Interferon type 1 (IFN‐1) production and signaling is associated with the acquisition of therapy resistance, following chronic DNA damage, via Interferon‐related DNA damage resistance signature (IRDS) gene expression. An alternative, DNA damage‐independent role of sustained IFN‐1 mediated resistance was identified and characterized by the emergence of ...
Ashlyn Conant +11 more
wiley +1 more source
Extreme sensitivity label-free biosensing platform based on topologically disruptive phase nano-optics. [PDF]
Du F +7 more
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Lead radionuclides for theranostic applications in nuclear medicine: from atom to bedside. [PDF]
Berckmans Y +10 more
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Expanding the Toolbox of Multi-Material Three-Dimensional-Printed Electrochemical Flow Cells Fabricated in a Single Step: Impinging Jet, Mixing and Dilution, and Dual-Electrode Generator-Collector Electrochemical Cells. [PDF]
Mancini KM +5 more
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Transport and Reaction of Electrons and Molecules in Solid Electrolyte Interphases formed at Different Electrode Potentials: A Combined Experimental and Modeling Approach. [PDF]
Krauss FT, Duncker A, Roling B.
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Unraveling Torsional Preferences: Comparative Analysis of Torsion Motif Torsional-Angle Distributions across Different Environments. [PDF]
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DrugForm-TAS: Target-Agnostic Selectivity as Proteome-wide Binding Propensity Estimation. [PDF]
Tashchilova A +9 more
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Spatial Generation of Molecules with Transformers
2021 International Joint Conference on Neural Networks (IJCNN), 2021Generative models play an important role in the discovery of new molecules. However, these models often operate on a string or graph based representation of molecules, without taking spatial information into consideration. In this paper we introduce an autoregressive generative neural network operating directly in the three-dimensional space of atoms ...
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Unpaired Generative Molecule-to-Molecule Translation for Lead Optimization
Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, 2021Molecular lead optimization is an important task of drug discovery focusing on generating novel molecules similar to a drug candidate but with enhanced properties. Prior works focused on supervised models requiring datasets of pairs of a molecule and an enhanced molecule. These approaches require large amounts of data and are limited by the bias of the
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Molecule‐Driven Nanoenergy Generator
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