scholarly journals Photoredox Chemistry with Organic Catalysts: Role of Computational Methods

ACS Omega ◽  
2021 ◽  
Author(s):  
Kareesa J. Kron ◽  
Andres Rodriguez-Katakura ◽  
Rachelle Elhessen ◽  
Shaama Mallikarjun Sharada
Keyword(s):  
Computational Methods ◽  
Organic Catalysts

Role of MOFs as Electro/‐Organic Catalysts

2020 ◽  
pp. 109-120 ◽  
Author(s):  
Manorama Singh ◽  
Ankita Rai ◽  
Vijai K. Rai ◽  
Smita R. Bhardiya ◽  
Ambika Asati
Keyword(s):  
Organic Catalysts

scholarly journals Role of Computational Methods in Going beyond X-ray Crystallography to Explore Protein Structure and Dynamics

2018 ◽  
Vol 19 (11) ◽  
pp. 3401 ◽  
Author(s):  
Ashutosh Srivastava ◽  
Tetsuro Nagai ◽  
Arpita Srivastava ◽  
Osamu Miyashita ◽  
Florence Tama
Keyword(s):  
Protein Dynamics ◽  
Computational Methods ◽  
Protein Structures ◽  
Three Dimensional ◽  
Dimensional Structure ◽  
X Ray ◽  
X Ray Crystallography ◽  
Insight Into

Protein structural biology came a long way since the determination of the first three-dimensional structure of myoglobin about six decades ago. Across this period, X-ray crystallography was the most important experimental method for gaining atomic-resolution insight into protein structures. However, as the role of dynamics gained importance in the function of proteins, the limitations of X-ray crystallography in not being able to capture dynamics came to the forefront. Computational methods proved to be immensely successful in understanding protein dynamics in solution, and they continue to improve in terms of both the scale and the types of systems that can be studied. In this review, we briefly discuss the limitations of X-ray crystallography in studying protein dynamics, and then provide an overview of different computational methods that are instrumental in understanding the dynamics of proteins and biomacromolecular complexes.

scholarly journals DNA-binding mechanism of spiropyran photoswitches: the role of electrostatics

2019 ◽  
Vol 21 (17) ◽  
pp. 8614-8618 ◽  
Author(s):  
Davide Avagliano ◽  
Pedro A. Sánchez-Murcia ◽  
Leticia González
Keyword(s):  
Dna Binding ◽  
Computational Methods ◽  
Open Form ◽  
Binding Mechanism

The binding mechanism of the protonated open form of three spiropyran derivatives into a 12-mer (poly-dAT)2 has been unveiled by means of computational methods.

scholarly journals Shape-Based Classification of Partially Observed Curves, With Applications to Anthropology

2021 ◽  
Vol 7 ◽  
Author(s):  
Gregory J. Matthews ◽  
Karthik Bharath ◽  
Sebastian Kurtek ◽  
Juliet K. Brophy ◽  
George K. Thiruvathukal ◽  
...  
Keyword(s):  
Computational Methods ◽  
Nearest Neighbor ◽  
Training Data ◽  
Paleoenvironmental Reconstruction ◽  
Shape Information ◽  
Partially Observed ◽  
Nearest Neighbor Classifiers ◽  
Imputation Procedure

We consider the problem of classifying curves when they are observed only partially on their parameter domains. We propose computational methods for (i) completion of partially observed curves; (ii) assessment of completion variability through a nonparametric multiple imputation procedure; (iii) development of nearest neighbor classifiers compatible with the completion techniques. Our contributions are founded on exploiting the geometric notion of shape of a curve, defined as those aspects of a curve that remain unchanged under translations, rotations and reparameterizations. Explicit incorporation of shape information into the computational methods plays the dual role of limiting the set of all possible completions of a curve to those with similar shape while simultaneously enabling more efficient use of training data in the classifier through shape-informed neighborhoods. Our methods are then used for taxonomic classification of partially observed curves arising from images of fossilized Bovidae teeth, obtained from a novel anthropological application concerning paleoenvironmental reconstruction.

scholarly journals Linguistics in the digital humanities: (computational) corpus linguistics

2014 ◽  
Vol 30 (57) ◽  
pp. 20 ◽  
Author(s):  
Kim Ebensgaard Jensen
Keyword(s):  
Computational Methods ◽  
Computer Technology ◽  
Digital Technology ◽  
Corpus Linguistics ◽  
Digital Humanities ◽  
Intimate Relationship ◽  
History Of ◽  
The 1960S ◽  
Language Corpus

<p class="p1">Corpus linguistics has been closely intertwined with digital technology since the introduction of university computer mainframes in the 1960s. Making use of both digitized data in the form of the language corpus and computational methods of analysis involving concordancers and statistics software, corpus linguistics arguably has a place in the digital humanities. Still, it remains obscure and fi gures only sporadically in the literature on the digital humanities. Th is article provides an overview of the main principles of corpus linguistics and the role of computer technology in relation to data and method and also off ers a bird's-eye view of the history of corpus linguistics with a focus on its intimate relationship with digital technology and how digital technology has impacted the very core of corpus linguistics and shaped the identity of the corpus linguist. Ultimately, the article is oriented towards an acknowledgment of corpus linguistics' alignment with the digital humanities.</p>

scholarly journals On the role of aromatic-sugar interactions in the molecular recognition of carbohydrates: A 3D view by using NMR

2008 ◽  
Vol 80 (8) ◽  
pp. 1827-1835 ◽  
Author(s):  
M. Dolores Díaz ◽  
María del Carmen Fernández-Alonso ◽  
Gabriel Cuevas ◽  
F. Javier Cañada ◽  
Jesús Jiménez-Barbero
Keyword(s):  
Molecular Recognition ◽  
Computational Methods ◽  
Theoretical Approach ◽  
Different Levels

This revision describes an up-to-date review of our efforts to investigate the interaction of carbohydrates with aromatic moieties at different levels of complexity. Protein-sugar interactions have been studied using NMR experiments on a variety of hevein/chitooligosaccharide systems. In addition, NMR and computational methods have also been used to evaluate the interaction of simple aromatic entities with simple monosaccharides. In between, the stacking features of aromatic-containing glycomolecules have also been described by using an analogous experimental-theoretical approach.

Dielectric properties and the role of grain boundaries in polycrystalline tetracene at high pressures

CrystEngComm ◽  
2019 ◽  
Vol 21 (30) ◽  
pp. 4507-4512 ◽  
Author(s):  
Qinglin Wang ◽  
Dandan Sang ◽  
Shitai Guo ◽  
Xiaoli Wang ◽  
Wenjun Wang ◽  
...  
Keyword(s):  
Dielectric Properties ◽  
Grain Boundaries ◽  
Computational Methods ◽  
High Pressures

Dielectric properties and the role of grain boundaries in polycrystalline tetracene under pressure were investigated using impedance and computational methods.

Computing the Optimally Fitted Spike Train for a Synapse

2001 ◽  
Vol 13 (11) ◽  
pp. 2477-2494 ◽  
Author(s):  
Thomas Natschläger ◽  
Wolfgang Maass
Keyword(s):  
Experimental Data ◽  
Spike Train ◽  
Computational Methods ◽  
Temporal Pattern ◽  
Neural Circuits ◽  
Spike Trains ◽  
Functional Explanation ◽  
Synaptic Dynamics ◽  
Synaptic Parameters

Experimental data have shown that synapses are heterogeneous: different synapses respond with different sequences of amplitudes of postsynaptic responses to the same spike train. Neither the role of synaptic dynamics itself nor the role of the heterogeneity of synaptic dynamics for computations in neural circuits is well understood. We present in this article two computational methods that make it feasible to compute for a given synapse with known synaptic parameters the spike train that is optimally fitted to the synapse in a certain sense. With the help of these methods, one can compute, for example, the temporal pattern of a spike train (with a given number of spikes) that produces the largest sum of postsynaptic responses for a specific synapse. Several other applications are also discussed. To our surprise, we find that most of these optimally fitted spike trains match common firing patterns of specific types of neurons that are discussed in the literature. Hence, our analysis provides a possible functional explanation for the experimentally observed regularity in the combination of specific types of synapses with specific types of neurons in neural circuits.

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