Machine learning SNP based prediction for precision medicine
In the past decade, precision genomics based medicine has emerged to provide tailored
and effective healthcare for patients depending upon their genetic features. Genome Wide …
and effective healthcare for patients depending upon their genetic features. Genome Wide …
Application of artificial intelligence and machine learning for COVID-19 drug discovery and vaccine design
The global pandemic of coronavirus disease 2019 (COVID-19), caused by severe acute
respiratory syndrome coronavirus 2, has led to a dramatic loss of human life worldwide …
respiratory syndrome coronavirus 2, has led to a dramatic loss of human life worldwide …
Pse-in-One: a web server for generating various modes of pseudo components of DNA, RNA, and protein sequences
B Liu, F Liu, X Wang, J Chen, L Fang… - Nucleic acids …, 2015 - academic.oup.com
With the avalanche of biological sequences generated in the post-genomic age, one of the
most challenging problems in computational biology is how to effectively formulate the …
most challenging problems in computational biology is how to effectively formulate the …
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 …
BioSeq-Analysis: a platform for DNA, RNA and protein sequence analysis based on machine learning approaches
B Liu - Briefings in bioinformatics, 2019 - academic.oup.com
With the avalanche of biological sequences generated in the post-genomic age, one of the
most challenging problems is how to computationally analyze their structures and functions …
most challenging problems is how to computationally analyze their structures and functions …
A novel features ranking metric with application to scalable visual and bioinformatics data classification
Coming with the big data era, the filtering of uninformative data becomes emerging. To this
end, ranking the high dimensionality features plays an important role. However, most of the …
end, ranking the high dimensionality features plays an important role. However, most of the …
Inferring microRNA-disease associations by random walk on a heterogeneous network with multiple data sources
Since the discovery of the regulatory function of microRNA (miRNA), increased attention has
focused on identifying the relationship between miRNA and disease. It has been suggested …
focused on identifying the relationship between miRNA and disease. It has been suggested …
Prediction of human protein subcellular localization using deep learning
Protein subcellular localization (PSL), as one of the most critical characteristics of human
cells, plays an important role for understanding specific functions and biological processes …
cells, plays an important role for understanding specific functions and biological processes …
Improved prediction of protein–protein interactions using novel negative samples, features, and an ensemble classifier
Computational methods are employed in bioinformatics to predict protein–protein
interactions (PPIs). PPIs and protein–protein non-interactions (PPNIs) display different levels …
interactions (PPIs). PPIs and protein–protein non-interactions (PPNIs) display different levels …
Finding the best classification threshold in imbalanced classification
Classification with imbalanced class distributions is a major problem in machine learning.
Researchers have given considerable attention to the applications in many real-world …
Researchers have given considerable attention to the applications in many real-world …