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 …
[HTML][HTML] XGB-DrugPred: computational prediction of druggable proteins using eXtreme gradient boosting and optimized features set
Accurate identification of drug-targets in human body has great significance for designing
novel drugs. Compared with traditional experimental methods, prediction of drug-targets via …
novel drugs. Compared with traditional experimental methods, prediction of drug-targets via …
[HTML][HTML] Single-stranded DNA binding proteins and their identification using machine learning-based approaches
JT Guo, F Malik - Biomolecules, 2022 - mdpi.com
Single-stranded DNA (ssDNA) binding proteins (SSBs) are critical in maintaining genome
stability by protecting the transient existence of ssDNA from damage during essential …
stability by protecting the transient existence of ssDNA from damage during essential …
Deep-AntiFP: Prediction of antifungal peptides using distanct multi-informative features incorporating with deep neural networks
World widely, Fungal infections have become a serious issue for human beings. Fungal
infections normally happen once invading fungus appear on a specific area of the body and …
infections normally happen once invading fungus appear on a specific area of the body and …
Prediction of antiviral peptides using transform evolutionary & SHAP analysis based descriptors by incorporation with ensemble learning strategy
Viral diseases are a major health concern in the last few years. Antiviral peptides (AVPs)
belong to a type of antimicrobial peptides (AMPs) that have the high potential to defend the …
belong to a type of antimicrobial peptides (AMPs) that have the high potential to defend the …
DBP-CNN: Deep learning-based prediction of DNA-binding proteins by coupling discrete cosine transform with two-dimensional convolutional neural network
To improve the prediction of DNA-binding Proteins (DBPs), this paper presents a deep
learning-based method, named DBP-CNN. To efficiently extract the important features, we …
learning-based method, named DBP-CNN. To efficiently extract the important features, we …
StackACPred: Prediction of anticancer peptides by integrating optimized multiple feature descriptors with stacked ensemble approach
Anticancer peptides (ACPs) have been emerged as a potential safe therapeutic agent for
treating cancer. Identifying novel ACPs is crucial for understanding deep insight their …
treating cancer. Identifying novel ACPs is crucial for understanding deep insight their …
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 …
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 …