In data analysis and machine learning practice, "dimensionality reduction" is an essential technique for visualizing high-dimensional data and as a preprocessing step for clustering. Representative ...

MOFA is a factor analysis model that provides a general framework for the integration of multi-omic data sets in a completely unsupervised fashion. Intuitively, MOFA can be viewed as a versatile and ...

Artificial intelligence is rapidly changing the job market, automating jobs across industries. Therefore, in such a scenario, upskilling oneself in industry-relevant AI skills becomes even more ...

Mass spectrometry-based lipidomics and metabolomics generate extensive data sets that, along with metadata such as clinical parameters, require specific data exploration skills to identify and ...

Guangxi Colleges and Universities Key Laboratory of Data Analysis and Computation, College of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin, China. With the ...

Orange Data Mining is a Python based visual programming software that has been used widely in many scientific publications. Principal component analysis (PCA) is one of the most common exploratory ...

We describe OHBA Software Library for the analysis of electrophysiology data (osl-ephys). This toolbox builds on top of the widely used MNE-Python package and provides unique analysis tools for ...

The rise of artificial intelligence (AI) deep learning algorithms is helping to accelerate brain-computer interfaces (BCIs). Published in this month’s Nature Neuroscience is new research that shows ...

In the dynamic scene of Python development, understanding the qualification between frameworks and libraries is pivotal for extended success. Python frameworks give structure and support for building ...

Transforming a dataset into one with fewer columns is more complicated than it might seem, explains Dr. James McCaffrey of Microsoft Research in this full-code, step-by-step machine learning tutorial.