Gene set analysis, a popular approach for analyzing high-throughput gene...
As the availability of omics data has increased in the last few years, m...
Programming is ubiquitous in applied biostatistics; adopting software
en...
Although the biostatistical scientific literature publishes new methods ...
The constant development of new data analysis methods in many fields of
...
Most machine learning algorithms are configured by one or several
hyperp...
In recent years, the need for neutral benchmark studies that focus on th...
Cluster analysis refers to a wide range of data analytic techniques for ...
Multi-omics data, that is, datasets containing different types of
high-d...
The random forest algorithm (RF) has several hyperparameters that have t...
Modern machine learning algorithms for classification or regression such...
The number of trees T in the random forest (RF) algorithm for supervised...
In a context where most published articles are devoted to the developmen...