A framework for analyzing single-cell genomics data, in which geometrical properties are harnessed to obtain insights on cellular diversity, including precise clustering, clear visualizations, and ...

The subthalamic nucleus contains subpopulations with different contributions to deliberative decision-making based on noisy evidence and reward-driven preferences.

Abstract: Hierarchical clustering is a method in data mining and statistics used to build a hierarchy of clusters. Traditional hierarchical clustering relies on a measure of dissimilarity to combine ...

This is a simplified C++ interface to the fast implementations of hierarchical clustering by Daniel Müllner. The original library with interfaces to R and Python can be found on danifold.net and is ...

Abstract: In this paper, we tackle the issue of clustering trajectories of geolocalized observations based on the distance between trajectories. We first provide a comprehensive review of the ...

This repository presents the HiPart package, an open-source native python library that provides efficient and interpretable implementations of divisive hierarchical clustering algorithms. HiPart ...

Here we developed an open-source Python-based library called Python rodent Analysis and Tracking (PyRAT). Our library analyzes tracking data to classify distinct behaviors, estimate traveled distance, ...

BIRCH is an alternative to MinibatchKMeans and is designed for large datasets. The algorithm converts data into a tree structure, facilitating efficient clustering. BIRCH allows for initial clustering ...

1 Department of Computer Science and Engineering, Oakland University (OU), Rochester, MI, USA. 2 Department of Electrical and Computer Engineering, Oakland University (OU), Rochester, MI, USA. The ...