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 …
IoMT-Based Healthcare Systems: A Review.
The integration of the Internet of Medical Things (IoMT) and the Internet of Things (IoT),
which has revolutionized patient care through features like remote critical care and real-time …
which has revolutionized patient care through features like remote critical care and real-time …
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 …
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 …
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 …
IP-GCN: A deep learning model for prediction of insulin using graph convolutional network for diabetes drug design
Insulin is a kind of protein that regulates the blood sugar levels is significant to prevent
complications associated with diabetes, such as cancer, neurodegenerative disorders …
complications associated with diabetes, such as cancer, neurodegenerative disorders …
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 …
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 …
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 …