BRAPH 2: A flexible, open-source, reproducible, community-oriented, easy-to-use framework for network analyses in neurosciences

SoftwareX 2026 Open access

Read full text
Authors: Yu-Wei Chang, Blanca Zufiria‐Gerboles, Emiliano Gómez-Ruiz, Anna Canal-García, Hang Zhao, Mite Mijalkov, Joana B. Pereira, Giovanni Volpe
DOI: 10.1016/j.softx.2026.102791
Cited by: 1
References: 21

Abstract

As network analyses in neuroscience continue to grow in both complexity and size, flexible methods are urgently needed to provide unbiased, reproducible insights into brain function. BRAPH 2 is a versatile, open-source framework that meets this challenge by offering streamlined workflows for advanced statistical models and deep learning, while supporting community-oriented extension, reuse, and sharing. Through its Genesis compiler, users can build specialized distributions with custom pipelines, ensuring flexibility and scalability across diverse research domains. These capabilities support reproducibility and accelerate discovery in neuroscience.

Fields of Study & Subjects

Functional Brain Connectivity Studies Cell Image Analysis Techniques Bioinformatics and Genomic Networks

Publication details

Journal / source
SoftwareX
Publisher
Elsevier BV
Volume
35
Pages
102791–102791
Publication date
12 June 2026
Language
EN