Engineering novel protein interactions with therapeutic potential using deep learning-guided surface design

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Recently, single-particle cryo-electron microscopy emerged as a technique capable of determining protein structures at near-atomic resolution and resolving protein dynamics with a temporal resolution ranging from second to milliseconds. This thesis describ ...

Deep neural networks (DNNs) are receiving increasing attention in wind power forecasting due to their ability to effectively capture complex patterns in wind data. However, their forecast errors are severely limited by the local optimal weight issue in opt ...

Cartilage homeostasis, crucial for musculoskeletal function, is orchestrated by interconnected biophysical cues. In healthy cartilage, repetitive compressive loading not only elicits a range of mechanical stimuli but also induces a gradual transient temper ...

Engineering and characterizing proteins can be time-consuming and cumbersome, motivating the development of generalist CRISPR-Cas enzymes1–4 to enable diverse genome editing applications. However, such enzymes have caveats such as an increased risk of off- ...

High-dimensional data must be highly structured to be learnable. Although the compositional and hierarchical nature of data is often put forward to explain learnability, quantitative measurements establishing these properties are scarce. Likewise, accessin ...

Machine learning has provided a means to accelerate early-stage drug discovery by combining molecule generation and filtering steps in a single architecture that leverages the experience and design preferences of medicinal chemists. However, designing mach ...

Facial paralysis is a highly burdening condition, resulting in a patient's inability to move his musculature on one or both sides of the mouth. The restoration of facial movement is crucial for enhancing the overall patients' quality of life. The use of DE ...

Optical biosensors offer significant advantages for minimally invasive in vivo and in vitro diagnostics. Optical sensors that are based on the fluorescence of semiconducting single-walled carbon nanotubes (SWCNTs) especially benefit from a near-infrared (n ...

Over the past two decades, protein S-acylation (often referred to as S-palmitoylation) has emerged as an important regulator of vital signalling pathways. S-Acylation is a reversible post-translational modification that involves the attachment of a fatty a ...

Sign Language conveys information through multiple channels composed of manual (handshape, hand movement) and non-manual (facial expression, mouthing, body posture) components. Sign language assessment involves giving granular feedback to a learner, in ter ...

Microorganisms are a key component in the chain of life. They are essential for agriculture, produce a large proportion of oxygen, and play a central role in the cycle of elements. Microorganisms are widely used in the production of food and alcoholic beve ...

“You never forget how to ride a bike”, – but how is that possible? The brain is able to learn complex skills, stop the practice for years, learn other skills in between, and still retrieve the original knowledge when necessary. The mechanisms of this capab ...

The synthesis of complex sugars is a key aspect of microbial biology. Cyclic beta-1,2-glucan (C beta G) is a circular polysaccharide critical for host interactions of many bacteria, including major pathogens of humans (Brucella) and plants (Agrobacterium). ...

Rigid body interactions are fundamental to numerous scientific disciplines, but remain challenging to simulate due to their abrupt nonlinear nature and sensitivity to complex, often unknown environmental factors. These challenges call for adaptable learnin ...

One of the goals of synthetic biology is the development of an artificial cell. Building an artificial cell from scratch will provide a deeper understanding of fundamental mechanisms and models in biology and promises to contribute towards building novel p ...

Neurons in the human amygdala and hippocampus are classically thought to encode a person’s identity invariant to visual features. However, it remains largely unknown how visual information from higher visual cortical areas is translated into such a semanti ...

Codes of practice can be overly conservative, particularly for the shear resistance of reinforced concrete beams with shear reinforcement when large loads act close to supports. This thesis addresses the topic by proposing a refined design approach based o ...

Change detection (CD) is a critical task in remote sensing, especially for monitoring dynamic urban environments. In this work, we present a novel, self-supervised CD approach that leverages a two-player architecture to improve the reliability and accuracy ...

Translation elongation plays an important role in regulating protein concentrations in the cell, and dysregulation of this process has been linked to several human diseases. In this study, we use data from ribo-seq experiments to model ribosome densities, ...

Physical adsorption is crucial in many industrial processes, prompting researchers to develop new materials for energy-efficient processes. Porous adsorbents are particularly promising due to their design flexibility, and computational screening has accele ...

Engineering novel protein interactions with therapeutic potential using deep learning-guided surface design

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Microsecond Time-Resolved Cryo-Electron Microscopy

Improving the accuracy and interpretability of neural networks for wind power forecasting

Synergetic Support of Cartilage Homeostasis via Coupled Thermal-Hydrostatic Pressure Stimuli

Custom CRISPR—Cas9 PAM variants via scalable engineering and machine learning

Probing the latent hierarchical structure of data via diffusion models

Machine learning-aided generative molecular design

DEMO: Dielectric elastomer actuators (DEAs) for the restoration of facial movements

Designing DNA-based nanotubes as near-infrared sensors for detecting cancer biomarkers

Mechanisms and functions of protein S-acylation

Posterior-Based Analysis of Spatio-Temporal Features for Sign Language Assessment

Reconstruction and analysis of genome-scale metabolic networks in single organisms and microbial communities

Context selectivity with dynamic availability enables lifelong continual learning

Structure-function analysis of the cyclic β-1,2-glucan synthase from Agrobacterium tumefaciens

Integrating Physics and Topology in Neural Networks for Learning Rigid Body Dynamics

Advancing Cell-Free Synthetic Biology: From sustained PURE protein synthesis to an isothermal one-pot DNA replication system

Feature-based encoding of face identity by single neurons in the human amygdala and hippocampus

Experimental and analytical investigation of shear-reinforced concrete and dowel action

Self-supervised Change Detection via Cooperative Learning: A Two-Player Model

Towards improving full-length ribosome density prediction by bridging sequence and graph-based representations

Classical density functional theory as a fast and accurate method for adsorption property prediction of porous materials