AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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2,039 papers
This paper explores the application of Geometric Information Theory (GIT) to computational biology, aiming to develop a novel measure of 'information content' within biological systems. GIT leverages the geometric structure of molecules and cellular processes to quantify complexity and connectivity, offering a potentia...
Statins are a commonly prescribed cholesterol-lowering drug class that can increase the risk of new-onset diabetes (NOD). The underlying molecular mechanisms have yet to be fully elucidated. We aimed to identify molecular factors associated with differential susceptibility to NOD and determine their effects on β-...
Vegetative desiccation tolerance requires specialised cell wall (CW) adaptations to withstand severe mechanical stress during dehydration and rehydration. While intracellular protective strategies in resurrection plants, including Ramonda serbica, are well documented, the CW response remains poorly understood. Here, we...
A unified physics‑based framework for macromolecular refinement , Predictor and mutational scanning. Built around a novel Self‑Organised Criticality (SOC) controller, it refines proteins, DNA, RNA, and their complexes using a fully differentiable energy function powered by OpenMM, then scales to thousands of in silico...
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This paper explores the application of Geometric Information Theory (GIT) to computational biology, aiming to develop a novel measure of 'information content' within biological systems. GIT leverages the geometric structure of molecules and cellular processes to quantify complexity and connectivity, offering a potentia...
This paper explores the application of non-standard harmonic analysis to the analysis of complex systems, specifically focusing on fluid dynamics and protein folding. Traditional methods often fall short in effectively modeling these systems due to their inherent complexity and the difficulty in capturing emergent prop...
First version submitted to Bioconductor. NADIA covers the differential abundance analysis of protein quantification data from the raw report to the figure, treating the missing values that dominate data-independent acquisition as the central problem rather than a nuisance to be filtered away. Reports from Spectronaut,...
This paper introduces a novel adaptive multi-dynamics simulation framework designed to model complex biological systems and optimize biological engineering design through automated parameter adjustment based on simulation results. Traditional multi-dynamics simulations often require extensive manual parameter tuning, h...
This paper explores the application of non-standard harmonic analysis to the analysis of complex systems, specifically focusing on fluid dynamics and protein folding. Traditional methods often fall short in effectively modeling these systems due to their inherent complexity and the difficulty in capturing emergent prop...
Protein folding, the process by which a polypeptide chain attains its functional three-dimensional structure, is a fundamental problem in biochemistry and bioinformatics. Traditional approaches to predicting protein folding pathways have faced significant challenges due to the complex, high-dimensional nature of the un...
Evolution ONE is a standalone, vendor‑neutral platform that models cancer progression through the lens of Self‑Organised Criticality (SOC), duon biology, and physics‑based structural refinement. It ingests genomic mutation data (MAF, VCF) and outputs a complete oncological profile: the evolutionary regime of the tumour...
A unified physics‑based framework for macromolecular refinement , Predictor and mutational scanning. Built around a novel Self‑Organised Criticality (SOC) controller, it refines proteins, DNA, RNA, and their complexes using a fully differentiable energy function powered by OpenMM, then scales to thousands of in silico...
Proof of concept for watermarking AI-generated proteins while preserving biological function.
A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.
Scientists are using AlphaFold to strengthen a photosynthesis enzyme for resilient, heat-tolerant crops.
Explore how AlphaFold has accelerated science and fueled a global wave of biological discovery.
AlphaFold has revealed the structure of a key protein behind heart disease
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