Predicting molecular conformations from molecular graphs is a fundamental problem in
cheminformatics and drug discovery. Recently, significant progress has been achieved with …

Drug discovery is a time-consuming and expensive process. With the development of
Artificial Intelligence (AI) techniques, molecular Geometric Deep Learning (GDL) has …

We study a fundamental problem in computational chemistry known as molecular
conformation generation, trying to predict stable 3D structures from 2D molecular graphs …

Biological age (BA) has been proposed to evaluate the aging status instead of chronological
age (CA). Our study shows evidence that there might be multiple" clocks" within the whole …

The computational prediction of atomistic structure is a long-standing problem in physics,
chemistry, materials, and biology. Conventionally, force-fields or ab initio methods determine …

Euclidean distance matrices (EDMs) are matrices of the squared distances between points.
The definition is deceivingly simple; thanks to their many useful properties, they have found …

Predicting molecular conformations (or 3D structures) from molecular graphs is a
fundamental problem in many applications. Most existing approaches are usually divided …

The occurrence of coronavirus (COVID-19) is greater than that of 2003 representing
respiratory infections syndrome (SARS). As of 12 August 2020, the reported cases are more …

In recent years, optimization theory has been greatly impacted by the advent of sum of
squares (SOS) optimization. The reliance of this technique on large-scale semidefinite …

With growing penetrations of wind power in electricity systems, the coordinated dispatch of
integrated electricity and natural gas systems is becoming a popular research topic …