AIMC Topic: Computational Biology

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Using a multi-strain infectious disease model with physical information neural networks to study the time dependence of SARS-CoV-2 variants of concern.

PLoS computational biology Feb 14, 2025
With the ongoing evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its increasing adaptation to humans, several variants of concern (VOCs) and variants of interest (VOIs) have been identified since late 2020. These include...
British Columbia Humans Neural Networks, Computer COVID-19 Algorithms Computer Simulation SARS-CoV-2 Computational Biology Models, Biological
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Simpler Protein Domain Identification Using Spectral Clustering.

Proteins Feb 13, 2025
The decomposition of a biomolecular complex into domains is an important step to investigate biological functions and ease structure determination. A successful approach to do so is the SPECTRUS algorithm, which provides a segmentation based on spect...
Cluster Analysis Proteins Databases, Protein Protein Conformation Algorithms Sequence Alignment Deep Learning Sequence Analysis, Protein Computational Biology Models, Molecular Protein Domains Amino Acid Sequence
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A Perspective on Artificial Intelligence for Molecular Pathologists.

The Journal of molecular diagnostics : JMD Feb 13, 2025
The widespread adoption of next-generation sequencing technology in molecular pathology has enabled us to interrogate the genome as never before. The huge quantities of data generated by sequencing, the enormous complexity of human and microbial gene...
High-Throughput Nucleotide Sequencing Pathology, Molecular Humans Machine Learning Artificial Intelligence Computational Biology Pathologists
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PhageDPO: A machine-learning based computational framework for identifying phage depolymerases.

Computers in biology and medicine Feb 13, 2025
Bacteriophages (phages) are the most predominant and genetically diverse biological entities on Earth. Phages are viruses that infect bacteria and encode numerous proteins with potential biotechnological application. However, most phage-encoded prote...
Viral Proteins Genome, Viral Machine Learning Software Bacteriophages Computational Biology Support Vector Machine
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scCobra allows contrastive cell embedding learning with domain adaptation for single cell data integration and harmonization.

Communications biology Feb 13, 2025
The rapid advancement of single-cell technologies has created an urgent need for effective methods to integrate and harmonize single-cell data. Technical and biological variations across studies complicate data integration, while conventional tools o...
Single-Cell Analysis Computational Biology Neural Networks, Computer Software Deep Learning Humans
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Reliability-enhanced data cleaning in biomedical machine learning using inductive conformal prediction.

PLoS computational biology Feb 13, 2025
Accurately labeling large datasets is important for biomedical machine learning yet challenging while modern data augmentation methods may generate noise in the training data, which may deteriorate machine learning model performance. Existing approac...
Computational Biology Reproducibility of Results SARS-CoV-2 Breast Neoplasms Electronic Health Records Female Humans Machine Learning COVID-19 Algorithms
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Early detection of disease outbreaks and non-outbreaks using incidence data: A framework using feature-based time series classification and machine learning.

PLoS computational biology Feb 13, 2025
Forecasting the occurrence and absence of novel disease outbreaks is essential for disease management, yet existing methods are often context-specific, require a long preparation time, and non-outbreak prediction remains understudied. To address this...
ROC Curve Computational Biology Singapore Disease Outbreaks Incidence Humans Machine Learning COVID-19 Forecasting SARS-CoV-2
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Self-supervised machine learning methods for protein design improve sampling but not the identification of high-fitness variants.

Science advances Feb 12, 2025
Machine learning (ML) is changing the world of computational protein design, with data-driven methods surpassing biophysical-based methods in experimental success. However, they are most often reported as case studies, lack integration and standardiz...
Computational Biology Proteins Models, Molecular Mutation Supervised Machine Learning Protein Engineering Machine Learning Software Algorithms
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A multi-classification deep neural network for cancer type identification from high-dimension, small-sample and imbalanced gene microarray data.

Scientific reports Feb 12, 2025
Gene microarray technology provides an efficient way to diagnose cancer. However, microarray gene expression data face the challenges of high-dimension, small-sample, and multi-class imbalance. The coupling of these challenges leads to inaccurate res...
Neoplasms Gene Expression Profiling Computational Biology Humans Neural Networks, Computer Algorithms Databases, Genetic Oligonucleotide Array Sequence Analysis
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Molecular structure of NRG-1 protein and its impact on adult hypertension and heart failure: A new clinical Indicator diagnosis based on advanced machine learning.

International journal of biological macromolecules Feb 11, 2025
The purpose of this study was to investigate the molecular structure of NRG-1 protein and its mechanism of action in adult hypertensive heart failure. The amino acid sequence of NRG-1 protein was analyzed by bioinformatics method. High-throughput seq...
Humans Machine Learning Biomarkers Female Heart Failure Neuregulin-1 Computational Biology Adult Hypertension Male Mutation Middle Aged
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