Development of Inspired Therapeutics Pediatric VAD: Computational Analysis and Characterization of VAD V3

2022 ◽  
Author(s):  
Landon H. Tompkins ◽  
Barry N. Gellman ◽  
Steven R. Prina ◽  
Gino F. Morello ◽  
Thomas Roussel ◽  
...  
Keyword(s):  
Computational Analysis

scholarly journals RA3 is a reference-guided approach for epigenetic characterization of single cells

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Shengquan Chen ◽  
Guanao Yan ◽  
Wenyu Zhang ◽  
Jinzhao Li ◽  
Rui Jiang ◽  
...  
Keyword(s):  
Single Cell ◽  
Computational Analysis ◽  
Reference Data ◽  
Single Cells ◽  
Chromatin Accessibility ◽  
Biological Variation ◽  
Superior Performance ◽  
High Dimensionality ◽  
High Degree

AbstractThe recent advancements in single-cell technologies, including single-cell chromatin accessibility sequencing (scCAS), have enabled profiling the epigenetic landscapes for thousands of individual cells. However, the characteristics of scCAS data, including high dimensionality, high degree of sparsity and high technical variation, make the computational analysis challenging. Reference-guided approaches, which utilize the information in existing datasets, may facilitate the analysis of scCAS data. Here, we present RA3 (Reference-guided Approach for the Analysis of single-cell chromatin Accessibility data), which utilizes the information in massive existing bulk chromatin accessibility and annotated scCAS data. RA3 simultaneously models (1) the shared biological variation among scCAS data and the reference data, and (2) the unique biological variation in scCAS data that identifies distinct subpopulations. We show that RA3 achieves superior performance when used on several scCAS datasets, and on references constructed using various approaches. Altogether, these analyses demonstrate the wide applicability of RA3 in analyzing scCAS data.

scholarly journals Computational analysis and characterization of UCE-like elements (ULEs) in plant genomes

2012 ◽  
Vol 22 (12) ◽  
pp. 2455-2466 ◽  
Author(s):  
K. Kritsas ◽  
S. E. Wuest ◽  
D. Hupalo ◽  
A. D. Kern ◽  
T. Wicker ◽  
...  
Keyword(s):  
Computational Analysis ◽  
Plant Genomes

Computational analysis and physico-chemical characterization of an inclusion compound between praziquantel and methyl-β-cyclodextrin for use as an alternative in the treatment of schistosomiasis

2010 ◽  
Vol 70 (1-2) ◽  
pp. 19-28 ◽  
Author(s):  
Stella Gomes Rodrigues ◽  
Izabel de Souza Chaves ◽  
Nathalie Ferreira Silva Melo ◽  
Marcelo Bispo Jesus ◽  
Leonardo Fernandes Fraceto ◽  
...  
Keyword(s):  
Inclusion Compound ◽  
Computational Analysis ◽  
Chemical Characterization ◽  
Physico Chemical

scholarly journals SYNTHESIS, CRYSTAL STRUCTURE, HIRSHFELD SURFACE ANALYSIS AND QUANTUM CHEMICAL CALCULATIONS OF [Cu2(C6H9N3S)2(ClO4)2] π-COMPLEX WITH 2-ALLYLAMINO-5-METHYL-1,3,4-THIADIAZOLE

2021 ◽  
Vol 26 (1(77)) ◽  
pp. 16-25
Author(s):  
Yu. I. Slyvka ◽  
E. A. Goreshnik ◽  
N. T. Pokhodylo ◽  
М. G. Mys’kiv
Keyword(s):  
Crystal Structure ◽  
Computational Analysis ◽  
Structure Characterization ◽  
Electrochemical Technique ◽  
The Novel ◽  
X Ray Diffraction ◽  
X Ray ◽  
Π Complex ◽  
Centrosymmetric Dimers

This work is focused on the synthesis and structure characterization of the novel Cu(I) π-complex [Cu2(Thiaz1)2(ClO4)2] (1) with 2-allylamino-5-methyl-1,3,4-thiadiazole (Thiaz1) ligand. The crystals of the compound were obtained by means of the alternating-current electrochemical technique and studied using single crystal X-ray diffraction. The crystal structure of the complex 1 is constructed from the centrosymmetric dimers, in which two copper(I) ions are coordinated by two Thiaz1 molecules through thiadiazole N atoms and allylic C=C bond. Energy framework computational analysis for structure 1 has been performed.  

scholarly journals A reference-guided approach for epigenetic characterization of single cells

2020 ◽  
Author(s):  
Shengquan Chen ◽  
Guanao Yan ◽  
Wenyu Zhang ◽  
Jinzhao Li ◽  
Rui Jiang ◽  
...  
Keyword(s):  
Single Cell ◽  
Computational Analysis ◽  
Reference Data ◽  
Single Cells ◽  
Chromatin Accessibility ◽  
Biological Variation ◽  
Superior Performance ◽  
High Dimensionality ◽  
High Degree

AbstractThe recent advancements in single-cell technologies, including single-cell chromatin accessibility sequencing (scCAS), have enabled profiling the epigenetic landscapes for thousands of individual cells. However, the characteristics of scCAS data, including high dimensionality, high degree of sparsity and high technical variation, make the computational analysis challenging. Reference-guided approach, which utilizes the information in existing datasets, may facilitate the analysis of scCAS data. We present RA3 (Reference-guided Approach for the Analysis of single-cell chromatin Acessibility data), which utilizes the information in massive existing bulk chromatin accessibility and annotated scCAS data. RA3 simultaneously models 1) the shared biological variation among scCAS data and the reference data, and 2) the unique biological variation in scCAS data that identifies distinct subpopulations. We show that RA3 achieves superior performance in many scCAS datasets. We also present several approaches to construct the reference data to demonstrate the wide applicability of RA3.

scholarly journals Structural and Computational Characterization of Disease-Related Mutations Involved in Protein-Protein Interfaces

2019 ◽  
Vol 20 (7) ◽  
pp. 1583 ◽  
Author(s):  
Dàmaris Navío ◽  
Mireia Rosell ◽  
Josu Aguirre ◽  
Xavier de la Cruz ◽  
Juan Fernández-Recio
Keyword(s):  
Protein Interactions ◽  
Computational Analysis ◽  
Molecular Level ◽  
Binding Free Energy ◽  
Evolutionary Conservation ◽  
Core Region ◽  
Protein Protein Interactions ◽  
The Core ◽  
Protein Interfaces

One of the known potential effects of disease-causing amino acid substitutions in proteins is to modulate protein-protein interactions (PPIs). To interpret such variants at the molecular level and to obtain useful information for prediction purposes, it is important to determine whether they are located at protein-protein interfaces, which are composed of two main regions, core and rim, with different evolutionary conservation and physicochemical properties. Here we have performed a structural, energetics and computational analysis of interactions between proteins hosting mutations related to diseases detected in newborn screening. Interface residues were classified as core or rim, showing that the core residues contribute the most to the binding free energy of the PPI. Disease-causing variants are more likely to occur at the interface core region rather than at the interface rim (p < 0.0001). In contrast, neutral variants are more often found at the interface rim or at the non-interacting surface rather than at the interface core region. We also found that arginine, tryptophan, and tyrosine are over-represented among mutated residues leading to disease. These results can enhance our understanding of disease at molecular level and thus contribute towards personalized medicine by helping clinicians to provide adequate diagnosis and treatments.

Characterization of Lithium-Ion Battery Thermal Abuse Behavior Using Experimental and Computational Analysis

2015 ◽  
Vol 162 (10) ◽  
pp. A2163-A2173 ◽  
Author(s):  
Carlos F. Lopez ◽  
Judith A. Jeevarajan ◽  
Partha P. Mukherjee
Keyword(s):  
Lithium Ion Battery ◽  
Computational Analysis ◽  
Lithium Ion
Sign in / Sign up

Export Citation Format

Share Document