AIMC Topic: Computational Biology

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An NLP-based method to mine gene and function relationships from published articles.

Scientific reports Mar 3, 2025
Understanding the intricacies of genes function within biological systems is paramount for scientific advancement and medical progress. Owing to the evolving landscape of this research and the complexity of biological processes, however, this task pr...
Data Mining Computational Biology Gene Ontology Natural Language Processing Arabidopsis
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Unveiling the ageing-related genes in diagnosing osteoarthritis with metabolic syndrome by integrated bioinformatics analysis and machine learning.

Artificial cells, nanomedicine, and biotechnology Mar 1, 2025
Ageing significantly contributes to osteoarthritis (OA) and metabolic syndrome (MetS) pathogenesis, yet the underlying mechanisms remain unknown. This study aimed to identify ageing-related biomarkers in OA patients with MetS. OA and MetS datasets an...
Humans Osteoarthritis Machine Learning Aging Gene Regulatory Networks Computational Biology Metabolic Syndrome
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Integrating Artificial Intelligence and Bioinformatics Methods to Identify Disruptive STAT1 Variants Impacting Protein Stability and Function.

Genes Mar 1, 2025
The Signal Transducer and Activator of Transcription 1 () gene is an essential component of the JAK-STAT signaling pathway. This pathway plays a pivotal role in the regulation of different cellular processes, including immune responses, cell growth,...
Humans Protein Stability Mutation, Missense STAT1 Transcription Factor Artificial Intelligence Polymorphism, Single Nucleotide Computational Biology
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Skittles: GNN-Assisted Pseudo-Ligands Generation and Its Application for Binding Sites Classification and Affinity Prediction.

Proteins Feb 28, 2025
Nowadays, multiple solutions are known for identifying ligand-protein binding sites. Another important task is labeling each point of a binding site with the appropriate atom type, a process known as pseudo-ligand generation. The number of solutions ...
Machine Learning Algorithms Protein Binding Neural Networks, Computer Models, Molecular Computational Biology Ligands Proteins Binding Sites Databases, Protein
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ieGENES: A machine learning method for selecting differentially expressed genes in cancer studies.

Journal of biomedical informatics Feb 28, 2025
Gene selection is crucial for cancer classification using microarray data. In the interests of improving cancer classification accuracy, in this paper, we developed a new wrapper method called ieGENES for gene selection. First we proposed a parsimoni...
Neoplasms Gene Expression Profiling Humans Computational Biology Machine Learning Gene Expression Regulation, Neoplastic Algorithms Databases, Genetic Oligonucleotide Array Sequence Analysis
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TransRM: Weakly supervised learning of translation-enhancing N6-methyladenosine (mA) in circular RNAs.

International journal of biological macromolecules Feb 27, 2025
As our understanding of Circular RNAs (circRNAs) continues to expand, accumulating evidence has demonstrated that circRNAs can interact with microRNAs and RNA-binding proteins to modulate gene expression. More importantly, a subset of circRNAs has be...
Translating RNA, Circular Internal Ribosome Entry Sites Supervised Machine Learning Adenosine Protein Biosynthesis Humans Computational Biology
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Identify the potential target of efferocytosis in knee osteoarthritis synovial tissue: a bioinformatics and machine learning-based study.

Frontiers in immunology Feb 27, 2025
INTRODUCTION: Knee osteoarthritis (KOA) is a degenerative joint disease characterized by the progressive deterioration of cartilage and synovial inflammation. A critical mechanism in the pathogenesis of KOA is impaired efferocytosis in synovial tissu...
Synovial Membrane Gene Expression Profiling Phagocytosis Humans Databases, Genetic Gene Regulatory Networks Osteoarthritis, Knee Machine Learning Computational Biology Efferocytosis
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Identification of potential biomarkers for lung cancer using integrated bioinformatics and machine learning approaches.

PloS one Feb 27, 2025
Lung cancer is one of the most common cancer and the leading cause of cancer-related death worldwide. Early detection of lung cancer can help reduce the death rate; therefore, the identification of potential biomarkers is crucial. Thus, this study ai...
Computational Biology Gene Expression Regulation, Neoplastic Humans Protein Interaction Maps Biomarkers, Tumor Machine Learning Gene Regulatory Networks Gene Expression Profiling Prognosis Lung Neoplasms ROC Curve
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Leveraging diverse cell-death patterns in diagnosis of sepsis by integrating bioinformatics and machine learning.

PeerJ Feb 26, 2025
BACKGROUND: Sepsis is a life-threatening disease causing millions of deaths every year. It has been reported that programmed cell death (PCD) plays a critical role in the development and progression of sepsis, which has the potential to be a diagnosi...
Calgranulin B Biomarkers Female CARD Signaling Adaptor Proteins Male Gene Expression Profiling Computational Biology Transcriptome Humans Apoptosis Sepsis Machine Learning Calcium-Binding Proteins
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Tisslet tissues-based learning estimation for transcriptomics.

BMC bioinformatics Feb 25, 2025
In the context of multi-omics data analytics for various diseases, transcriptome-wide association studies leveraging genetically predicted gene expression hold promise for identifying novel regions linked to complex traits. However, existing methods ...
Computational Biology Organ Specificity Gene Expression Profiling Transcriptome Humans Machine Learning Algorithms
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