DrugLogit: Logistic Discrimination between Drugs and Nondrugs Including Disease-Specificity by Assigning Probabilities Based on Molecular Properties

2012 ◽  
Vol 52 (8) ◽  
pp. 2165-2180 ◽  
Author(s):  
Alfonso T. García-Sosa ◽  
Mare Oja ◽  
Csaba Hetényi ◽  
Uko Maran
Keyword(s):  
Molecular Properties ◽  
Logistic Discrimination ◽  
Disease Specificity

Ultrastructure of Fibroblast Cultures, Lymphocytes, and Liver in Mucopolysaccharidoses Types I, II, III, IV, and VI.

1970 ◽  
Vol 28 ◽  
pp. 204-205
Author(s):  
George Hug ◽  
William K. Schubert ◽  
Shirley Soukup
Keyword(s):  
Lysosomal Enzyme ◽  
Apparent Lack ◽  
Fibroblast Cultures ◽  
Lysosomal Diseases ◽  
Disease Specificity ◽  
Deficient Activity

McKusick subdivided the syndrome of mucopolysaccharidoses into six types according to clinical, roentenographic, and genetic criteria and to the kind of mucopolysaccharide(s) excreted in the urine (1). Deficient activity of a lysosomal enzyme, (β-galactosidase, has recently been reported in types I, II and III of mucopolysaccharidoses as well as in generalized gangliosidosis (2). This apparent lack of disease specificity makes the enzymatic deficiency difficult to interpret. Nevertheless, the involvement of a lysosomal enzyme tends to characterize these disorders as lysosomal diseases.

Discriminant Analysis and its Applications in Epidemiology

1980 ◽  
Vol 19 (04) ◽  
pp. 220-226 ◽  
Author(s):  
P. A. Lachenbruch ◽  
W. R. Clarke
Keyword(s):  
Discriminant Analysis ◽  
Historical Review ◽  
Review Article ◽  
Logistic Discrimination

This review article discusses current use of discriminant analysis in epidemiology. Contents include historical review, simple extensions and generalizations, examples, evaluation of rules, logistic discrimination, and robustness.

A Thorough Theoretical Exploration of Intriguing Characteristics of Cyclo[18]carbon: Geometry, Bonding Nature, Aromaticity, Weak Interaction, Reactivity, Excited States, Vibrations, Molecular Dynamics and Various Molecular Properties

2019 ◽  
Author(s):  
Tian Lu ◽  
Qinxue Chen ◽  
Zeyu Liu
Keyword(s):  
Molecular Dynamics ◽  
Excited States ◽  
Electronic Excitation ◽  
Ring Structure ◽  
Molecular Properties ◽  
Molecular Vibration ◽  
Full Characterization ◽  
Long Time ◽  
Almost All

Although cyclo[18]carbon has been theoretically and experimentally investigated since long time ago, only very recently it was prepared and directly observed by means of STM/AFM in condensed phase (Kaiser et al., <i>Science</i>, <b>365</b>, 1299 (2019)). The unique ring structure and dual 18-center π delocalization feature bring a variety of unusual characteristics and properties to the cyclo[18]carbon, which are quite worth to be explored. In this work, we present an extremely comprehensive and detailed investigation on almost all aspects of the cyclo[18]carbon, including (1) Geometric characteristics (2) Bonding nature (3) Electron delocalization and aromaticity (4) Intermolecular interaction (5) Reactivity (6) Electronic excitation and UV/Vis spectrum (7) Molecular vibration and IR/Raman spectrum (8) Molecular dynamics (9) Response to external field (10) Electron ionization, affinity and accompanied process (11) Various molecular properties. We believe that our full characterization of the cyclo[18]carbon will greatly deepen researchers' understanding of this system, and thereby help them to utilize it in practice and design its various valuable derivatives.

A Thorough Theoretical Exploration of Intriguing Characteristics of Cyclo[18]carbon: Geometry, Bonding Nature, Aromaticity, Weak Interaction, Reactivity, Excited States, Vibrations, Molecular Dynamics and Various Molecular Properties

2019 ◽  
Author(s):  
Tian Lu ◽  
Qinxue Chen ◽  
Zeyu Liu
Keyword(s):  
Molecular Dynamics ◽  
Excited States ◽  
Electronic Excitation ◽  
Ring Structure ◽  
Molecular Properties ◽  
Molecular Vibration ◽  
Full Characterization ◽  
Long Time ◽  
Almost All

Although cyclo[18]carbon has been theoretically and experimentally investigated since long time ago, only very recently it was prepared and directly observed by means of STM/AFM in condensed phase (Kaiser et al., <i>Science</i>, <b>365</b>, 1299 (2019)). The unique ring structure and dual 18-center π delocalization feature bring a variety of unusual characteristics and properties to the cyclo[18]carbon, which are quite worth to be explored. In this work, we present an extremely comprehensive and detailed investigation on almost all aspects of the cyclo[18]carbon, including (1) Geometric characteristics (2) Bonding nature (3) Electron delocalization and aromaticity (4) Intermolecular interaction (5) Reactivity (6) Electronic excitation and UV/Vis spectrum (7) Molecular vibration and IR/Raman spectrum (8) Molecular dynamics (9) Response to external field (10) Electron ionization, affinity and accompanied process (11) Various molecular properties. We believe that our full characterization of the cyclo[18]carbon will greatly deepen researchers' understanding of this system, and thereby help them to utilize it in practice and design its various valuable derivatives.

Accurate and Transferable Multitask Prediction of Chemical Properties with an Atoms-in-Molecule Neural Network

2018 ◽  
Author(s):  
Roman Zubatyuk ◽  
Justin S. Smith ◽  
Jerzy Leszczynski ◽  
Olexandr Isayev
Keyword(s):  
Neural Network ◽  
Molecular System ◽  
Computational Cost ◽  
Chemical Properties ◽  
The State ◽  
Molecular Properties ◽  
Training Data ◽  
Dft Methods ◽  
Benchmark Datasets ◽  
Quantum Phenomena

<p>Atomic and molecular properties could be evaluated from the fundamental Schrodinger’s equation and therefore represent different modalities of the same quantum phenomena. Here we present AIMNet, a modular and chemically inspired deep neural network potential. We used AIMNet with multitarget training to learn multiple modalities of the state of the atom in a molecular system. The resulting model shows on several benchmark datasets the state-of-the-art accuracy, comparable to the results of orders of magnitude more expensive DFT methods. It can simultaneously predict several atomic and molecular properties without an increase in computational cost. With AIMNet we show a new dimension of transferability: the ability to learn new targets utilizing multimodal information from previous training. The model can learn implicit solvation energy (like SMD) utilizing only a fraction of original training data, and archive MAD error of 1.1 kcal/mol compared to experimental solvation free energies in MNSol database.</p>

Thienopyrrolocarbazoles: New Building Blocks for Functional Organic Materials

2019 ◽  
Author(s):  
Dorian Bader ◽  
Johannes Fröhlich ◽  
Paul Kautny
Keyword(s):  
Building Block ◽  
Organic Materials ◽  
Building Blocks ◽  
Molecular Properties ◽  
The Family ◽  
Facile Preparation

The facile preparation of three regioisomeric thienopyrrolocarbazoles applying a convenient C-H activation approach is presented. Derived from indolo[3,2,1-<i>jk</i>]carbazole, the incorporation of thiophene into the triarylamine framework significantly impacted the molecular properties of the parent scaffold. The developed thienopyrrolocarbazoles enrich the family of triarylamine donors and constitute a novel building block for functional organic materials.

Thienopyrrolocarbazoles: New Building Blocks for Functional Organic Materials

2019 ◽  
Author(s):  
Dorian Bader ◽  
Johannes Fröhlich ◽  
Paul Kautny
Keyword(s):  
Building Block ◽  
Organic Materials ◽  
Building Blocks ◽  
Molecular Properties ◽  
The Family ◽  
Facile Preparation

The facile preparation of three regioisomeric thienopyrrolocarbazoles applying a convenient C-H activation approach is presented. Derived from indolo[3,2,1-<i>jk</i>]carbazole, the incorporation of thiophene into the triarylamine framework significantly impacted the molecular properties of the parent scaffold. The developed thienopyrrolocarbazoles enrich the family of triarylamine donors and constitute a novel building block for functional organic materials.

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