Multi-scale calculation of the electric properties of organic-based devices from the molecular structure

2016 ◽  
Vol 33 ◽  
pp. 164-171 ◽  
Author(s):  
Haoyuan Li ◽  
Yong Qiu ◽  
Lian Duan
Keyword(s):  
Molecular Structure ◽  
Electric Properties ◽  
Multi Scale

scholarly journals A multi-scale approach to describe electrical impulses propagating along actin filaments in both intracellular andin vitroconditions

RSC Advances ◽  
2018 ◽  
Vol 8 (22) ◽  
pp. 12017-12028 ◽  
Author(s):  
Christian Hunley ◽  
Diego Uribe ◽  
Marcelo Marucho
Keyword(s):  
Molecular Structure ◽  
Actin Filaments ◽  
Analytic Solution ◽  
Multi Scale ◽  
Biological Environment ◽  
Electrical Impulses

An innovative analytic solution accounting for the molecular structure, its biological environment, and their impact on electrical impulses along microfilaments.

MUFFIN: multi-scale feature fusion for drug–drug interaction prediction

2021 ◽  
Author(s):  
Yujie Chen ◽  
Tengfei Ma ◽  
Xixi Yang ◽  
Jianmin Wang ◽  
Bosheng Song ◽  
...  
Keyword(s):  
Molecular Structure ◽  
Deep Learning ◽  
Medical Information ◽  
Feature Fusion ◽  
Molecular Graph ◽  
Knowledge Graph ◽  
Sequence Information ◽  
Learning Models ◽  
Scale Feature ◽  
Multi Scale

Abstract Motivation Adverse drug–drug interactions (DDIs) are crucial for drug research and mainly cause morbidity and mortality. Thus, the identification of potential DDIs is essential for doctors, patients and the society. Existing traditional machine learning models rely heavily on handcraft features and lack generalization. Recently, the deep learning approaches that can automatically learn drug features from the molecular graph or drug-related network have improved the ability of computational models to predict unknown DDIs. However, previous works utilized large labeled data and merely considered the structure or sequence information of drugs without considering the relations or topological information between drug and other biomedical objects (e.g. gene, disease and pathway), or considered knowledge graph (KG) without considering the information from the drug molecular structure. Results Accordingly, to effectively explore the joint effect of drug molecular structure and semantic information of drugs in knowledge graph for DDI prediction, we propose a multi-scale feature fusion deep learning model named MUFFIN. MUFFIN can jointly learn the drug representation based on both the drug-self structure information and the KG with rich bio-medical information. In MUFFIN, we designed a bi-level cross strategy that includes cross- and scalar-level components to fuse multi-modal features well. MUFFIN can alleviate the restriction of limited labeled data on deep learning models by crossing the features learned from large-scale KG and drug molecular graph. We evaluated our approach on three datasets and three different tasks including binary-class, multi-class and multi-label DDI prediction tasks. The results showed that MUFFIN outperformed other state-of-the-art baselines. Availability and implementation The source code and data are available at https://github.com/xzenglab/MUFFIN.

Molecular structure and electric properties of some pyridine and pyridine-N-oxide derivatives

1998 ◽  
Vol 471 (1-3) ◽  
pp. 127-137 ◽  
Author(s):  
V.V. Prezhdo ◽  
E.V. Vaschenko ◽  
O.V. Prezhdo ◽  
A. Puszko
Keyword(s):  
Molecular Structure ◽  
Electric Properties

Molecular structure and electric properties of N -methyl- N -nitroaniline and its derivatives

2001 ◽  
Vol 559 (1-3) ◽  
pp. 321-330 ◽  
Author(s):  
O.V. Prezhdo ◽  
A.S. Bykova ◽  
V.V. Prezhdo ◽  
A. Koll ◽  
Z. Daszkiewicz
Keyword(s):  
Molecular Structure ◽  
Electric Properties

Multiscale Modeling Techniques Based on Molecular Structure and Elastic Properties

2013 ◽  
Vol 312 ◽  
pp. 438-441
Author(s):  
Jiu Li
Keyword(s):  
Molecular Structure ◽  
Force Field ◽  
Elastic Properties ◽  
Polymer Structure ◽  
Structure And Properties ◽  
Basic Principles ◽  
Multi Scale ◽  
Scale Modeling ◽  
Modeling Techniques ◽  
Nonlinear Continuum

Based on the principle of using atomistic force field, and the use of ultra-flexible multi-scale modeling techniques to predict the polycarbonate and polyimide polymer molecular structure and the elastic properties of the system. The model combines molecular modeling and nonlinear continuum mechanics basic principles, to simulate and predict the behavior of the material properties of the polymer molecular structure. For the polymer structure and properties, using a plurality of force field simulation to predict the contrast, and binding experiments measured polymer performance value, using static and dynamic molecular simulation technology for molecular mechanics energy minimization to solve.

Experimental and theoretical investigation on the molecular structure, spectroscopic and electric properties of 2,4-dinitrodiphenylamine, 2-nitro-4-(trifluoromethyl)aniline and 4-bromo-2-nitroaniline

2015 ◽  
Vol 149 ◽  
pp. 240-253 ◽  
Author(s):  
Javier Hernández-Paredes ◽  
Ofelia Hernández-Negrete ◽  
Roberto C. Carrillo-Torres ◽  
Raúl Sánchez-Zeferino ◽  
Alberto Duarte-Moller ◽  
...  
Keyword(s):  
Molecular Structure ◽  
Theoretical Investigation ◽  
Electric Properties

Molecular Structure of the Outermost Cell Wall Component of Spirillum Serpens

1977 ◽  
Vol 35 ◽  
pp. 342-343
Author(s):  
Wah Chiu ◽  
David Grano
Keyword(s):  
Molecular Structure ◽  
Cell Wall ◽  
Outer Membrane ◽  
Gel Electrophoresis ◽  
Electron Microscopic Examination ◽  
Electron Microscopic ◽  
Cell Wall Component ◽  
Protein Components ◽  
Exposure Technique ◽  
Structural Aspects

The periodic structure external to the outer membrane of Spirillum serpens VHA has been isolated by similar procedures to those used by Buckmire and Murray (1). From SDS gel electrophoresis, we have found that the isolated fragments contain several protein components, and that the crystalline structure is composed of a glycoprotein component with a molecular weight of ∽ 140,000 daltons (2). Under an electron microscopic examination, we have visualized the hexagonally-packed glycoprotein subunits, as well as the bilayer profile of the outer membrane. In this paper, we will discuss some structural aspects of the crystalline glycoproteins, based on computer-reconstructed images of the external cell wall fragments.The specimens were prepared for electron microscopy in two ways: negatively stained with 1% PTA, and maintained in a frozen-hydrated state (3). The micrographs were taken with a JEM-100B electron microscope with a field emission gun. The minimum exposure technique was essential for imaging the frozen- hydrated specimens.

Sign in / Sign up

Export Citation Format

Share Document