Results 151 to 160 of about 1,201,498 (234)

Consensus Formation and Change are Enhanced by Neutrality

open access: yesAdvanced Science, EarlyView.
Neutral agents are shown to enhance both the formation and overturning of consensus in collective decision‐making. A general mathematical model and experiments with locusts and humans reveal that neutrality enables robust consensus via simple interactions and accelerates consensus change by reducing effective population size.
Andrei Sontag   +3 more
wiley   +1 more source

TAD conservation in vertebrate genomes is driven by stabilising selection

open access: yesBMC Biology
Background Topologically associating domains (TADs) are fundamental structural and gene regulatory components of chromatin defined by regions of high intra-domain contact frequency.
Fabiana Patalano   +3 more
doaj   +1 more source

Machine Learning for Green Solvents: Assessment, Selection and Substitution

open access: yesAdvanced Science, EarlyView.
Environmental regulations have intensified demand for green solvents, but discovery is limited by Solvent Selection Guides (SSGs) that quantify solvent sustainability. Training a machine learning model on GlaxoSmithKline SSG, a database of sustainability metrics for 10,189 solvents, GreenSolventDB is developed. Integrated with Hansen solubility metrics,
Rohan Datta   +4 more
wiley   +1 more source

Efficient and Accurate Detection of Topologically Associating Domains from Contact Maps.

open access: yes, 2017
Continuous improvements to high-throughput conformation capture (Hi-C) are revealing richerinformation about the spatial organization of the chromatin and its role in cellular functions.Several studies have confirmed the existence of structural features of the genome 3D organiza-tion that are stable across cell types and conserved across species ...
Abbas Roayaei Ardakany, Stefano Lonardi
openaire   +4 more sources

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

open access: yesAdvanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray   +3 more
wiley   +1 more source

The hierarchical folding dynamics of topologically associating domains are closely related to transcriptional abnormalities in cancers. [PDF]

open access: yesComput Struct Biotechnol J, 2021
Du G   +22 more
europepmc   +1 more source

Overcoming Artificial Structures in Resolution‐Enhanced Hi‐C Data by Signal Decomposition and Multi‐Scale Attention

open access: yesAdvanced Science, EarlyView.
Deep‐learning‐based signal enhancement is an effective way to recover high‐resolution details from a low‐resolution chromatin contact map. However, due to computational challenges, existing methods commonly divide up the contact map into small patches and create artificial discontinuities at patch boundaries.
Qinyao Li   +6 more
wiley   +1 more source

Type‐II Dirac Fermions in Monolayer In2O: Interplay of Magnetotransport, Spin Hall Effect, and Superconductivity

open access: yesAdvanced Science, EarlyView.
First‐principles calculations reveal that monolayer In2O${\rm In}_2{\rm O}$ hosts type‐II Dirac fermions near the Fermi level, which split into Weyl points under spin‐orbit coupling. The material exhibits negative and giant magnetoresistance, a pronounced spin Hall effect, and phonon‐mediated superconductivity at 1.5 K, establishing it as a unique ...
Qing‐Bo Liu   +6 more
wiley   +1 more source

juan-mulero/cisreg: Semantic model for CRM, TAD and gene extension for BioGateway knowledge graphs

open access: yes
<p>Version associated with the manuscript "<em>Integration of chromosome locations and functional aspects of enhancers and topologically associating domains in knowledge graphs enables versatile queries about gene regulation</em> ...
Juan Mulero-Hernández
core   +1 more source

Unifying Composition and Process Design: A Heterogeneous Graph Neural Network for Discovering High‐Performance Cu Alloys

open access: yesAdvanced Science, EarlyView.
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin   +12 more
wiley   +1 more source

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