AIMC Topic: Algorithms

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An automatic approach for the classification of lumpy skin disease in cattle.

Tropical animal health and production
Lumpy Skin Disease (LSD) presents significant risks and economic challenges to global cattle farming. Effective and accurate classification of LSD is essential for managing the disease and reducing its impacts. Manual diagnosis is time-consuming, lab...

RETINA: Reconstruction-based pre-trained enhanced TransUNet for electron microscopy segmentation on the CEM500K dataset.

PLoS computational biology
Electron microscopy (EM) has revolutionized our understanding of cellular structures at the nanoscale. Accurate image segmentation is required for analyzing EM images. While manual segmentation is reliable, it is labor-intensive, incentivizing the de...

Identification of mitophagy-related biomarkers in severe acute pancreatitis: integration of WGCNA, machine learning algorithms and scRNA-seq.

Frontiers in immunology
BACKGROUND: Mitophagy is a highly conserved cellular process in eukaryotic cells that selectively clears dysfunctional or damaged mitochondria through autophagy mechanisms to maintain mitochondrial homeostasis. However, the role of mitophagy in the p...

Characteristic genes and immune landscape of interstitial cystitis.

PloS one
BACKGROUND: Interstitial cystitis (IC) was still a disease with the exclusive diagnosis and lacked an effective gold standard. It was of great significance to find diagnostic markers for IC. Our study was aimed to screen characteristic genes via mach...

scE2EGAE: enhancing single-cell RNA-Seq data analysis through an end-to-end cell-graph-learnable graph autoencoder with differentiable edge sampling.

Biology direct
BACKGROUND: Single-cell RNA sequencing (scRNA-Seq) technology reveals biological processes and molecular-level genomic information among individual cells. Numerous computational methods, including methods based on graph neural networks (GNNs), have b...

Reliable protein-protein docking with AlphaFold, Rosetta, and replica exchange.

eLife
Despite the recent breakthrough of AlphaFold (AF) in the field of protein sequence-to-structure prediction, modeling protein interfaces and predicting protein complex structures remains challenging, especially when there is a significant conformation...

A new dataset for measuring the performance of blood vessel segmentation methods under distribution shifts.

PloS one
Creating a dataset for training supervised machine learning algorithms can be a demanding task. This is especially true for blood vessel segmentation since one or more specialists are usually required for image annotation, and creating ground truth l...

Image key information processing using convolutional neural network and rotational invariant-hierarchical max pooling algorithm.

PloS one
In the information age, the effectiveness of image processing determines the quality of a large number of image analysis tasks. A fusion algorithm-based processing technique was proposed to process key image information. A feature dictionary was intr...

Hybrid optimization technique for matrix chain multiplication using Strassen's algorithm.

F1000Research
BACKGROUND: Matrix Chain Multiplication (MCM) is a fundamental problem in computational mathematics and computer science, often encountered in scientific computing, graphics, and machine learning. Traditional MCM optimization techniques use Dynamic P...

TaxaCal: enhancing species-level profiling accuracy of 16S amplicon data.

BMC bioinformatics
BACKGROUND: 16S rRNA amplicon sequencing is a widely used method for microbiome composition analysis due to its cost-effectiveness and lower data requirements compared to metagenomic whole-genome sequencing (WGS). However, inherent limitations in 16S...