Results 181 to 190 of about 2,467,001 (317)
An improved approach to infer protein-protein interaction based on a hierarchical vector space model. [PDF]
BMC Bioinformatics, 2018 Zhang J, Jia K, Jia J, Qian Y.
europepmc +1 more source
Geometry of Spaces of Vector-Valued Harmonic Functions [PDF]
, 1994 Patrick N. Dowling +2 more
openalex +1 more source
Advanced Functional Materials, EarlyView.Non‐covalent protein–protein interactions mediated by SH3, PDZ, or GBD domains enable the self‐assembly of stable and biocatalytically active hydrogel materials. These soft materials can be processed into monodisperse foams that, once dried, exhibit enhanced mechanical stability and activity and are easily integrated into microstructured flow ...
Julian S. Hertel +5 more
wiley +1 more source
Prediction of miRNA-disease associations with a vector space model. [PDF]
Sci Rep, 2016 Pasquier C, Gardès J.
europepmc +1 more source
MOFs and COFs in Electronics: Bridging the Gap between Intrinsic Properties and Measured Performance
Advanced Functional Materials, EarlyView.Metal‐organic frameworks (MOFs) and covalent organic frameworks (COFs) hold promise for advanced electronics. However, discrepancies in reported electrical conductivities highlight the importance of measurement methodologies. This review explores intrinsic charge transport mechanisms and extrinsic factors influencing performance, and critically ...
Jonas F. Pöhls, R. Thomas Weitz
wiley +1 more source
Integrals for functions with values in a partially ordered vector space. [PDF]
Positivity (Dordr), 2016 van Rooij ACM, van Zuijlen WB.
europepmc +1 more source
The Levi problem in non-locally convex seperable topological vector spaces.
, 1990 Aboubakr Bayoumi
openalex +2 more sources
The algebra of K-invariant vector fields on a symmetric space G/K [PDF]
, 2003 Ilka Agricola, Roe Goodman
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Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
Advanced Functional Materials, EarlyView.A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source