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: DBSCAN (Density-Based Spatial Clustering of Applications with Noise) is an unsupervised clustering algorithm designed to identify clusters of various shapes and sizes in noisy datasets by ...

This repository contains the code base and examples for Building Aggregates with a Neighborhood Kernel and Spatial Yardstick developed for: BANKSY: A Spatial Clustering Algorithm that Unifes Cell ...

In today’s data-rich environment, business are always looking for a way to capitalize on available data for new insights and increased efficiencies. Given the escalating volumes of data and the ...

Classification algorithms learn how to assign class labels to examples (observations or data points), although their decisions can appear opaque. A popular diagnostic for understanding the decisions ...

Microsoft Excel is essential for the End-User Approach (EUA), offering versatility in data organization, analysis, and visualization, as well as widespread accessibility. It fosters collaboration and ...

Matplotlib is a versatile 2D plotting library that provides an array of visualization options. Whether it's line plots, scatter plots, bar plots, or even 3D plots, Matplotlib has you covered. Its ...

If you want to learn the math behind data science and machine learning, 3Blue1Brown is the channel for you. Created by Grant Sanderson, 3Blue1Brown uses animation to explain complex mathematical ...

Clustering is usually the first exploratory analysis step in empirical data. When the data set comprises graphs, the most common approaches focus on clustering its vertices. In this work, we are ...