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Computational Biology

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Elucidating the role of KCTD10 in coronary atherosclerosis: Harnessing bioinformatics and machine learning to advance understanding.

Scientific reports
Atherosclerosis (AS) is increasingly recognized as a chronic inflammatory disease that significantly compromises vascular health and serves as a major contributor to cardiovascular diseases. KCTD10, a protein implicated in a variety of biological pro...

Comprehensive integration of diagnostic biomarker analysis and immune cell infiltration features in sepsis via machine learning and bioinformatics techniques.

Frontiers in immunology
INTRODUCTION: Sepsis, a critical medical condition resulting from an irregular immune response to infection, leads to life-threatening organ dysfunction. Despite medical advancements, the critical need for research into dependable diagnostic markers ...

BacTermFinder: a comprehensive and general bacterial terminator finder using a CNN ensemble.

NAR genomics and bioinformatics
A terminator is a DNA region that ends the transcription process. Currently, multiple computational tools are available for predicting bacterial terminators. However, these methods are specialized for certain bacteria or terminator type (i.e. intrins...

DeepMVD: A Novel Multiview Dynamic Feature Fusion Model for Accurate Protein Function Prediction.

Journal of chemical information and modeling
Proteins, as the fundamental macromolecules of life, play critical roles in various biological processes. Recent advancements in intelligent protein function prediction methods leverage sequences, structures, and biomedical literature data. Among the...

DRAMMA: a multifaceted machine learning approach for novel antimicrobial resistance gene detection in metagenomic data.

Microbiome
BACKGROUND: Antibiotics are essential for medical procedures, food security, and public health. However, ill-advised usage leads to increased pathogen resistance to antimicrobial substances, posing a threat of fatal infections and limiting the benefi...

Yeast Knowledge Graphs Database for Exploring Saccharomyces Cerevisiae and Schizosaccharomyces Pombe.

Journal of molecular biology
Biomedical literature contains an extensive wealth of information on gene and protein function across various biological processes and diseases. However, navigating this vast and often restricted-access data can be challenging, making it difficult to...

EVlncRNA-net: A dual-channel deep learning approach for accurate prediction of experimentally validated lncRNAs.

International journal of biological macromolecules
Long non-coding RNAs (lncRNAs) play key roles in numerous biological processes and are associated with various human diseases. High-throughput RNA sequencing (HTlncRNAs) has identified tens of thousands of lncRNAs across species, but only a small fra...

GRATCR: Epitope-Specific T Cell Receptor Sequence Generation With Data-Efficient Pre-Trained Models.

IEEE journal of biomedical and health informatics
T cell receptors (TCRs) play a crucial role in numerous immunotherapies targeting tumor cells. However, their acquisition and optimization present significant challenges, involving laborious and time-consuming wet lab experimental resource. Deep gene...

CardiOT: Towards Interpretable Drug Cardiotoxicity Prediction Using Optimal Transport and Kolmogorov--Arnold Networks.

IEEE journal of biomedical and health informatics
Investigating the inhibitory effects of compounds on cardiac ion channels is essential for assessing cardiac drug safety. Consequently, researchers have developed computational models to evaluate combined cardiotoxicity (CCT) on cardiac ion channels....

NPENN: A Noise Perturbation Ensemble Neural Network for Microbiome Disease Phenotype Prediction.

IEEE journal of biomedical and health informatics
With advances in microbiomics, the crucial role of microbes in disease progression is increasingly recognized. However, predicting disease phenotypes using microbiome data remains challenging due to data complexity, heterogeneity, and limited model g...