AIMC Topic: Computational Biology

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MvGraphDTA: multi-view-based graph deep model for drug-target affinity prediction by introducing the graphs and line graphs.

BMC biology Aug 26, 2024
BACKGROUND: Accurately identifying drug-target affinity (DTA) plays a pivotal role in drug screening, design, and repurposing in pharmaceutical industry. It not only reduces the time, labor, and economic costs associated with biological experiments b...
Deep Learning Drug Discovery Computational Biology Pharmaceutical Preparations
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MAGICAL: A multi-class classifier to predict synthetic lethal and viable interactions using protein-protein interaction network.

PLoS computational biology Aug 26, 2024
Synthetic lethality (SL) and synthetic viability (SV) are commonly studied genetic interactions in the targeted therapy approach in cancer. In SL, inhibiting either of the genes does not affect the cancer cell survival, but inhibiting both leads to a...
Protein Interaction Maps Computational Biology Humans Algorithms Machine Learning Neoplasms Synthetic Lethal Mutations
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Regression convolutional neural network models implicate peripheral immune regulatory variants in the predisposition to Alzheimer's disease.

PLoS computational biology Aug 26, 2024
Alzheimer's disease (AD) involves aggregation of amyloid β and tau, neuron loss, cognitive decline, and neuroinflammatory responses. Both resident microglia and peripheral immune cells have been associated with the immune component of AD. However, th...
Alzheimer Disease Microglia Neurons Neural Networks, Computer Humans Genetic Predisposition to Disease Computational Biology
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Benchmarking the negatives: Effect of negative data generation on the classification of miRNA-mRNA interactions.

PLoS computational biology Aug 26, 2024
MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression post-transcriptionally. In animals, this regulation is achieved via base-pairing with partially complementary sequences on mainly 3' UTR region of messenger RNAs (mRNAs). Comp...
Machine Learning Algorithms Benchmarking Animals Humans RNA, Messenger Computational Biology MicroRNAs
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Res-GCN: Identification of protein phosphorylation sites using graph convolutional network and residual network.

Computational biology and chemistry Aug 24, 2024
An essential post-translational modification, phosphorylation is intimately related with a wide range of biological activities. The advancement of effective computational methods for correctly recognizing phosphorylation sites is important for in-dep...
Protein Processing, Post-Translational SARS-CoV-2 Humans Phosphorylation Computational Biology Neural Networks, Computer
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Smccnet 2.0: a comprehensive tool for multi-omics network inference with shiny visualization.

BMC bioinformatics Aug 24, 2024
Sparse multiple canonical correlation network analysis (SmCCNet) is a machine learning technique for integrating omics data along with a variable of interest (e.g., phenotype of complex disease), and reconstructing multi-omics networks that are speci...
Multiomics Genomics Computational Biology Software Gene Regulatory Networks Humans Machine Learning
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MSH-DTI: multi-graph convolution with self-supervised embedding and heterogeneous aggregation for drug-target interaction prediction.

BMC bioinformatics Aug 23, 2024
BACKGROUND: The rise of network pharmacology has led to the widespread use of network-based computational methods in predicting drug target interaction (DTI). However, existing DTI prediction models typically rely on a limited amount of data to extra...
Network Pharmacology Deep Learning Computational Biology Supervised Machine Learning
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aiSEGcell: User-friendly deep learning-based segmentation of nuclei in transmitted light images.

PLoS computational biology Aug 23, 2024
Segmentation is required to quantify cellular structures in microscopic images. This typically requires their fluorescent labeling. Convolutional neural networks (CNNs) can detect these structures also in only transmitted light images. This eliminate...
Computational Biology Cell Nucleus Animals Neural Networks, Computer Deep Learning Image Processing, Computer-Assisted Software Humans Mice
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PhosBERT: A self-supervised learning model for identifying phosphorylation sites in SARS-CoV-2-infected human cells.

Methods (San Diego, Calif.) Aug 22, 2024
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a single-stranded RNA virus, which mainly causes respiratory and enteric diseases and is responsible for the outbreak of coronavirus disease 19 (COVID-19). Numerous studies have demonstr...
Neural Networks, Computer COVID-19 Humans Computational Biology Protein Processing, Post-Translational Phosphorylation SARS-CoV-2 Spike Glycoprotein, Coronavirus Supervised Machine Learning
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StackDPPred: Multiclass prediction of defensin peptides using stacked ensemble learning with optimized features.

Methods (San Diego, Calif.) Aug 22, 2024
Host defense or antimicrobial peptides (AMPs) are promising candidates for protecting host against microbial pathogens for example bacteria, virus, fungi, yeast. Defensins are the type of AMPs that act as potential therapeutic drug agent and perform ...
Machine Learning Algorithms Defensins Amino Acid Sequence Position-Specific Scoring Matrices Computational Biology Principal Component Analysis
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