AIMC Topic: RNA, Fungal

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YModPred: an interpretable prediction method for multi-type RNA modification sites in S. cerevisiae based on deep learning.

BMC biology Aug 29, 2025
BACKGROUND: RNA post-transcriptional modifications involve the addition of chemical groups to RNA molecules or alterations to their local structure. These modifications can change RNA base pairing, affect thermal stability, and influence RNA folding,...
Deep Learning Saccharomyces cerevisiae RNA Processing, Post-Transcriptional RNA, Fungal
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iMethyl-Deep: N6 Methyladenosine Identification of Yeast Genome with Automatic Feature Extraction Technique by Using Deep Learning Algorithm.

Genes May 9, 2020
One of the most common and well studied post-transcription modifications in RNAs is N6-methyladenosine (m6A) which has been involved with a wide range of biological processes. Over the past decades, N6-methyladenosine produced some positive consequen...
Algorithms Deep Learning ROC Curve Computational Biology Datasets as Topic Methylation Saccharomyces cerevisiae Adenosine Genome, Fungal RNA Processing, Post-Transcriptional RNA, Fungal
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