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 …
AIPs-SnTCN: Predicting anti-inflammatory peptides using fastText and transformer encoder-based hybrid word embedding with self-normalized temporal …
Inflammation is a biologically resistant response to harmful stimuli, such as infection,
damaged cells, toxic chemicals, or tissue injuries. Its purpose is to eradicate pathogenic …
damaged cells, toxic chemicals, or tissue injuries. Its purpose is to eradicate pathogenic …
Comparative analysis of the existing methods for prediction of antifreeze proteins
Antifreeze proteins (AFPs) are found in different living organisms like plants, insects, and
fish. AFPs avoid the formation of ice crystals in these organisms and make them able to …
fish. AFPs avoid the formation of ice crystals in these organisms and make them able to …
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 …
AFP-SPTS: an accurate prediction of antifreeze proteins using sequential and pseudo-tri-slicing evolutionary features with an extremely randomized tree
The development of intracellular ice in the bodies of cold-blooded living organisms may
cause them to die. These species yield antifreeze proteins (AFPs) to live in subzero …
cause them to die. These species yield antifreeze proteins (AFPs) to live in subzero …
DBP-DeepCNN: prediction of DNA-binding proteins using wavelet-based denoising and deep learning
DNA-binding proteins (DBPs) are highly concerned with several types of cancers (lung,
breast, and liver), other fatal diseases (AIDS/HIV, asthma), and are used in the designing of …
breast, and liver), other fatal diseases (AIDS/HIV, asthma), and are used in the designing of …
Prediction of antifreeze proteins using machine learning
Living organisms including fishes, microbes, and animals can live in extremely cold weather.
To stay alive in cold environments, these species generate antifreeze proteins (AFPs), also …
To stay alive in cold environments, these species generate antifreeze proteins (AFPs), also …
Target-DBPPred: an intelligent model for prediction of DNA-binding proteins using discrete wavelet transform based compression and light eXtreme gradient boosting
DNA-protein interaction is a critical biological process that performs influential activities,
including DNA transcription and recombination. DBPs (DNA-binding proteins) are closely …
including DNA transcription and recombination. DBPs (DNA-binding proteins) are closely …
Deep-AGP: Prediction of angiogenic protein by integrating two-dimensional convolutional neural network with discrete cosine transform
Angiogenic proteins (AGPs) play a primary role in the formation of new blood vessels from
pre-existing ones. AGPs have diverse applications in cancer, including serving as …
pre-existing ones. AGPs have diverse applications in cancer, including serving as …
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 …