Supercomputer-developed AI learns the intricate language of biomolecules

Scientists at the University of Glasgow have harnessed a powerful supercomputer, normally used by astronomers and physicists ...

Unlock the Secrets of Google Colab: Your Ultimate Beginner’s Guide

Learn how to use Google Colab for coding, data science, and AI projects with this beginner-friendly guide. Free GPU access ...
IEEE

Why Do Machine Learning Notebooks Crash? An Empirical Study on Public Python Jupyter Notebooks

Abstract: Jupyter notebooks have become central in data science, integrating code, text and output in a flexible environment. With the rise of machine learning (ML), notebooks are increasingly used ...

Benchling Reveals the Next Chapter of R&D at Benchtalk 2025

Benchling today unveiled major new capabilities at Benchtalk, its annual customer conference. These new releases are designed to help ...
Frontiers

Construction of a diagnostic model and identification of effect genes for diabetic kidney disease with concurrent vascular calcification based on bioinformatics and multiple ...

Objective: This study aims to construct a diagnostic model for diabetic kidney disease (DKD) with concurrent vascular calcification (VC) using bioinformatics combined with machine learning approaches ...
eLife

Explainable machine learning-assisted exploration of chromatin dynamics reveals chromosome-specific response to serum starvation

This interesting study adapts machine learning tools to analyze movements of a chromatin locus in living cells in response to serum starvation. The machine learning approach developed is useful, the ...
Frontiers

Identification and validation of biomarkers in gastric cancer-associated membranous nephropathy: Insights from comprehensive bioinformatics analysis and machine learning

1 Department of Nephrology, China-Japan Friendship Hospital, Beijing, China 2 Department of Nephrology, Peking University China-Japan Friendship School of Clinical Medicine, Beijing, China Background: ...
IEEE

Adaptive Homophily Clustering: Structure Homophily Graph Learning With Adaptive Filter for Hyperspectral Image

Abstract: Hyperspectral image (HSI) clustering is a fundamental yet challenging task that typically operates without training labels. Recent advancements in deep graph clustering methods have shown ...