In silico feasibility of novel biodegradation pathways for 1,2,4-trichlorobenzene

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In the domain of computational structural biology, predicting protein interactions based on molecular structure remains a pivotal challenge. This thesis delves into this challenge through a series of interconnected studies. The first chapter introduces th ...

This study combined protein modeling methods to generate the prolamins' fractions as precise as possible. Hence, gliadins, zeins, kafirins, hordeins, secalins, avenins and oryzins were generated based on their characteristics and disulfide mapping. Finding ...

The application of computational biology in drug development for membrane protein targets has experienced a boost from recent developments in deep learning-driven structure prediction, increased speed and resolution of structure elucidation, machine learni ...

Post-translational modifications (PTMs) play a pivotal role in regulating protein structure, interaction, and function. Aberrant PTM patterns are associated with diseases. Moreover, individual PTMs have a complex interaction with each other, known as PTM c ...

Proteins, the central building blocks of life, play pivotal roles in nearly every biological function. To do so, these macromolecular structures interact with their surrounding environment in complex ways, leading to diverse functional behaviors. The predi ...

High-throughput generation of large and consistent ab initio data combined with advanced machine-learning techniques are enabling the creation of interatomic potentials of near ab initio quality. This capability has the potential of dramatically impacting ...

Saliency models are image-based prediction models that estimate human visual attention. Such models, when applied to architectural spaces, could pave the way for design decisions where visual attention is taken into account. In this study, we tested the pe ...

The interpretation of lung auscultation is highly subjective and relies on non-specific nomenclature. Computer-aided analysis has the potential to better standardize and automate evaluation. We used 35.9 hours of auscultation audio from 572 pediatric outpa ...

Inferring protein-protein interactions from sequences is an important task in computational biology. Recent methods based on Direct Coupling Analysis (DCA) or Mutual Information (MI) allow to find interaction partners among paralogs of two protein families ...

The sheer size of the protein sequence space is massive: a protein of 100 residues can have 20^100 possible sequence combinations; and knowing that this exceeds the number of atoms in the universe, the chance of randomly discovering a stable new sequence w ...

Predicting the effects of mutations on protein stability is a key problem in fundamental and applied biology, still unsolved even for the relatively simple case of small, soluble, globular, monomeric, two-state-folder proteins. Many articles discuss the li ...

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 ...

Human trajectory forecasting in crowds, at its core, is a sequence prediction problem with specific challenges of capturing inter-sequence dependencies (social interactions) and consequently predicting socially-compliant multimodal distributions. In recent ...

The concept of post-tensioned glass beams builds on the concrete analogy of the reinforced glass beams. By additionally prestressing the reinforcement in a post-tensioned system, a compressive pre-stress is applied on the glass, enhancing the initial fract ...

Structure-based antibody and antigen design has advanced greatly in recent years, due not only to the increasing availability of experimentally determined structures but also to improved computational methods for both prediction and design. Constant improv ...

We propose the Graph2Graph Transformer architecture for conditioning on and predicting arbitrary graphs, and apply it to the challenging task of transition-based dependency parsing. After proposing two novel Transformer models of transition-based dependenc ...

Protein-protein interaction (PPI) network alignment is a canonical operation to transfer biological knowledge among species. The alignment of PPI-networks has many applications, such as the prediction of protein function, detection of conserved network mot ...

The importance of additive manufacturing, also known as 3D printing, has grown exponentially in the recent years thanks to its high flexibility to manufacture intricate parts. This process can be divided into many different sub-categories, depending on the ...

In the recent Internet-of-Things (IoT) era where biomedical applications require continuous monitoring of relevant data, edge computing keeps gaining more and more importance. These new architectures for edge computing include multi-core and parallel compu ...

Predicting interactions between proteins and other biomolecules solely based on structure remains a challenge in biology. A high-level representation of protein structure, the molecular surface, displays patterns of chemical and geometric features that fin ...

In silico feasibility of novel biodegradation pathways for 1,2,4-trichlorobenzene

Chattez avec Graph Search

Predicting protein interactions using geometric deep learning on protein surfaces

Prolamins' 3D structure: A new insight into protein modeling using the language of numbers and shapes

Computational drug development for membrane protein targets

Investigating the intra-molecular and inter-molecular effects of post-translational modifications on intrinsically disordered protein regions and structured protein regions

A Geometric Transformer for Structural Biology: Development and Applications of the Protein Structure Transformer

Machine-learned interatomic potentials: Recent developments and prospective applications

Saliency prediction in 360° architectural scenes: Performance and impact of daylight variations

DeepBreath-automated detection of respiratory pathology from lung auscultation in 572 pediatric outpatients across 5 countries

Correlations from structure and phylogeny combine constructively in the inference of protein partners from sequences

Towards automating de novo protein design for novel functionalities: controlling protein folds and protein-protein interactions

Reviewing Challenges of Predicting Protein Melting Temperature Change Upon Mutation Through the Full Analysis of a Highly Detailed Dataset with High-Resolution Structures

Fast end-to-end learning on protein surfaces

Interpretable Social Anchors for Human Trajectory Forecasting in Crowds

Flexural behaviour of post-tensioned glass beams: Experimental and analytical study of three beam typologies

Modeling Immunity with Rosetta: Methods for Antibody and Antigen Design

Graph-to-Graph Transformer for Transition-based Dependency Parsing

MPGM: Scalable and Accurate Multiple Network Alignment

Operando X-ray diffraction during laser 3D printing: from machine design to experiments and computer simulations

Real-Time Personalized Atrial Fibrillation Prediction on Multi-Core Wearable Sensors

Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning