AIMC Topic: Computational Biology
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Exploring deep learning in phage discovery and characterization.
Virology
Apr 29, 2025
Bacteriophages, or bacterial viruses, play diverse ecological roles by shaping bacterial populations and also hold significant biotechnological and medical potential, including the treatment of infections caused by multidrug-resistant bacteria. The d...
Machine learning: Python tools for studying biomolecules and drug design.
Molecular diversity
Apr 29, 2025
The increasing adoption of computational methods and artificial intelligence in scientific research has led to a growing interest in versatile tools like Python. In the fields of medical chemistry, biochemistry, and bioinformatics, Python has emerged...
Identification of M2 macrophage-related genes associated with diffuse large B-cell lymphoma via bioinformatics and machine learning approaches.
Biology direct
Apr 29, 2025
M2 macrophages play a crucial role in the initiation and progression of various tumors, including diffuse large B-cell lymphoma (DLBCL). However, the characterization of M2 macrophage-related genes in DLBCL remains incomplete. In this study, we downl...
Multifractal analysis and support vector machine for the classification of coronaviruses and SARS-CoV-2 variants.
Scientific reports
Apr 29, 2025
This study presents a novel approach for the classification of coronavirus species and variants of SARS-CoV-2 using Chaos Game Representation (CGR) and 2D Multifractal Detrended Fluctuation Analysis (2D MF-DFA). By extracting fractal parameters from ...
Identification and Validation of Glycosylation‑Related Genes in Ischemic Stroke Based on Bioinformatics and Machine Learning.
Journal of molecular neuroscience : MN
Apr 29, 2025
Ischemic stroke (IS) constitutes a severe neurological disorder with restricted treatment alternatives. Recent investigations have disclosed that glycosylation is closely associated with the occurrence and outcome of IS. Nevertheless, data on the tra...
VTrans: A VAE-Based Pre-Trained Transformer Method for Microbiome Data Analysis.
Journal of computational biology : a journal of computational molecular cell biology
Apr 28, 2025
Predicting the survival outcomes and assessing the risk of patients play a pivotal role in comprehending the microbial composition across various stages of cancer. With the ongoing advancements in deep learning, it has been substantiated that deep le...
[Nobel Prize in chemistry 2024: David Baker, Demis Hassabis et John M. Jumper. The revolution of artificial intelligence in structural biology].
Medecine sciences : M/S
Apr 28, 2025
The 2024 Nobel Prize in chemistry has been awarded to Demis Hassabis and John M. Jumper (Google DeepMind) for the development of artificial intelligence-guided protein structure prediction and to David Baker (University of Washington, Seattle, USA) f...
Unlocking the soundscape of coral reefs with artificial intelligence: pretrained networks and unsupervised learning win out.
PLoS computational biology
Apr 28, 2025
Passive acoustic monitoring can offer insights into the state of coral reef ecosystems at low-costs and over extended temporal periods. Comparison of whole soundscape properties can rapidly deliver broad insights from acoustic data, in contrast to de...
Multiscale insights into cornuside's effects on NAFLD: A cross-disciplinary integrating bioinformatics, computational chemistry, and machine learning.
Phytomedicine : international journal of phytotherapy and phytopharmacology
Apr 26, 2025
BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is a complex metabolic disorder involving intertwined signaling pathways, posing challenges for targeted therapeutic interventions. Cornus Fructus (CF), a traditional medicinal herb, holds potenti...
ScAGCN: Graph Convolutional Network with Adaptive Aggregation Mechanism for scRNA-seq Data Dimensionality Reduction.
Interdisciplinary sciences, computational life sciences
Apr 25, 2025
With the development of single-cell RNA-sequencing (scRNA-seq) technology, scRNA-seq data analysis suffers huge challenges due to large scale, high dimensionality, high noise, and high sparsity. To achieve accurately embedded representation in the la...
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