/978-1-0716-4079-1_16

Ministry points / journal

70

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