Quantitative ROESY analysis of computational models: structural studies of citalopram and β -cyclodextrin complexes by 1 H-NMR and computational methods

2015 ◽  
Vol 53 (7) ◽  
pp. 526-535 ◽  
Author(s):  
Syed Mashhood Ali ◽  
Shazia Shamim
Keyword(s):  
Computational Methods ◽  
Computational Models ◽  
Structural Studies ◽  
Cyclodextrin Complexes ◽  
H Nmr ◽  
Quantitative Roesy

Towards Computational Models of Identifying Protein Ubiquitination Sites

2019 ◽  
Vol 20 (5) ◽  
pp. 565-578 ◽  
Author(s):  
Lidong Wang ◽  
Ruijun Zhang
Keyword(s):  
Computational Methods ◽  
Computational Models ◽  
Feature Representation ◽  
Biological Sequence ◽  
Post Translational Modification ◽  
Test Dataset ◽  
Protein Ubiquitination ◽  
Protein Functions ◽  
Independent Test Dataset ◽  
Benchmark Datasets

Ubiquitination is an important post-translational modification (PTM) process for the regulation of protein functions, which is associated with cancer, cardiovascular and other diseases. Recent initiatives have focused on the detection of potential ubiquitination sites with the aid of physicochemical test approaches in conjunction with the application of computational methods. The identification of ubiquitination sites using laboratory tests is especially susceptible to the temporality and reversibility of the ubiquitination processes, and is also costly and time-consuming. It has been demonstrated that computational methods are effective in extracting potential rules or inferences from biological sequence collections. Up to the present, the computational strategy has been one of the critical research approaches that have been applied for the identification of ubiquitination sites, and currently, there are numerous state-of-the-art computational methods that have been developed from machine learning and statistical analysis to undertake such work. In the present study, the construction of benchmark datasets is summarized, together with feature representation methods, feature selection approaches and the classifiers involved in several previous publications. In an attempt to explore pertinent development trends for the identification of ubiquitination sites, an independent test dataset was constructed and the predicting results obtained from five prediction tools are reported here, together with some related discussions.

Computational Intelligence Approaches to Computational Aesthetics

2019 ◽  
pp. 81-92
Author(s):  
Erandi Lakshika ◽  
Michael Barlow
Keyword(s):  
Computational Methods ◽  
Computational Intelligence ◽  
Computational Models ◽  
Automatic Generation ◽  
Classification Problems ◽  
Future Directions ◽  
Simple Classification ◽  
Computational Aesthetics

Computational aesthetics is an area of research that attempts to develop computational methods that can perform human-like aesthetic judgements. Aesthetic judgements are often subjective, and as such, the development of computational models of aesthetics is highly challenging. This chapter summarizes the advancements in the area of computational aesthetics and how computational intelligence techniques are applied in art and aesthetics ranging from simple classification problems to more advanced problems such as automatic generation of art artefacts, stories, and simulations. The chapter concludes by summarizing major challenges that need to be addressed, and future directions that need to be undertaken in order to make significant advancements in the area of computational aesthetics and its applications.

Structural studies on the polysaccharide portion of "A-band" lipopolysaccharide from a mutant (AK1401) of Pseudomonas aeruginosa strain PAO1

1991 ◽  
Vol 69 (8) ◽  
pp. 1273-1280 ◽  
Author(s):  
Todd L. Arsenault ◽  
Donald W. Hughes ◽  
David B. MacLean ◽  
Walter A. Szarek ◽  
Andrew M. B. Kropinski ◽  
...  
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Structural Studies ◽  
Coherence Transfer ◽  
Strain Pao1 ◽  
Nmr Spectrum ◽  
H Nmr ◽  
Main Structural Feature ◽  
Nuclear Magnetic Resonance Spectra ◽  
Structure Formula ◽  
Nuclear Overhauser

AK1401 is a mutant of Pseudomonas aeruginosa strain PAO1 (serotype 05) that does not express O-antigen, but does express "A-band" lipopolysaccharide (LPS). The polysaccharide portion of the A-band LPS (A-PS) from AK1401 was found to consist mainly of D-rhamnose, with smaller amounts of 3-O-methylrhamnose, ribose, mannose, glucose, and a 3-O-methylhexose. 1H nuclear magnetic resonance spectra of the intact A-PS indicated that the main structural feature was a repeating trisaccharide of α-D-rhamnose having the following structure:[Formula: see text]The 1H NMR spectrum of the repeating unit was completely assigned through the use of 2D shift-correlated and relayed coherence transfer NMR spectroscopy. The linkage positions and sequence of residues were found by nuclear Overhauser enhancement difference spectroscopy. Key words: Pseudomonas aeruginosa, lipopolysaccharide, 1H NMR.

scholarly journals Platforms for publishing and archiving computer-aided research

F1000Research ◽  
2014 ◽  
Vol 3 ◽  
pp. 289 ◽  
Author(s):  
Konrad Hinsen
Keyword(s):  
Computational Methods ◽  
Computational Models ◽  
Journal Article ◽  
Scientific Research ◽  
Software Tools ◽  
Computing Environment ◽  
Scientific Software ◽  
Important Place ◽  
Computer Aided

Computational models and methods take an ever more important place in modern scientific research. At the same time, they are becoming ever more complex, to the point that many such models and methods can no longer be adequately described in the narrative of a traditional journal article. Often they exist only as part of scientific software tools, which causes two important problems: (1) software tools are much more complex than the models and methods they embed, making the latter unnecessarily difficult to understand, (2) software tools depend on minute details of the computing environment they were written for, making them difficult to deploy and often completely unusable after a few years. This article addresses the second problem, based on the experience gained from the development and use of a platform specifically designed to facilitate the integration of computational methods into the scientific record.

Comparison and integration of computational methods for deleterious synonymous mutation prediction

2019 ◽  
Vol 21 (3) ◽  
pp. 970-981 ◽  
Author(s):  
Na Cheng ◽  
Menglu Li ◽  
Le Zhao ◽  
Bo Zhang ◽  
Yuhua Yang ◽  
...  
Keyword(s):  
Computational Methods ◽  
Computational Models ◽  
Predictive Performance ◽  
Specific Method ◽  
Ensemble Model ◽  
Synonymous Mutation ◽  
Synonymous Mutations ◽  
Sequencing Technologies ◽  
Nucleotide Mutation ◽  
Mutation Prediction

Abstract Synonymous mutations do not change the encoded amino acids but may alter the structure or function of an mRNA in ways that impact gene function. Advances in next generation sequencing technologies have detected numerous synonymous mutations in the human genome. Several computational models have been proposed to predict deleterious synonymous mutations, which have greatly facilitated the development of this important field. Consequently, there is an urgent need to assess the state-of-the-art computational methods for deleterious synonymous mutation prediction to further advance the existing methodologies and to improve performance. In this regard, we systematically compared a total of 10 computational methods (including specific method for deleterious synonymous mutation and general method for single nucleotide mutation) in terms of the algorithms used, calculated features, performance evaluation and software usability. In addition, we constructed two carefully curated independent test datasets and accordingly assessed the robustness and scalability of these different computational methods for the identification of deleterious synonymous mutations. In an effort to improve predictive performance, we established an ensemble model, named Prediction of Deleterious Synonymous Mutation (PrDSM), which averages the ratings generated by the three most accurate predictors. Our benchmark tests demonstrated that the ensemble model PrDSM outperformed the reviewed tools for the prediction of deleterious synonymous mutations. Using the ensemble model, we developed an accessible online predictor, PrDSM, available at http://bioinfo.ahu.edu.cn:8080/PrDSM/. We hope that this comprehensive survey and the proposed strategy for building more accurate models can serve as a useful guide for inspiring future developments of computational methods for deleterious synonymous mutation prediction.

Structural studies of organoboron compounds. XIX. 1,7-Dimethyl-3,5-diphenyl-2,4,6-trioxa-7-aza-1-azonia-3-bora-5-boratabicyclo[3.3.0]octane

1984 ◽  
Vol 62 (3) ◽  
pp. 515-520 ◽  
Author(s):  
Wolfgang Kliegel ◽  
Steven J. Rettig ◽  
James Trotter
Keyword(s):  
Solid State ◽  
Least Squares ◽  
Variable Temperature ◽  
Direct Methods ◽  
Structural Studies ◽  
Organoboron Compounds ◽  
Full Matrix ◽  
Space Group ◽  
H Nmr ◽  
Valence Tautomers

Crystals of 1,7-dimethyl-3,5-diphenyl-2,4,6-trioxa-7-aza-1-azonia-3-bora-5-boratabicyclo[3.3.0]octane are triclinic, a = 10.559(2), b = 15.156(3), c = 10.338(2) Å, α = 99.14(1), β = 89.90(1), γ = 96.73(1)°, Z = 4, space group [Formula: see text]. The structure was solved by direct methods and was refined by full-matrix least-squares procedures to R = 0.032 and Rw = 0.038 for 2396 reflections with I ≥ 3σ(I). The structure consists of two crystallographically independent, but virtually identical, molecules containing sterically lengthened N—B coordinative bonds (mean 1.740(3) Å). The structurally inequivalent (in the solid state) pairs of N-methyl and B-phenyl groups are observed by variable temperature 1H nmr to be magnetically equivalent in solution, implying a rapid interconversion of "valence tautomers" at temperatures down to −60 °C.

scholarly journals Structural studies of B-type Aurora kinase inhibitors using computational methods

2010 ◽  
Vol 31 (2) ◽  
pp. 244-258 ◽  
Author(s):  
Mm Neaz ◽  
M Muddassar ◽  
Fa Pasha ◽  
Seung Joo Cho
Keyword(s):  
Computational Methods ◽  
Kinase Inhibitors ◽  
Aurora Kinase ◽  
Structural Studies ◽  
Aurora Kinase Inhibitors

Structural Studies of Native Paecilomyces sp. Exopolysaccharide

2007 ◽  
Vol 62 (9-10) ◽  
pp. 623-626
Author(s):  
Luis Lillo ◽  
Julio Alarcón ◽  
Gerardo Cabello ◽  
Sergio Águila
Keyword(s):  
Gel Permeation Chromatography ◽  
Structural Studies ◽  
H Nmr ◽  
Gel Permeation ◽  
C Nmr

A polysaccharide separated from Paecilomyces sp. was determined by gel permeation chromatography to be homogeneous. HPLC showed a monosaccharide containing d-glucose and d-fructose at a ratio of about 2:1. The results obtained from IR, 1H NMR, and 13C NMR analyses confirmed the proposed structure.

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