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Protein–Protein Interaction Network Analysis Using NetworkX
In recent years, extracting information from biological data has become a particularly valuable way of gaining knowledge. Molecular interaction...
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Protein–Protein Interaction Network Exploration Using Cytoscape
As the protein–protein interaction (PPI) data increase exponentially, the development and usage of computational methods to analyze these datasets...
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Using protein language models for protein interaction hot spot prediction with limited data
BackgroundProtein language models, inspired by the success of large language models in deciphering human language, have emerged as powerful tools for...
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Predicting Protein Interaction Sites Using PITHIA
Several proteins work independently, but the majority work together to maintain the functions of the cell. Thus, it is crucial to know the...
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Building Protein–Protein Interaction Graph Database Using Neo4j
A cell’s various components interact with each other in a coordinated manner to respond to environmental cues and intracellular signals. Compared to...
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Protein–protein interaction site prediction by model ensembling with hybrid feature and self-attention
BackgroundProtein–protein interactions (PPIs) are crucial in various biological functions and cellular processes. Thus, many computational approaches...
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Protein–protein interaction and non-interaction predictions using gene sequence natural vector
Predicting protein–protein interaction and non-interaction are two important different aspects of multi-body structure predictions, which provide...
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Protein features fusion using attributed network embedding for predicting protein-protein interaction
BackgroundProtein-protein interactions (PPIs) hold significant importance in biology, with precise PPI prediction as a pivotal factor in...
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xCAPT5: protein–protein interaction prediction using deep and wide multi-kernel pooling convolutional neural networks with protein language model
BackgroundPredicting protein–protein interactions (PPIs) from sequence data is a key challenge in computational biology. While various computational...
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Machine Learning Methods for Virus–Host Protein–Protein Interaction Prediction
The attachment of a virion to a respective cellular receptor on the host organism occurring through the virus–host protein–protein interactions...
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GraphsformerCPI: Graph Transformer for Compound–Protein Interaction Prediction
Accurately predicting compound–protein interactions (CPI) is a critical task in computer-aided drug design. In recent years, the exponential growth...
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DisoFLAG: accurate prediction of protein intrinsic disorder and its functions using graph-based interaction protein language model
Intrinsically disordered proteins and regions (IDPs/IDRs) are functionally important proteins and regions that exist as highly dynamic conformations...
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DL-PPI: a method on prediction of sequenced protein–protein interaction based on deep learning
PurposeSequenced Protein–Protein Interaction (PPI) prediction represents a pivotal area of study in biology, playing a crucial role in elucidating...
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AptaTrans: a deep neural network for predicting aptamer-protein interaction using pretrained encoders
BackgroundAptamers, which are biomaterials comprised of single-stranded DNA/RNA that form tertiary structures, have significant potential as...
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Building, Visualizing, and Analyzing Glycosaminoglycan–Protein Interaction Networks
This chapter describes how to generate, visualize, and analyze interaction networks of glycosaminoglycans (GAGs), which are linear polyanionic...
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LncRNA–protein interaction prediction with reweighted feature selection
LncRNA–protein interactions are ubiquitous in organisms and play a crucial role in a variety of biological processes and complex diseases. Many...
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Identification of the bacteriophage nucleus protein interaction network
In the arms race between bacteria and bacteriophages (phages), some large-genome jumbo phages have evolved a protein shell that encloses their...
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Improved compound–protein interaction site and binding affinity prediction using self-supervised protein embeddings
BackgroundCompound–protein interaction site and binding affinity predictions are crucial for drug discovery and drug design. In recent years, many...
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SDNN-PPI: self-attention with deep neural network effect on protein-protein interaction prediction
BackgroundProtein-protein interactions (PPIs) dominate intracellular molecules to perform a series of tasks such as transcriptional regulation,...
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Computational Methods and Deep Learning for Elucidating Protein Interaction Networks
Protein interactions play a critical role in all biological processes, but experimental identification of protein interactions is a time- and...