An explainability framework for deep learning on chemical reactions exemplified by enzyme-catalysed reaction classification

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Given a ground-level query image and a geo-referenced aerial image that covers the query’s local surroundings, fine-grained cross-view localization aims to estimate the location of the ground camera inside the aerial image. Recent works have focused on dev ...

Metabolic "dark matter" describes currently unknown metabolic processes, which form a blind spot in our general understanding of metabolism and slow down the development of biosynthetic cell factories and naturally derived pharmaceuticals. Mapping the dark ...

Background: Overexpression of the transsulfuration enzyme cystathionine-beta-synthase (CBS), and overproduction of its product, hydrogen sulfide (H2S) are recognized as potential pathogenetic factors in Down syndrome (DS). The purpose of the study was to d ...

Lignin has emerged as an attractive alternative in the search for more eco-friendly and less costly materials for enzyme immobilization. In this work, the terephthalic aldehyde-stabilization of lignin is carried out during its extraction to develop a serie ...

Organohalides are a class of compounds often considered as persistent pollutants and harmful to environmental and human health. Some bacteria, among which are representatives from the Firmicutes phylum, are capable of using these compounds as terminal acce ...

In phenylketonuria, absence or malfunction of the phenylalanine hydroxylase enzyme results in toxic accumulation of phenylalanine in the body. An injectable recombinant enzyme therapy was recently approved and has the potential to improve the quality of li ...

The advancements in genome editing techniques over the past years have rekindled interest in rational metabolic engineering strategies. While Metabolic Control Analysis (MCA) is a well-established method for quantifying the effects of metabolic engineering ...

The gut microbiome, often referred to as "super organ", comprises up to a hundred trillion microorganisms, and the species diversity may vary from person to person. They perform a decisive role in diverse biological functions related to metabolism, immunit ...

Motivation: Finding biosynthetic pathways is essential for metabolic engineering of organisms to produce chemicals, biodegradation prediction of pollutants and drugs, and for the elucidation of bioproduction pathways of secondary metabolites. A key step in ...

Microorganisms are essential for life on Earth, performing key roles in numerous biological processes. Their influence extends across a wide spectrum, from human health and ecological balance to advancements in biotechnology and industrial applications. Th ...

The first step in the construction of a regression model or a data-driven analysis, aiming to predict or elucidate the relationship between the atomic-scale structure of matter and its properties, involves transforming the Cartesian coordinates of the atom ...

Fiber reinforced polymer confined-recycled aggregate concrete filled steel tube (FRP-RACFST) not only proposes excellent load-bearing capacity and corrosion resistance, but is also an environmentally friendly structure due to the incorporation of recycled ...

The discovery of a drug requires over a decade of intensive research and financial investments – and still has a high risk of failure. To reduce this burden, we developed the NICEdrug.ch resource, which incorporates 250,000 bioactive molecules, and studied ...

Statistical (machine-learning, ML) models are more and more often used in computational chemistry as a substitute to more expensive ab initio and parametrizable methods. While the ML algorithms are capable of learning physical laws implicitly from data, ad ...

SIRT5 is a member of the sirtuin family of NAD(+)-dependent protein lysine deacylases implicated in a variety of physiological processes. SIRT5 removes negatively charged malonyl, succinyl, and glutaryl groups from lysine residues and thereby regulates mul ...

Proteins' biological functions are defined by the geometric and chemical structure of their 3D molecular surfaces. Recent works have shown that geometric deep learning can be used on mesh-based representations of proteins to identify potential functional s ...

High-entropy alloys (HEAs), containing several metallic elements in near-equimolar proportions, have long been of interest for their unique mechanical properties. More recently, they have emerged as a promising platform for the development of novel heterog ...

For the past two decades, linear free energy scaling relationships and volcano plots have seen frequent use as computational tools that aid in understanding and predicting the catalytic behavior of heterogeneous and electrocatalysts. Based on Sabatier's pr ...

A review is given on the highlights of a scatter-shot approach of developing machine-learning methods and artificial neural networks based fast predictors for the application to fusion exhaust. The aim is to enable and facilitate optimized and improved mod ...

An explainability framework for deep learning on chemical reactions exemplified by enzyme-catalysed reaction classification

Chattez avec Graph Search

Adapting Fine-Grained Cross-View Localization to Areas Without Fine Ground Truth

Expanding biochemical knowledge and illuminating metabolic dark matter with ATLASx

Role of the cystathionine beta-synthase / H2S pathway in the development of cellular metabolic dysfunction and pseudohypoxia in down syndrome

Dual Valorization of Lignin as a Versatile and Renewable Matrix for Enzyme Immobilization and (Flow) Bioprocess Engineering

Organohalide respiration in Firmicutes: energy metabolism and transcription regulation

Microfluidics and cell-free synthetic biology in the development of new diagnostic and therapeutic platforms

Constraint-based metabolic control analysis for rational strain engineering

Probiotics and gut microbiome-Prospects and challenges in remediating heavy metal toxicity

NICEpath: Finding metabolic pathways in large networks through atom-conserving substrate-product pairs

Optimality principles for the analysis of biological processes across scales: From enzyme kinetics to microbiome dynamics

Physics-Inspired Structural Representations for Molecules and Materials

Intelligent prediction framework for axial compressive capacity of FRP-RACFST columns

NICEdrug.ch, a workflow for rational drug design and systems-level analysis of drug metabolism

Encoding quantum-chemical knowledge into machine-learning models of complex molecular properties

Pharmacological and genetic perturbation establish SIRT5 as a promising target in breast cancer

Replica method for computational problems with randomness: principles and illustrations

Fast end-to-end learning on protein surfaces

Surface segregation in high-entropy alloys from alchemical machine learning

The Genesis of Molecular Volcano Plots

Data-driven models in fusion exhaust: AI methods and perspectives