Topological Data Analysis for Python🐍

A Lean Persistent Homology Library for Python

Distances and representations of persistence diagrams

Topological Data Analysis in Python: Simplicial Complex

Flexible and efficient persistent homology computation.

A repackaged version of the Kenzo program by Francis Sergeraert and collaborators.

A homology-based, computationally lightweight pipeline for discovering genes in the absence of an assembly

R pipeline for computing persistent homology in topological data analysis. See https://doi.org/10.21105/joss.00860 for more details.

Workflow for identifying and classifying homologous gene/protein sequences

Find reciprocal best hits (DIAMOND or BLAST) between two (or more!) sets of sequences.

Use Thor's Axe to cut exons into their evolutionary building blocks ⚡

Feature-aware orthology prediction tool. Provided data package: Quest for Orthologs reference gene sets 2019.

Simple Ripser wrapper in Julia

华中科技大学软件安全课程设计2019

Topological Data Analysis with Persistent Homology summer course (2021, FGV)

Computing homology groups of simplicial complexes

Identification and structural characterization of transcription factors based on supervised machine learning

A simple python project for computing persistent homology

UDiPH is a package that creates a new metric space where the points are uniformly sampled with respect to a global metric. It is oriented for creating Vietoris-Rips filtrations that are independent of the metric of the initial space.