AIMC Topic: Computational Biology
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Analysis and validation of hub genes for atherosclerosis and AIDS and immune infiltration characteristics based on bioinformatics and machine learning.
Scientific reports
Apr 10, 2025
Atherosclerosis is the major cause of cardiovascular diseases worldwide, and AIDS linked with chronic inflammation and immune activation, increases atherosclerosis risk. The application of bioinformatics and machine learning to identify hub genes for...
Integrative Multi-Omics Analysis Reveals Molecular Subtypes of Ovarian Cancer and Constructs Prognostic Models.
Journal of immunotherapy (Hagerstown, Md. : 1997)
Apr 9, 2025
Ovarian cancer (OV) remains the most lethal gynecological malignancy. The aim of this study was to identify molecular subtypes of OV through integrative multi-omics analysis and construct machine learning-based prognostic models for predicting the ef...
Comprehensive analysis of scRNA-seq and bulk RNA-seq data via machine learning and bioinformatics reveals the role of lysine metabolism-related genes in gastric carcinogenesis.
BMC cancer
Apr 9, 2025
BACKGROUND: Gastric cancer (GC) is a highly aggressive and heterogeneous cancer with extremely complex biological characteristics. Lysine and its metabolism are closely related to human cancer, but little is known about how lysine metabolism-related ...
Nomograms
Cell Proliferation
Carcinogenesis
Vimentin
Humans
Lysine
Machine Learning
Biomarkers, Tumor
Computational Biology
Prognosis
Sequence Analysis, RNA
Cell Line, Tumor
Stomach Neoplasms
Gene Expression Regulation, Neoplastic
RNA-Seq
Single-Cell Analysis
Gene Regulatory Networks
Single-Cell Gene Expression Analysis
Integration of graph neural networks and transcriptomics analysis identify key pathways and gene signature for immunotherapy response and prognosis of skin melanoma.
BMC cancer
Apr 9, 2025
OBJECTIVE: The assessment of immunotherapy plays a pivotal role in the clinical management of skin melanoma. Graph neural networks (GNNs), alongside other deep learning algorithms and bioinformatics approaches, have demonstrated substantial promise i...
Utilizing a deep learning model based on BERT for identifying enhancers and their strength.
PloS one
Apr 9, 2025
An enhancer is a specific DNA sequence typically located within a gene at upstream or downstream position and serves as a pivotal element in the regulation of eukaryotic gene transcription. Therefore, the recognition of enhancers is highly significan...
Unified Deep Learning of Molecular and Protein Language Representations with T5ProtChem.
Journal of chemical information and modeling
Apr 8, 2025
Deep learning has revolutionized difficult tasks in chemistry and biology, yet existing language models often treat these domains separately, relying on concatenated architectures and independently pretrained weights. These approaches fail to fully e...
MIDAA: deep archetypal analysis for interpretable multi-omic data integration based on biological principles.
Genome biology
Apr 8, 2025
High-throughput multi-omic molecular profiling allows the probing of biological systems at unprecedented resolution. However, integrating and interpreting high-dimensional, sparse, and noisy multimodal datasets remains challenging. Deriving new biolo...
DeepMethyGene: a deep-learning model to predict gene expression using DNA methylations.
BMC bioinformatics
Apr 8, 2025
Gene expression is the basis for cells to achieve various functions, while DNA methylation constitutes a critical epigenetic mechanism governing gene expression regulation. Here we propose DeepMethyGene, an adaptive recursive convolutional neural net...
Subtractive genomics approach: A guide to unveiling therapeutic targets across pathogens.
Journal of microbiological methods
Apr 7, 2025
Subtractive genomics is an adaptable bioinformatics technique that is used to identify potential therapeutic targets by differentiating essential genes in pathogens and non-pathogenic genes. Since, identification of therapeutic targets and understand...
An integrated AI knowledge graph framework of bacterial enzymology and metabolism.
Proceedings of the National Academy of Sciences of the United States of America
Apr 7, 2025
The study of bacterial metabolism holds immense significance for improving human health and advancing agricultural practices. The prospective applications of genomically encoded bacterial metabolism present a compelling opportunity, particularly in t...
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