scispace - formally typeset
P

Pengfei Xuan

Researcher at Clemson University

Publications -  20
Citations -  1125

Pengfei Xuan is an academic researcher from Clemson University. The author has contributed to research in topics: Data-intensive computing & Big data. The author has an hindex of 9, co-authored 18 publications receiving 980 citations. Previous affiliations of Pengfei Xuan include Chinese Academy of Sciences.

Papers
More filters
Journal ArticleDOI

The high-quality draft genome of peach ( Prunus persica ) identifies unique patterns of genetic diversity, domestication and genome evolution

TL;DR: Comparisons showed that peach has not undergone recent whole-genome duplication, and even though the ancestral triplicated blocks in peach are fragmentary compared to those in grape, all seven paleosets of paralogs from the putative paleoancestor are detectable.
Journal ArticleDOI

Field Effect on the Singlet and Triplet Exciton Formation in Organic/Polymeric Light-Emitting Diodes

TL;DR: In this article, a correlated quantum-chemical approach coupled with a first-order perturbation was applied to investigate the relationship between the formation ratio and the electric field, and it was found that for p-phenylene-vinylene oligomer, the formation rate of singlet excitons with respect to triplet exciton increases with the external electric field.
Journal ArticleDOI

Development of a 3D QSPR model for adsorption of aromatic compounds by carbon nanotubes: comparison of multiple linear regression, artificial neural network and support vector machine

TL;DR: In this paper, a 3D quantitative structure-property relationship (QSPR) model was developed by the utilization of 3D molecular structures of 39 aromatic compounds, and three different learning approaches, multiple linear regression (MLR), artificial neural network (ANN), and support vector machine (SVM) were used.
Journal ArticleDOI

A quantitative structure-activity relationship (QSAR) study on glycan array data to determine the specificities of glycan-binding proteins.

TL;DR: A novel quantitative structure-activity relationship (QSAR) method to analyze glycan array data and was able to effectively identify subtrees that indicate the binding specificities of a glycan-binding protein.
Journal ArticleDOI

Accelerating big data analytics on HPC clusters using two-level storage

TL;DR: A novel two-level storage system that integrates an upper-level in-memory file system with a lower-level parallel file system that renders memory-speed high I/O performance and the latter renders consistent storage with large capacity is presented.