Recent advances in machine learning-based models for prediction of antiviral peptides
Viruses have killed and infected millions of people across the world. It causes several
chronic diseases like COVID-19, HIV, and hepatitis. To cope with such diseases and virus …
chronic diseases like COVID-19, HIV, and hepatitis. To cope with such diseases and virus …
Deepstacked-AVPs: predicting antiviral peptides using tri-segment evolutionary profile and word embedding based multi-perspective features with deep stacking …
Background Viral infections have been the main health issue in the last decade. Antiviral
peptides (AVPs) are a subclass of antimicrobial peptides (AMPs) with substantial potential to …
peptides (AVPs) are a subclass of antimicrobial peptides (AMPs) with substantial potential to …
Prediction of amyloid proteins using embedded evolutionary & ensemble feature selection based descriptors with eXtreme gradient boosting model
Amyloid proteins (AMYs) are usually an aggregate of insoluble fibrous that have major
pathogenic effects on various tissues. However, its abnormal deposition may lead to several …
pathogenic effects on various tissues. However, its abnormal deposition may lead to several …
A bi-layer model for identification of piwiRNA using deep neural learning
Abstract piwiRNA is a kind of non-coding RNA (ncRNA) that cannot be translated into
proteins. It helps in understanding the study of gametes generation and regulation of gene …
proteins. It helps in understanding the study of gametes generation and regulation of gene …
Machine learning-based model for accurate identification of druggable proteins using light extreme gradient boosting
The identification of druggable proteins (DPs) is significant for the development of new
drugs, personalized medicine, understanding of disease mechanisms, drug repurposing …
drugs, personalized medicine, understanding of disease mechanisms, drug repurposing …
Leveraging a meta-learning approach to advance the accuracy of Nav blocking peptides prediction
The voltage-gated sodium (Nav) channel is a crucial molecular component responsible for
initiating and propagating action potentials. While the α subunit, forming the channel pore …
initiating and propagating action potentials. While the α subunit, forming the channel pore …
Accurate Prediction of Antifreeze Protein from Sequences through Natural Language Text Processing and Interpretable Machine Learning Approaches
Antifreeze proteins (AFPs) bind to growing iceplanes owing to their structural
complementarity nature, thereby inhibiting the ice-crystal growth by thermal hysteresis …
complementarity nature, thereby inhibiting the ice-crystal growth by thermal hysteresis …
FRP-XGBoost: Identification of ferroptosis-related proteins based on multi-view features
L Lin, Y Long, J Liu, D Deng, Y Yuan, L Liu… - International Journal of …, 2024 - Elsevier
Ferroptosis represents a novel form of programmed cell death. Pan-cancer bioinformatics
analysis indicates that identifying and modulating ferroptosis offer innovative approaches for …
analysis indicates that identifying and modulating ferroptosis offer innovative approaches for …
DPI_CDF: druggable protein identifier using cascade deep forest
Background Drug targets in living beings perform pivotal roles in the discovery of potential
drugs. Conventional wet-lab characterization of drug targets is although accurate but …
drugs. Conventional wet-lab characterization of drug targets is although accurate but …
An ensemble computational model for prediction of clathrin protein by coupling machine learning with discrete cosine transform
Clathrin protein (CP) plays a pivotal role in numerous cellular processes, including
endocytosis, signal transduction, and neuronal function. Dysregulation of CP has been …
endocytosis, signal transduction, and neuronal function. Dysregulation of CP has been …