AIMC Topic: Computational Biology
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Identification and validation of the nicotine metabolism-related signature of bladder cancer by bioinformatics and machine learning.
Frontiers in immunology
Dec 17, 2024
BACKGROUND: Several studies indicate that smoking is one of the major risk factors for bladder cancer. Nicotine and its metabolites, the main components of tobacco, have been found to be strongly linked to the occurrence and progression of bladder ca...
SpatialCVGAE: Consensus Clustering Improves Spatial Domain Identification of Spatial Transcriptomics Using VGAE.
Interdisciplinary sciences, computational life sciences
Dec 16, 2024
The advent of spatially resolved transcriptomics (SRT) has provided critical insights into the spatial context of tissue microenvironments. Spatial clustering is a fundamental aspect of analyzing spatial transcriptomics data. However, spatial cluster...
Subspace learning using low-rank latent representation learning and perturbation theorem: Unsupervised gene selection.
Computers in biology and medicine
Dec 14, 2024
In recent years, gene expression data analysis has gained growing significance in the fields of machine learning and computational biology. Typically, microarray gene datasets exhibit a scenario where the number of features exceeds the number of samp...
Fuzzy-Based Identification of Transition Cells to Infer Cell Trajectory for Single-Cell Transcriptomics.
Journal of computational biology : a journal of computational molecular cell biology
Dec 13, 2024
With the continuous evolution of single-cell RNA sequencing technology, it has become feasible to reconstruct cell development processes using computational methods. Trajectory inference is a crucial downstream analytical task that provides valuable ...
Adapting to time: Why nature may have evolved a diverse set of neurons.
PLoS computational biology
Dec 13, 2024
Brains have evolved diverse neurons with varying morphologies and dynamics that impact temporal information processing. In contrast, most neural network models use homogeneous units that vary only in spatial parameters (weights and biases). To explor...
Neural networks with optimized single-neuron adaptation uncover biologically plausible regularization.
PLoS computational biology
Dec 13, 2024
Neurons in the brain have rich and adaptive input-output properties. Features such as heterogeneous f-I curves and spike frequency adaptation are known to place single neurons in optimal coding regimes when facing changing stimuli. Yet, it is still u...
Advanced vision transformers and open-set learning for robust mosquito classification: A novel approach to entomological studies.
PLoS computational biology
Dec 13, 2024
Mosquito-related diseases pose a significant threat to global public health, necessitating efficient and accurate mosquito classification for effective surveillance and control. This work presents an innovative approach to mosquito classification by ...
Identification and verification of the optimal feature genes of ferroptosis in thyroid-associated orbitopathy.
Frontiers in immunology
Dec 13, 2024
BACKGROUND: Thyroid-associated orbitopathy (TAO) is an autoimmune inflammatory disorder of the orbital adipose tissue, primarily causing oxidative stress injury and tissue remodeling in the orbital connective tissue. Ferroptosis is a form of programm...
S-PLM: Structure-Aware Protein Language Model via Contrastive Learning Between Sequence and Structure.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Dec 12, 2024
Proteins play an essential role in various biological and engineering processes. Large protein language models (PLMs) present excellent potential to reshape protein research by accelerating the determination of protein functions and the design of pro...
Novel machine learning model for predicting cancer drugs' susceptibilities and discovering novel treatments.
Journal of biomedical informatics
Dec 12, 2024
BACKGROUND AND OBJECTIVE: Timely treatment is crucial for cancer patients, so it's important to administer the appropriate treatment as soon as possible. Because individuals can respond differently to a given drug due to their unique genomic profiles...
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