A first computational frame for recognizing heparin-binding protein
W Zhu, SS Yuan, J Li, CB Huang, H Lin, B Liao - Diagnostics, 2023 - mdpi.com
Heparin-binding protein (HBP) is a cationic antibacterial protein derived from multinuclear
neutrophils and an important biomarker of infectious diseases. The correct identification of …
neutrophils and an important biomarker of infectious diseases. The correct identification of …
Accurately identifying hemagglutinin using sequence information and machine learning methods
Introduction Hemagglutinin (HA) is responsible for facilitating viral entry and infection by
promoting the fusion between the host membrane and the virus. Given its significance in the …
promoting the fusion between the host membrane and the virus. Given its significance in the …
HLPpred-Fuse: improved and robust prediction of hemolytic peptide and its activity by fusing multiple feature representation
Motivation Therapeutic peptides failing at clinical trials could be attributed to their toxicity
profiles like hemolytic activity, which hamper further progress of peptides as drug …
profiles like hemolytic activity, which hamper further progress of peptides as drug …
Prediction of interactions between viral and host proteins using supervised machine learning methods
Background Viral-host protein-protein interaction plays a vital role in pathogenesis, since it
defines viral infection of the host and regulation of the host proteins. Identification of key viral …
defines viral infection of the host and regulation of the host proteins. Identification of key viral …
Sequence based prediction of DNA-binding proteins based on hybrid feature selection using random forest and Gaussian naive Bayes
W Lou, X Wang, F Chen, Y Chen, B Jiang, H Zhang - PloS one, 2014 - journals.plos.org
Developing an efficient method for determination of the DNA-binding proteins, due to their
vital roles in gene regulation, is becoming highly desired since it would be invaluable to …
vital roles in gene regulation, is becoming highly desired since it would be invaluable to …
AMPDeep: hemolytic activity prediction of antimicrobial peptides using transfer learning
Background Deep learning's automatic feature extraction has proven to give superior
performance in many sequence classification tasks. However, deep learning models …
performance in many sequence classification tasks. However, deep learning models …
[PDF][PDF] Identification of hormone binding proteins based on machine learning methods
JX Tan, SH Li, ZM Zhang, CX Chen, W Chen… - Math. Biosci …, 2019 - aimspress.com
The soluble carrier hormone binding protein (HBP) plays an important role in the growth of
human and other animals. HBP can also selectively and non-covalently interact with …
human and other animals. HBP can also selectively and non-covalently interact with …
A web server and mobile app for computing hemolytic potency of peptides
Numerous therapeutic peptides do not enter the clinical trials just because of their high
hemolytic activity. Recently, we developed a database, Hemolytik, for maintaining …
hemolytic activity. Recently, we developed a database, Hemolytik, for maintaining …
[HTML][HTML] Pred-BVP-Unb: Fast prediction of bacteriophage Virion proteins using un-biased multi-perspective properties with recursive feature elimination
Bacteriophage virion proteins (BVPs) are bacterial viruses that have a great impact on
different biological functions of bacteria. They are significantly used in genetic engineering …
different biological functions of bacteria. They are significantly used in genetic engineering …
Optimizing classification efficiency with machine learning techniques for pattern matching
The study proposes a novel model for DNA sequence classification that combines machine
learning methods and a pattern-matching algorithm. This model aims to effectively …
learning methods and a pattern-matching algorithm. This model aims to effectively …