AIMC Topic: Computational Biology
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PredIDR: Accurate prediction of protein intrinsic disorder regions using deep convolutional neural network.
International journal of biological macromolecules
Nov 19, 2024
The involvement of protein intrinsic disorder in essential biological processes, it is well known in structural biology. However, experimental methods for detecting intrinsic structural disorder and directly measuring highly dynamic behavior of prote...
DeepKlapred: A deep learning framework for identifying protein lysine lactylation sites via multi-view feature fusion.
International journal of biological macromolecules
Nov 19, 2024
Lysine lactylation (Kla) is a post-translational modification (PTM) that holds significant importance in the regulation of various biological processes. While traditional experimental methods are highly accurate for identifying Kla sites, they are bo...
Deep-m5U: a deep learning-based approach for RNA 5-methyluridine modification prediction using optimized feature integration.
BMC bioinformatics
Nov 19, 2024
BACKGROUND: RNA 5-methyluridine (m5U) modifications play a crucial role in biological processes, making their accurate identification a key focus in computational biology. This paper introduces Deep-m5U, a robust predictor designed to enhance the pre...
Targeting bioinformatics tools to study the dissemination and spread of antibiotic resistant genes in the environment and clinical settings.
Critical reviews in microbiology
Nov 18, 2024
Antibiotic resistance has expanded as a result of the careless use of antibiotics in the medical field, the food industry, agriculture, and other industries. By means of genetic recombination between commensal and pathogenic bacteria, the microbes ob...
Rapid prediction of key residues for foldability by machine learning model enables the design of highly functional libraries with hyperstable constrained peptide scaffolds.
PLoS computational biology
Nov 18, 2024
Peptides are an emerging modality for developing therapeutics that can either agonize or antagonize cellular pathways associated with disease, yet peptides often suffer from poor chemical and physical stability, which limits their potential. However,...
Simplified internal models in human control of complex objects.
PLoS computational biology
Nov 18, 2024
Humans are skillful at manipulating objects that possess nonlinear underactuated dynamics, such as clothes or containers filled with liquids. Several studies suggested that humans implement a predictive model-based strategy to control such objects. H...
DMHGNN: Double multi-view heterogeneous graph neural network framework for drug-target interaction prediction.
Artificial intelligence in medicine
Nov 17, 2024
Accurate identification of drug-target interactions (DTIs) plays a crucial role in drug discovery. Compared with traditional experimental methods that are labor-intensive and time-consuming, computational methods for drug-target interactions predicti...
Predicting the effects of drugs and unveiling their mechanisms of action using an interpretable pharmacodynamic mechanism knowledge graph (IPM-KG).
Computers in biology and medicine
Nov 17, 2024
BACKGROUND: Multiple studies have aimed to consolidate drug-related data and predict drug effects. However, most of these studies have focused on integrating diverse data through correlation rather than representing them based on the pharmacodynamic ...
SDC4 protein action and related key genes in nonhealing diabetic foot ulcers based on bioinformatics analysis and machine learning.
International journal of biological macromolecules
Nov 17, 2024
Diabetic foot ulcers (DFU) is a complication associated with diabetes characterised by high morbidity, disability, and mortality, involving chronic inflammation and infiltration of multiple immune cells. We aimed to identify the critical genes in non...
RAEPI: Predicting Enhancer-Promoter Interactions Based on Restricted Attention Mechanism.
Interdisciplinary sciences, computational life sciences
Nov 15, 2024
Enhancer-promoter interactions (EPIs) are crucial in gene transcription regulation and cell differentiation. Traditional biological experiments are costly and time-consuming, motivating the development of computational prediction methods. However, ex...
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