Dataset Information

Identification of plant microRNAs using convolutional neural network.

ABSTRACT: MicroRNAs (miRNAs) are of significance in tuning and buffering gene expression. Despite abundant analysis tools that have been developed in the last two decades, plant miRNA identification from next-generation sequencing (NGS) data remains challenging. Here, we show that we can train a convolutional neural network to accurately identify plant miRNAs from NGS data. Based on our methods, we also present a user-friendly pure Java-based software package called Small RNA-related Intelligent and Convenient Analysis Tools (SRICATs). SRICATs encompasses all the necessary steps for plant miRNA analysis. Our results indicate that SRICATs outperforms currently popular software tools on the test data from five plant species. For non-commercial users, SRICATs is freely available at https://sourceforge.net/projects/sricats.

SUBMITTER: Zhang Y

PROVIDER: S-EPMC10985208 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature

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Identification of plant microRNAs using convolutional neural network.

Zhang Yun Y Huang Jianghua J Xie Feixiang F Huang Qian Q Jiao Hongguan H Cheng Wenbo W

Frontiers in plant science 20240319

MicroRNAs (miRNAs) are of significance in tuning and buffering gene expression. Despite abundant analysis tools that have been developed in the last two decades, plant miRNA identification from next-generation sequencing (NGS) data remains challenging. Here, we show that we can train a convolutional neural network to accurately identify plant miRNAs from NGS data. Based on our methods, we also present a user-friendly pure Java-based software package called Small RNA-related Intelligent and Conve ...[more]

PMID: 38567128

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Dataset Information

Identification of plant microRNAs using convolutional neural network.

Publications

Identification of plant microRNAs using convolutional neural network.

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