AIMC Topic: Sequence Analysis, RNA

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Quantitative Modeling of Stemness in Single-Cell RNA Sequencing Data: A Nonlinear One-Class Support Vector Machine Method.

Journal of computational biology : a journal of computational molecular cell biology Nov 28, 2023
Intratumoral heterogeneity and the presence of cancer stem cells are challenging issues in cancer therapy. An appropriate quantification of the stemness of individual cells for assessing the potential for self-renewal and differentiation from the cel...
Humans Neoplasms Support Vector Machine Cell Differentiation Single-Cell Analysis Sequence Analysis, RNA
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Evaluation of deep learning-based feature selection for single-cell RNA sequencing data analysis.

Genome biology Nov 10, 2023
BACKGROUND: Feature selection is an essential task in single-cell RNA-seq (scRNA-seq) data analysis and can be critical for gene dimension reduction and downstream analyses, such as gene marker identification and cell type classification. Most popula...
Cluster Analysis Single-Cell Analysis Sequence Analysis, RNA Gene Expression Profiling Reproducibility of Results Data Analysis Deep Learning Algorithms
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AliNA - a deep learning program for RNA secondary structure prediction.

Molecular informatics Nov 2, 2023
Nowadays there are numerous discovered natural RNA variations participating in different cellular processes and artificial RNA, e. g., aptamers, riboswitches. One of the required tasks in the investigation of their functions and mechanism of influenc...
Sequence Analysis, RNA Humans RNA Nucleic Acid Conformation Algorithms Deep Learning
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LSTM4piRNA: Efficient piRNA Detection in Large-Scale Genome Databases Using a Deep Learning-Based LSTM Network.

International journal of molecular sciences Oct 27, 2023
Piwi-interacting RNAs (piRNAs) are a new class of small, non-coding RNAs, crucial in the regulation of gene expression. Recent research has revealed links between piRNAs, viral defense mechanisms, and certain human cancers. Due to their clinical pote...
Deep Learning Sequence Analysis, RNA Humans Algorithms Piwi-Interacting RNA RNA, Small Interfering RNA, Small Untranslated
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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 ...
Single-Cell Analysis Single-Cell Gene Expression Analysis Support Vector Machine Sequence Analysis, RNA Gene Expression Profiling Machine Learning Cluster Analysis Transcriptome Algorithms
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Artificial Intelligence Models for Cell Type and Subtype Identification Based on Single-Cell RNA Sequencing Data in Vision Science.

IEEE/ACM transactions on computational biology and bioinformatics Oct 9, 2023
Single-cell RNA sequencing (scRNA-seq) provides a high throughput, quantitative and unbiased framework for scientists in many research fields to identify and characterize cell types within heterogeneous cell populations from various tissues. However,...
Gene Expression Profiling Single-Cell Analysis Cluster Analysis RNA Sequence Analysis, RNA Artificial Intelligence
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Methods for cell-type annotation on scRNA-seq data: A recent overview.

Journal of bioinformatics and computational biology Sep 23, 2023
The evolution of single-cell technology is ongoing, continually generating massive amounts of data that reveal many mysteries surrounding intricate diseases. However, their drawbacks continue to constrain us. Among these, annotating cell types in sin...
Sequence Analysis, RNA Gene Expression Profiling Single-Cell Gene Expression Analysis Neural Networks, Computer
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Predicting transcriptional outcomes of novel multigene perturbations with GEARS.

Nature biotechnology Aug 17, 2023
Understanding cellular responses to genetic perturbation is central to numerous biomedical applications, from identifying genetic interactions involved in cancer to developing methods for regenerative medicine. However, the combinatorial explosion in...
Gene Regulatory Networks Deep Learning Humans Computational Biology Sequence Analysis, RNA Single-Cell Analysis Transcription, Genetic Computer Simulation
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Machine-learning and combined analysis of single-cell and bulk-RNA sequencing identified a DC gene signature to predict prognosis and immunotherapy response for patients with lung adenocarcinoma.

Journal of cancer research and clinical oncology Jul 28, 2023
BACKGROUND: Innate immune effectors, dendritic cells (DCs), influence cancer prognosis and immunotherapy significantly. As such, dendritic cells are important in killing tumors and influencing tumor microenvironment, whereas their roles in lung adeno...
Single-Cell Analysis Lung Neoplasms Sequence Analysis, RNA Adenocarcinoma of Lung Immunotherapy Transcriptome Dendritic Cells Male Middle Aged Humans Female Tumor Microenvironment Biomarkers, Tumor Machine Learning Prognosis
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Rm-LR: A long-range-based deep learning model for predicting multiple types of RNA modifications.

Computers in biology and medicine Jul 8, 2023
Recent research has highlighted the pivotal role of RNA post-transcriptional modifications in the regulation of RNA expression and function. Accurate identification of RNA modification sites is important for understanding RNA function. In this study,...
RNA Deep Learning Sequence Analysis, RNA
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