38 citations · 83 across the 6 of their papers we have counts for
6 papers
Prediction of Protein Aggregation Propensity via Data-driven Approaches
Seungpyo Kang, Minseon Kim, Jiwon Sun +2
Protein aggregation occurs when misfolded or unfolded proteins physically bind together, and can promote the development of various amyloid diseases. This study aimed to construct…
AmorProt: Amino Acid Molecular Fingerprints Repurposing based Protein Fingerprint
Myeonghun Lee, Kyoungmin Min
As protein therapeutics play an important role in almost all medical fields, numerous studies have been conducted on proteins using artificial intelligence. Artificial intelligence…
MGCVAE: Multi-objective Inverse Design via Molecular Graph Conditional Variational Autoencoder
Myeonghun Lee, Kyoungmin Min
The ultimate goal of various fields is to directly generate molecules with desired properties, such as finding water-soluble molecules in drug development and finding molecules sui…
Machine Learning-Aided Discovery of Superionic Solid-State Electrolyte for Li-Ion Batteries
Seungpyo Kang, Minseon Kim, Kyoungmin Min
Li-Ion Solid-State Electrolytes (Li-SSEs) are a promising solution that resolves the critical issues of conventional Li-Ion Batteries (LIBs) such as poor ionic conductivity, interf…
Machine learning aided materials design platform for predicting the mechanical properties of Na-ion solid-state electrolytes
Junho Jo, Eunseong Choi, Minseon Kim +1
Na-ion solid-state electrolytes (Na-SSE) exhibit high potential for electrical energy storage owing to their high energy densities and low manufacturing cost. However, their mechan…
Capacitive Sensing of Intercalated H2O Molecules Using Graphene
Eric J. Olson, Rui Ma, Tao Sun +5
Understanding the interactions of ambient molecules with graphene and adjacent dielectrics is of fundamental importance for a range of graphene-based devices, particularly sensors,…