Refining Regulatory Networks through Phylogenetic Transfer of Information

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Gene regulation is inherently multiscale, but scale-adaptive machine learning methods that fully exploit this property in single-nucleus accessibility data are still lacking. Here, we develop ChromatinHD, a pair of scale-adaptive models that uses the raw a ...

Symbolic Regression holds great potential for uncovering underlying mathematical and physical relationships from observed data. However, the vast combinatorial space of possible expressions poses significant challenges for previous online search methods an ...

High resolution multi-physics core solvers predict safety parameters on a local scale with high accuracy while simulating local heterogeneities and their consequences. To achieve this, large computational resources are needed which renders the extensive us ...

Glacier-fed streams are the cold, ultra-oligotrophic, and unstable streams that are fed by glacial meltwater. Despite these extreme conditions, they harbour a diverse and abundant microbial diversity that develops into biofilms, covering the boulders and s ...

Background: Interactions among cis-regulatory elements (CREs) play a crucial role in gene regulation. Various approaches have been developed to map these interactions genome-wide, including those relying on interindividual epigenomic variation to identify ...

The adaptation of organisms to their environment depends on the innovative potential inherent to genetic variation. In complex organisms such as mammals, processes like development and immunity require tight gene regulation. Complex forms emerge more often ...

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 ...

Modern integrated circuits are tiny yet incredibly complex technological artifacts, composed of millions and billions of individual structures working in unison. Managing their complexity and facilitating their design drove part of the co-evolution of mode ...

The proliferation of microscopy methods for live-cell imaging offers many new possibilities for users but can also be challenging to navigate. The prevailing challenge in live-cell fluorescence microscopy is capturing intra-cellular dynamics while preservi ...

The main aim of this thesis is to study extreme value theory in a multivariate framework and to propose new methods for modeling and estimating dependence between several variables at extreme levels. We first give a brief overview of the main concepts of e ...

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 ...

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 ...

Mechanical resonators are widely used in sensors, transducers and optomechanical systems, where mechanical dissipation sets the ultimate limit to performance. Over the past 15 years, the quality factors in strained mechanical resonators have increased by f ...

As large, data-driven artificial intelligence models become ubiquitous, guaranteeing high data quality is imperative for constructing models. Crowdsourcing, community sensing, and data filtering have long been the standard approaches to guaranteeing or imp ...

This article reports on the current state of the OBI DICT project, a bilingual e-dictionary of oracle-bone inscriptions (OBI), incorporating artificial intelligence (AI) image recognition technology. It first provides a brief overview of the development of ...

The design and discovery of potential novel materials is critical for the advancement of climate change mitigation technologies. In this respect, metal-organic frameworks (MOFs) have received considerable attention over the last two decades. The combinatio ...

Background and Objective: Computational models of the cardiovascular system allow for a detailed and quantitative investigation of both physiological and pathological conditions, thanks to their ability to combine clinical-possibly patient-specific-data wi ...

Gruber et al. (2022) offered a framework how to explain "Physical time within human time", solving the 'two times problem: Here, I am asking whether such a problem exists at all. To question the question, I will appeal to neurobiological, evolutionary, and ...

Genome-wide chromatin conformation capture assays provide formidable insights into the spatial organization of genomes. However, due to the complexity of the data structure, their integration in multi-omics workflows remains challenging. We present data st ...

The Mycobacterium tuberculosis complex (MTBC) comprises nine human-adapted lineages that differ in their geographical distribution. Local adaptation of specific MTBC genotypes to the respective human host population has been invoked in this context. We aim ...

Refining Regulatory Networks through Phylogenetic Transfer of Information

Chattez avec Graph Search

ChromatinHD connects single-cell DNA accessibility and conformation to gene expression through scale-adaptive machine learning

Interactive symbolic regression with co-design mechanism through offline reinforcement learning

High-Resolution Predictions of the Fuel and Cladding Temperatures for the 3D PWR Core with Artificial Neural Networks trained on CTF

The microbial genomics of glacier-fed streams: adaptations to an extreme ecosystem

Non-coding variants impact cis-regulatory coordination in a cell type-specific manner

Meeting our Makers: Uncovering the cis-regulatory activity of transposable elements using statistical learning

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

Graph generative deep learning models with an application to circuit topologies

Live-cell imaging powered by computation

Flexible Statistical Inference for Multivariate Extremes

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

Surface segregation in high-entropy alloys from alchemical machine learning

Ultrahigh-quality-factor micro- and nanomechanical resonators using dissipation dilution

Extensions of Peer Prediction Incentive Mechanisms

The Current State of the OBI DICT Project: A Bilingual e-Dictionary of Oracle-Bone Inscriptions with AI Image Recognition

A diversity-driven discovery of potential nanoporous materials for energy-related applications

The role of computational methods in cardiovascular medicine: a narrative review

The Two Times Problem: Where Is the Problem?

Orchestrating chromosome conformation capture analysis with Bioconductor

Bacterial diversity dominates variable macrophage responses of tuberculosis patients in Tanzania