8 papers
Mixing Vector Model for Copolymer Inference via Mixed Integer Linear Programming
Jianshen Zhu, Raveena Rai, Taiyo Sohkawa +4
A novel two-phase molecule inference framework, mol-infer, has recently been developed to infer chemical graphs with prescribed abstract structures and desired property values thro…
Enumeration of Tree-like Multigraphs with a Given Number of Vertices, Self-loops and Multiple Edges
Naveed Ahmed Azam, Seemab Hayat
Counting non-isomorphic tree-like multigraphs that include self-loops and multiple edges is an important problem in combinatorial enumeration, with applications in chemical graph t…
Combining Graph Neural Networks and Mixed Integer Linear Programming for Molecular Inference under the Two-Layered Model
Jianshen Zhu, Naveed Ahmed Azam, Kazuya Haraguchi +2
Recently, a novel two-phase framework named mol-infer for inference of chemical compounds with prescribed abstract structures and desired property values has been proposed. The fra…
Towards Environment-Sensitive Molecular Inference via Mixed Integer Linear Programming
Jianshen Zhu, Mao Takekida, Naveed Ahmed Azam +3
Traditional QSAR/QSPR and inverse QSAR/QSPR methods often assume that chemical properties are dictated by single molecules, overlooking the influence of molecular interactions and…
Counting Tree-Like Multigraphs with a Given Number of Vertices and Multiple Edges
Muhammad Ilyas, Seemab Hayat, Naveed Ahmed Azam
The enumeration of chemical graphs is an important topic in cheminformatics and bioinformatics, particularly in the discovery of novel drugs. These graphs are typically either tree…
A Method to Generate Multi-interval Pairwise Compatibility Graphs
Seemab Hayat, Naveed Ahmed Azam
Reconstruction of evolutionary relationships between species is an important topic in the field of computational biology. Pairwise compatibility graphs (PCGs) are used to model suc…