Helix is an open-source, FAIR-by-design analytics framework to address the growing need for transparency, interpretability, and reproducibility in data-driven scientific research. Designed for tabular data, Helix integrates the full analytical life cycle within a single modular, extensible environment. Helix places experimental provenance and human interpretability at its core, ensuring that modeling decisions, data transformations, and analytical outcomes are fully traceable and accessible. Its lightweight, browser-based interface lowers technical barriers for domain scientists while preserving methodological rigor and flexibility.

Network analysis is a cornerstone of network science research. Here, the authors present EasyGraph, an open-source network analysis library that supports a series of important interdisciplinary networ...

Mothers in academia take on considerably more childcare-related responsibilities than do fathers.

PDF | The growing concern for data privacy and user autonomy has led to the rise of decentralized online social networks, such as Mastodon. Unlike... | Find, read and cite all the research you need on...

Liang Wenfeng is part of Nature’s 10, a list of people who shaped science in 2025.

Nature - The milestone makes machine-learning trailblazer Yoshua Bengio the most cited researcher on Google Scholar.

Humanities and Social Sciences Communications - EasyHypergraph: an open-source software for fast and memory-saving analysis and learning of higher-order networks

EasyGraph is an open-source network analysis library designed to cover advanced network processing methods. It includes functionalities for detecting structural hole spanners, network embedding, an...

PDF | Decentralized online social networks such as Mastodon have emerged quickly during the past years, and offer unique opportunities to investigate... | Find, read and cite all the research you need...