AIMC Topic: Transcriptome

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Deep learning and CRISPR-Cas13d ortholog discovery for optimized RNA targeting.

Cell systems Dec 12, 2023
Effective and precise mammalian transcriptome engineering technologies are needed to accelerate biological discovery and RNA therapeutics. Despite the promise of programmable CRISPR-Cas13 ribonucleases, their utility has been hampered by an incomplet...
CRISPR-Cas Systems RNA RNA, Guide, CRISPR-Cas Systems Transcriptome Deep Learning Humans
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Generating bulk RNA-Seq gene expression data based on generative deep learning models and utilizing it for data augmentation.

Computers in biology and medicine Dec 7, 2023
Large-scale high-throughput transcriptome sequencing data holds significant value in biomedical research. However, practical challenges such as difficulty in sample acquisition often limit the availability of large sample sizes, leading to decreased ...
Deep Learning RNA-Seq High-Throughput Nucleotide Sequencing Reproducibility of Results Transcriptome
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Personal transcriptome variation is poorly explained by current genomic deep learning models.

Nature genetics Nov 30, 2023
Genomic deep learning models can predict genome-wide epigenetic features and gene expression levels directly from DNA sequence. While current models perform well at predicting gene expression levels across genes in different cell types from the refer...
Transcriptome Deep Learning Genetic Variation Genome Genomics Humans
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Identifying the Interaction Between Tuberculosis and SARS-CoV-2 Infections via Bioinformatics Analysis and Machine Learning.

Biochemical genetics Nov 22, 2023
The number of patients with COVID-19 caused by severe acute respiratory syndrome coronavirus 2 is still increasing. In the case of COVID-19 and tuberculosis (TB), the presence of one disease affects the infectious status of the other. Meanwhile, coin...
COVID-19 SARS-CoV-2 Gene Expression Profiling Humans Machine Learning Computational Biology Coinfection Tuberculosis Transcriptome Protein Interaction Maps
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SPACEL: deep learning-based characterization of spatial transcriptome architectures.

Nature communications Nov 22, 2023
Spatial transcriptomics (ST) technologies detect mRNA expression in single cells/spots while preserving their two-dimensional (2D) spatial coordinates, allowing researchers to study the spatial distribution of the transcriptome in tissues; however, j...
Algorithms Gene Expression Profiling Deep Learning Models, Statistical Transcriptome
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Associations of maternal stress, gene expression, and newborn birthweight in the Democratic Republic of Congo.

American journal of biological anthropology Oct 27, 2023
OBJECTIVES: Maternal stress has long been associated with lower birthweight, which is associated with adverse health outcomes including many adult diseases. The underlying mechanisms remain elusive although changes in gene expression may play a role....
Placenta Adult Female Gene Expression Humans Infant, Newborn Transcriptome Democratic Republic of the Congo Young Adult Pregnancy Stress, Psychological Birth Weight
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On the use of QDE-SVM for gene feature selection and cell type classification from scRNA-seq data.

PloS one Oct 19, 2023
Cell type identification is one of the fundamental tasks in single-cell RNA sequencing (scRNA-seq) studies. It is a key step to facilitate downstream interpretations such as differential expression, trajectory inference, etc. scRNA-seq data contains ...
Cluster Analysis Machine Learning Algorithms Transcriptome Gene Expression Profiling Sequence Analysis, RNA Single-Cell Gene Expression Analysis Single-Cell Analysis Support Vector Machine
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Reliable interpretability of biology-inspired deep neural networks.

NPJ systems biology and applications Oct 10, 2023
Deep neural networks display impressive performance but suffer from limited interpretability. Biology-inspired deep learning, where the architecture of the computational graph is based on biological knowledge, enables unique interpretability where re...
Humans Mutation Models, Biological Neural Networks, Computer Transcriptome
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Prediction of Multiple Types of RNA Modifications via Biological Language Model.

IEEE/ACM transactions on computational biology and bioinformatics Oct 9, 2023
It has been demonstrated that RNA modifications play essential roles in multiple biological processes. Accurate identification of RNA modifications in the transcriptome is critical for providing insights into the biological functions and mechanisms. ...
RNA Saccharomyces cerevisiae Pseudouridine Arabidopsis Animals Transcriptome Mice Artificial Intelligence
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Immune response and mesenchymal transition of papillary thyroid carcinoma reflected in ultrasonography features assessed by radiologists and deep learning.

Journal of advanced research Oct 1, 2023
INTRODUCTION: Ultrasonography (US) features of papillary thyroid cancers (PTCs) are used to select nodules for biopsy due to their association with tumor behavior. However, the molecular biological mechanisms that lead to the characteristic US featur...
Radiologists Epithelial-Mesenchymal Transition Thyroid Cancer, Papillary Ultrasonography Gene Expression Regulation, Neoplastic Middle Aged Gene Expression Profiling Deep Learning Thyroid Neoplasms Transcriptome Aged Adult Male Humans Female
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