AIMC Topic: Computational Biology

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ZeRPI: A graph neural network model for zero-shot prediction of RNA-protein interactions.

Methods (San Diego, Calif.) Jan 30, 2025
RNA-protein interactions are crucial for biological functions across multiple levels. RNA binding proteins (RBPs) intricately engage in diverse biological processes through specific RNA molecule interactions. Previous studies have revealed the indisp...
Protein Binding Humans Computational Biology Neural Networks, Computer RNA Machine Learning Graph Neural Networks Algorithms RNA-Binding Proteins
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Optimized convolutional neural network using African vulture optimization algorithm for the detection of exons.

Scientific reports Jan 30, 2025
The detection of exons is an important area of research in genomic sequence analysis. Many signal-processing methods have been established successfully for detecting the exons based on their periodicity property. However, some improvement is still re...
Algorithms Convolutional Neural Networks Computational Biology Humans Neural Networks, Computer Sequence Analysis, DNA Exons Introns
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ASGCL: Adaptive Sparse Mapping-based graph contrastive learning network for cancer drug response prediction.

PLoS computational biology Jan 30, 2025
Personalized cancer drug treatment is emerging as a frontier issue in modern medical research. Considering the genomic differences among cancer patients, determining the most effective drug treatment plan is a complex and crucial task. In response to...
Humans Machine Learning Precision Medicine Neoplasms Algorithms Antineoplastic Agents Cell Line, Tumor Computational Biology
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Elucidating the role of FBXW4 in osteoporosis: integrating bioinformatics and machine learning for advanced insight.

BMC pharmacology & toxicology Jan 29, 2025
BACKGROUND: Osteoporosis (OP), often termed the "silent epidemic," poses a substantial public health burden. Emerging insights into the molecular functions of FBXW4 have spurred interest in its potential roles across various diseases.
F-Box Proteins Computational Biology Machine Learning Databases, Genetic Osteoporosis Humans
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scSMD: a deep learning method for accurate clustering of single cells based on auto-encoder.

BMC bioinformatics Jan 29, 2025
BACKGROUND: Single-cell RNA sequencing (scRNA-seq) has transformed biological research by offering new insights into cellular heterogeneity, developmental processes, and disease mechanisms. As scRNA-seq technology advances, its role in modern biology...
Sequence Analysis, RNA Cluster Analysis Gene Expression Profiling Deep Learning RNA-Seq Computational Biology Single-Cell Analysis Humans
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The calcitron: A simple neuron model that implements many learning rules via the calcium control hypothesis.

PLoS computational biology Jan 29, 2025
Theoretical neuroscientists and machine learning researchers have proposed a variety of learning rules to enable artificial neural networks to effectively perform both supervised and unsupervised learning tasks. It is not always clear, however, how t...
Humans Neural Networks, Computer Machine Learning Computational Biology Neuronal Plasticity Models, Neurological Learning Animals Synapses Neurons Calcium
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Multimodal learning for mapping genotype-phenotype dynamics.

Nature computational science Jan 28, 2025
How complex phenotypes emerge from intricate gene expression patterns is a fundamental question in biology. Integrating high-content genotyping approaches such as single-cell RNA sequencing and advanced learning methods such as language models offers...
Phenotype Genetic Association Studies Gene Expression Profiling Humans Computational Biology Single-Cell Analysis Machine Learning Transcriptome von Willebrand Factor Genotype
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Caps-ac4C: An effective computational framework for identifying N4-acetylcytidine sites in human mRNA based on deep learning.

Journal of molecular biology Jan 28, 2025
N4-acetylcytidine (ac4C) is a crucial post-transcriptional modification in human mRNA, involving the acetylation of the nitrogen atom at the fourth position of cytidine. This modification, catalyzed by N-acetyltransferases such as NAT10, is primarily...
Cytidine Humans Computational Biology RNA Processing, Post-Transcriptional RNA, Messenger Deep Learning
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Modern machine learning methods for protein property prediction.

Current opinion in structural biology Jan 28, 2025
Recent progress and development of artificial intelligence and machine learning (AI/ML) techniques have enabled addressing complex biomolecular problems. AI/ML models learn the underlying distribution of data they are trained on and when exposed to n...
Proteins Machine Learning Protein Conformation Computational Biology
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Alzheimer's disease: an integrative bioinformatics and machine learning analysis reveals glutamine metabolism-associated gene biomarkers.

BMC pharmacology & toxicology Jan 28, 2025
BACKGROUND: Alzheimer's disease (AD), a hallmark of age-related cognitive decline, is defined by its unique neuropathology. Metabolic dysregulation, particularly involving glutamine (Gln) metabolism, has emerged as a critical but underexplored aspect...
Machine Learning Biomarkers Humans Alzheimer Disease Computational Biology Glutamine
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