AIMC Topic: Transcriptome

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Deep learning exploration of single-cell and spatially resolved cancer transcriptomics to unravel tumour heterogeneity.

Computers in biology and medicine Jul 18, 2023
Tumour heterogeneity is one of the critical confounding aspects in decoding tumour growth. Malignant cells display variations in their gene transcription profiles and mutation spectra even when originating from a single progenitor cell. Single-cell a...
Neoplasms Gene Expression Profiling Transcriptome Deep Learning Humans Precision Medicine
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Deep learning of 2D-Restructured gene expression representations for improved low-sample therapeutic response prediction.

Computers in biology and medicine Jul 18, 2023
Clinical outcome prediction is important for stratified therapeutics. Machine learning (ML) and deep learning (DL) methods facilitate therapeutic response prediction from transcriptomic profiles of cells and clinical samples. Clinical transcriptomic ...
Gene Expression Profiling Transcriptome Humans Algorithms Deep Learning Benchmarking
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Interpretable deep learning for improving cancer patient survival based on personal transcriptomes.

Scientific reports Jul 13, 2023
Precision medicine chooses the optimal drug for a patient by considering individual differences. With the tremendous amount of data accumulated for cancers, we develop an interpretable neural network to predict cancer patient survival based on drug p...
Humans Neural Networks, Computer Deep Learning Neoplasms Transcriptome Research
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DeeP4med: deep learning for P4 medicine to predict normal and cancer transcriptome in multiple human tissues.

BMC bioinformatics Jul 4, 2023
BACKGROUND: P4 medicine (predict, prevent, personalize, and participate) is a new approach to diagnosing and predicting diseases on a patient-by-patient basis. For the prevention and treatment of diseases, prediction plays a fundamental role. One of ...
Machine Learning Humans Neoplasms Transcriptome Bayes Theorem Deep Learning
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Deep learning applications in single-cell genomics and transcriptomics data analysis.

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie Jul 1, 2023
Traditional bulk sequencing methods are limited to measuring the average signal in a group of cells, potentially masking heterogeneity, and rare populations. The single-cell resolution, however, enhances our understanding of complex biological system...
Machine Learning Deep Learning Genomics Gene Expression Profiling Transcriptome
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scTour: a deep learning architecture for robust inference and accurate prediction of cellular dynamics.

Genome biology Jun 23, 2023
Despite the continued efforts, a batch-insensitive tool that can both infer and predict the developmental dynamics using single-cell genomics is lacking. Here, I present scTour, a novel deep learning architecture to perform robust inference and accur...
Deep Learning Gene Expression Profiling Genomics Transcriptome
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Deciphering ligand-receptor-mediated intercellular communication based on ensemble deep learning and the joint scoring strategy from single-cell transcriptomic data.

Computers in biology and medicine Jun 12, 2023
BACKGROUND: Cell-cell communication in a tumor microenvironment is vital to tumorigenesis, tumor progression and therapy. Intercellular communication inference helps understand molecular mechanisms of tumor growth, progression and metastasis.
Head and Neck Neoplasms Cell Communication Ligands Endothelial Cells Sequence Analysis, RNA Tumor Microenvironment Humans Deep Learning Squamous Cell Carcinoma of Head and Neck Melanoma Transcriptome
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Harnessing deep learning into hidden mutations of neurological disorders for therapeutic challenges.

Archives of pharmacal research Jun 1, 2023
The relevant study of transcriptome-wide variations and neurological disorders in the evolved field of genomic data science is on the rise. Deep learning has been highlighted utilizing algorithms on massive amounts of data in a human-like manner, and...
Nervous System Diseases Humans Transcriptome Deep Learning Mutation
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SPIN-AI: A Deep Learning Model That Identifies Spatially Predictive Genes.

Biomolecules May 27, 2023
Spatially resolved sequencing technologies help us dissect how cells are organized in space. Several available computational approaches focus on the identification of spatially variable genes (SVGs), genes whose expression patterns vary in space. The...
Deep Learning Gene Expression Profiling Transcriptome Artificial Intelligence
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TransOrGAN: An Artificial Intelligence Mapping of Rat Transcriptomic Profiles between Organs, Ages, and Sexes.

Chemical research in toxicology May 18, 2023
Animal studies are required for the evaluation of candidate drugs to ensure patient and volunteer safety. Toxicogenomics is often applied in these studies to gain understanding of the underlying mechanisms of toxicity, which is usually focused on cri...
Transcriptome Rats Male Artificial Intelligence Female Animals
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