AIMC Topic: Computational Biology

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Addressing bias in biomarker discovery for inflammatory bowel diseases: A multi-faceted analytical approach.

International immunopharmacology
Xiang-Guang et al. investigate the identification of novel biomarkers linked to M1 macrophage infiltration in inflammatory bowel diseases (IBD). Utilizing advanced bioinformatics and machine learning techniques, the researchers developed predictive m...

Limitations of current machine learning models in predicting enzymatic functions for uncharacterized proteins.

G3 (Bethesda, Md.)
Thirty to seventy percent of proteins in any given genome have no assigned function and have been labeled as the protein "unknome." This large knowledge shortfall is one of the final frontiers of biology. Machine learning (ML) approaches are enticing...

NABP-LSTM-Att: Nanobody-Antigen binding prediction using bidirectional LSTM and soft attention mechanism.

Computational biology and chemistry
In vertebrates, antibody-mediated immunity is a vital component of the immune system, and antibodies have become a rapidly expanding class of therapeutic agents. Nanobodies, a distinct type of antibody, have recently emerged as a stable and cost-effe...

Transcriptomic and single-cell insights into mitochondrial genes NDUFA8, ECI2, and ACADM in acute myocardial infarction.

Gene
Mitochondrial function plays a crucial role in understanding the pathogenesis of acute myocardial infarction.This study investigates mitochondrial function-related genes (MFRGs) in acute myocardial infarction (AMI) through bioinformatics and rigorous...

Identification of lipid metabolism-associated biomarkers in lupus nephritis by SVM model and therapeutic potential of Alisol B 23-acetate.

Gene
Systemic lupus erythematosus (SLE), a multifaceted autoimmune disorder, has lupus nephritis (LN) as one of its grave complications and is strongly associated with dyslipidemia. This investigation sought to delineate renal-specific lipid metabolism-re...

DeepPhosPPI: a deep learning framework with attention-CNN and transformer for predicting phosphorylation effects on protein-protein interactions.

Briefings in bioinformatics
Protein phosphorylation regulates protein function and cellular signaling pathways, and is strongly associated with diseases, including neurodegenerative disorders and cancer. Phosphorylation plays a critical role in regulating protein activity and c...

DeepMobilome: predicting mobile genetic elements using sequencing reads of microbiomes.

Briefings in bioinformatics
MOTIVATION: Mobile genetic elements (MGEs) play an important role in facilitating the acquisition of antibiotic resistance genes (ARGs) within microbial communities, significantly impacting the evolution of antibiotic resistance. Understanding the me...

AlphaFold modeling uncovers global structural features of class I and class II fungal hydrophobins.

Protein science : a publication of the Protein Society
Hydrophobins are a family of small fungal proteins that self-assemble at hydrophobic-hydrophilic interfaces. Hydrophobins not only play crucial roles in filamentous fungal growth and development but also have attracted substantial attention due to th...

Utilizing protein structure graph embeddings to predict the pathogenicity of missense variants.

NAR genomics and bioinformatics
Genetic variants can impact the structure of the corresponding protein, which can have detrimental effects on protein function. While the effect of protein-truncating variants is often easier to evaluate, most genetic variants that affect the protein...

Identification and validation of epithelial‑mesenchymal transition‑related genes for diabetic nephropathy by WGCNA and machine learning.

Molecular medicine reports
Diabetic nephropathy (DN) is the main cause of end‑stage renal disease, with epithelial‑mesenchymal transition (EMT) serving a key role in its initiation and progression. Nevertheless, the precise mechanisms involved remain unidentified. The present ...