AIMC Topic: Base Sequence

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Identification of potential riboswitch elements in Homo sapiens mRNA 5'UTR sequences using positive-unlabeled machine learning.

PloS one Apr 24, 2025
Riboswitches are a class of noncoding RNA structures that interact with target ligands to cause a conformational change that can then execute some regulatory purpose within the cell. Riboswitches are ubiquitous and well characterized in bacteria and ...
5' Untranslated Regions Nucleic Acid Conformation Riboswitch Machine Learning RNA, Messenger Ligands Base Sequence Humans
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DHUpredET: A comparative computational approach for identification of dihydrouridine modification sites in RNA sequence.

Analytical biochemistry Mar 6, 2025
Laboratory-based detection of D sites is laborious and expensive. In this study, we developed effective machine learning models employing efficient feature encoding methods to identify D sites. Initially, we explored various state-of-the-art feature ...
Machine Learning RNA Base Sequence Uridine Computational Biology Sequence Analysis, RNA
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A sparse and wide neural network model for DNA sequences.

Neural networks : the official journal of the International Neural Network Society Dec 19, 2024
Accurate modeling of DNA sequences requires capturing distant semantic relationships between the nucleotide acid bases. Most existing deep neural network models face two challenges: (1) they are limited to short DNA fragments and cannot capture long-...
Neural Networks, Computer Deep Learning Humans Base Sequence Sequence Analysis, DNA DNA
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Generative language models on nucleotide sequences of human genes.

Scientific reports Sep 27, 2024
Language models, especially transformer-based ones, have achieved colossal success in natural language processing. To be precise, studies like BERT for natural language understanding and works like GPT-3 for natural language generation are very impor...
Sequence Analysis, DNA Natural Language Processing Humans Computational Biology Base Sequence
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DeepCBA: A deep learning framework for gene expression prediction in maize based on DNA sequences and chromatin interactions.

Plant communications Jun 10, 2024
Chromatin interactions create spatial proximity between distal regulatory elements and target genes in the genome, which has an important impact on gene expression, transcriptional regulation, and phenotypic traits. To date, several methods have been...
Base Sequence Promoter Regions, Genetic Gene Expression Regulation, Plant Chromatin Deep Learning Zea mays
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Predicting Serotonin Detection with DNA-Carbon Nanotube Sensors across Multiple Spectral Wavelengths.

Journal of chemical information and modeling May 13, 2024
Owing to the value of DNA-wrapped single-walled carbon nanotube (SWNT)-based sensors for chemically specific imaging in biology, we explore machine learning (ML) predictions DNA-SWNT serotonin sensor responsivity as a function of DNA sequence based o...
DNA Machine Learning Spectrometry, Fluorescence Biosensing Techniques Nanotubes, Carbon Serotonin Base Sequence
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Fundamentals for predicting transcriptional regulations from DNA sequence patterns.

Journal of human genetics May 10, 2024
Cell-type-specific regulatory elements, cataloged through extensive experiments and bioinformatics in large-scale consortiums, have enabled enrichment analyses of genetic associations that primarily utilize positional information of the regulatory el...
Transcription, Genetic Regulatory Sequences, Nucleic Acid Computational Biology Sequence Analysis, DNA Gene Expression Regulation Machine Learning Base Sequence Genomics Alleles Humans
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DEBFold: Computational Identification of RNA Secondary Structures for Sequences across Structural Families Using Deep Learning.

Journal of chemical information and modeling Apr 22, 2024
It is now known that RNAs play more active roles in cellular pathways beyond simply serving as transcription templates. These biological mechanisms might be mediated by higher RNA stereo conformations, triggering the need to understand RNA secondary ...
Nucleic Acid Conformation Thermodynamics Deep Learning RNA Base Sequence Computational Biology Models, Molecular
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promSEMBLE: Hard Pattern Mining and Ensemble Learning for Detecting DNA Promoter Sequences.

IEEE/ACM transactions on computational biology and bioinformatics Feb 5, 2024
Accurate identification of DNA promoter sequences is of crucial importance in unraveling the underlying mechanisms that regulate gene transcription. Initiation of transcription is controlled through regulatory transcription factors binding to promote...
TATA Box Machine Learning DNA Promoter Regions, Genetic Base Sequence Transcription, Genetic
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Self-supervised Learning for DNA sequences with circular dilated convolutional networks.

Neural networks : the official journal of the International Neural Network Society Dec 2, 2023
DNA molecules commonly exhibit wide interactions between the nucleobases. Modeling the interactions is important for obtaining accurate sequence-based inference. Although many deep learning methods have recently been developed for modeling DNA sequen...
Base Sequence DNA Humans Supervised Machine Learning Neural Networks, Computer
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