The emergence of the information age in the last few decades brought with it an explosion of
biomedical data. But with great power comes great responsibility: there is now a pressing …

Persistent homology (PH) is a method used in topological data analysis (TDA) to study
qualitative features of data that persist across multiple scales. It is robust to perturbations of …

Motivation Topological methods have recently emerged as a reliable and interpretable
framework for extracting information from high-dimensional data, leading to the creation of a …

Biology has entered the age of Big Data. The technical revolution has transformed the field,
and extracting meaningful information from large biological data sets is now a central …

Network data has become widespread, larger, and more complex over the years. Traditional
network data is dyadic, capturing the relations among pairs of entities. With the need to …

In this study, we investigated cancer cellular networks in the context of gene interactions and
their associated patterns in order to recognize the structural features underlying this disease …

As malaria control programmes concentrate their efforts towards malaria elimination a better
understanding of malaria transmission patterns at fine spatial resolution units becomes …

Understanding how gene expression translates to and affects human behavior is one of the
ultimate goals of neuroscience. In this paper, we present a pipeline based on Mapper, a …

This article is a user's guide to algebraic topological methods for data analysis with a
particular focus on applications to datasets arising in experimental biology. We begin with …

The study of topology is strictly speaking, a topic in pure mathematics. However in only a few
years, Topological Data Analysis (TDA), which refers to methods of utilizing topological …