AIMC Topic: Computational Biology

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TransST: transfer learning embedded spatial factor modeling of spatial transcriptomics data.

BMC bioinformatics
BACKGROUND: Spatial transcriptomics have emerged as a powerful tool in biomedical research because of its ability to capture both the spatial contexts and abundance of the complete RNA transcript profile in organs of interest. However, limitations of...

A deep learning framework for lysine 2-hydroxyisobutyrylation site prediction using evolutionary feature representation.

Scientific reports
Lysine 2-hydroxyisobutyrylation (Khib) has emerged as a crucial Post-Translational Modification (PTM) with significant roles in diverse biological processes ranging from gene expression to metabolic regulation. Despite its importance, computational a...

TXSelect: A multi-task learning model to identify secretory effectors.

PLoS computational biology
Secretory effectors from pathogenic microorganisms significantly influence pathogen survival and pathogenicity by manipulating host signalling, immune responses, and metabolic processes. However, because of sequence and structural heterogeneity among...

Identification of key genes and regulatory networks associated with atherosclerotic carotid artery stenosis through comprehensive bioinformatics analysis and machine learning.

European journal of medical research
OBJECTIVE: To identify the potential diagnostic biomarkers and therapeutic targets of atherosclerotic carotid artery stenosis (ACAS), a comprehensive bioinformatics analysis was conducted to identify its related key genes and regulatory networks.

A lightweight single-view contrastive learning hypergraph neural network for food-microbe-disease association prediction.

BMC bioinformatics
BACKGROUND: Identifying potential associations among food, gut microbiota and disease is fundamental for elucidating interaction mechanisms and advancing personalized healthy dietary strategies. While computational methods have been extensively appli...

Identified endoplasmic reticulum stress-related molecular cluster and immune characterization in endometriosis.

Scientific reports
Endometriosis is a common disease among women of childbearing age, and endoplasmic reticulum stress (ERS), a response involved in regulating protein homeostasis, has been linked to its pathogenesis. To identify ERS-related hub genes, this study seque...

From sequence to scaffold: Computational design of protein nanoparticle vaccines from AlphaFold2-predicted building blocks.

Proceedings of the National Academy of Sciences of the United States of America
Self-assembling protein nanoparticles are being increasingly utilized in the design of next-generation vaccines due to their ability to induce antibody responses of superior magnitude, breadth, and durability. Computational protein design offers a ro...

AFPDeepPred: A Deep Learning Framework for Accurate Identification of Antifreeze Proteins.

Journal of chemical information and modeling
Antifreeze proteins (AFPs) are essential for the survival of organisms in subzero environments and have significant potential in biomedical and agricultural applications. However, their high sequence diversity poses a significant challenge for accura...

A robust deep learning framework for RNA 5-methyluridine modification prediction using integrated features.

BMC biology
BACKGROUND: The discovery of RNA 5-methyluridine (m5U) modifications is vital in computational biology due to their essential significance in different biological processes. This study presents a powerful predictor named 5-meth-Uri, which improves th...

A novel modality contribution confidence-enhanced multimodal deep learning framework for multiomics data.

BMC bioinformatics
Multimodal learning for classification tasks has recently gained significant attention in bioinformatics. Current approaches primarily concentrate on devising efficient deep learning architectures to capture features within and across modalities. How...