Machine learning for drug-target interaction prediction
Identifying drug-target interactions will greatly narrow down the scope of search of candidate
medications, and thus can serve as the vital first step in drug discovery. Considering that in …
medications, and thus can serve as the vital first step in drug discovery. Considering that in …
A brief survey of machine learning methods in protein sub-Golgi localization
Background: The location of proteins in a cell can provide important clues to their functions
in various biological processes. Thus, the application of machine learning method in the …
in various biological processes. Thus, the application of machine learning method in the …
Distance-based support vector machine to predict DNA N6-methyladenine modification
Background: DNA N6-methyladenine plays an important role in the restriction-modification
system to isolate invasion from adventive DNA. The shortcomings of the high time …
system to isolate invasion from adventive DNA. The shortcomings of the high time …
MRMD2. 0: a python tool for machine learning with feature ranking and reduction
S He, F Guo, Q Zou - Current Bioinformatics, 2020 - ingentaconnect.com
Aims: The study aims to find a way to reduce the dimensionality of the dataset. Background:
Dimensionality reduction is the key issue of the machine learning process. It does not only …
Dimensionality reduction is the key issue of the machine learning process. It does not only …
Gene expression value prediction based on XGBoost algorithm
Gene expression profiling has been widely used to characterize cell status to reflect the
health of the body, to diagnose genetic diseases, etc. In recent years, although the cost of …
health of the body, to diagnose genetic diseases, etc. In recent years, although the cost of …
Discovering symptom patterns of COVID-19 patients using association rule mining
Background The COVID-19 pandemic is a significant public health crisis that is hitting hard
on people's health, well-being, and freedom of movement, and affecting the global economy …
on people's health, well-being, and freedom of movement, and affecting the global economy …
A random forest sub-Golgi protein classifier optimized via dipeptide and amino acid composition features
To gain insight into the malfunction of the Golgi apparatus and its relationship to various
genetic and neurodegenerative diseases, the identification of sub-Golgi proteins, both cis …
genetic and neurodegenerative diseases, the identification of sub-Golgi proteins, both cis …
NPI-GNN: Predicting ncRNA–protein interactions with deep graph neural networks
ZA Shen, T Luo, YK Zhou, H Yu… - Briefings in …, 2021 - academic.oup.com
Noncoding RNAs (ncRNAs) play crucial roles in many biological processes. Experimental
methods for identifying ncRNA–protein interactions (NPIs) are always costly and time …
methods for identifying ncRNA–protein interactions (NPIs) are always costly and time …
CPPred-FL: a sequence-based predictor for large-scale identification of cell-penetrating peptides by feature representation learning
Cell-penetrating peptides (CPPs) have been shown to be a transport vehicle for delivering
cargoes into live cells, offering great potential as future therapeutics. It is essential to identify …
cargoes into live cells, offering great potential as future therapeutics. It is essential to identify …
PredT4SE-stack: prediction of bacterial type IV secreted effectors from protein sequences using a stacked ensemble method
Gram-negative bacteria use various secretion systems to deliver their secreted effectors.
Among them, type IV secretion system exists widely in a variety of bacterial species, and …
Among them, type IV secretion system exists widely in a variety of bacterial species, and …