Can graph neural networks count substructures?

Z Chen, L Chen, S Villar… - Advances in neural …, 2020 - proceedings.neurips.cc
The ability to detect and count certain substructures in graphs is important for solving many
tasks on graph-structured data, especially in the contexts of computational chemistry and …

[HTML][HTML] Open source molecular modeling

S Pirhadi, J Sunseri, DR Koes - Journal of Molecular Graphics and …, 2016 - Elsevier
The success of molecular modeling and computational chemistry efforts are, by definition,
dependent on quality software applications. Open source software development provides …

ClassyFire: automated chemical classification with a comprehensive, computable taxonomy

Y Djoumbou Feunang, R Eisner, C Knox… - Journal of …, 2016 - Springer
Background Scientists have long been driven by the desire to describe, organize, classify,
and compare objects using taxonomies and/or ontologies. In contrast to biology, geology …

The Chemistry Development Kit (CDK) v2. 0: atom ty**, depiction, molecular formulas, and substructure searching

EL Willighagen, JW Mayfield, J Alvarsson… - Journal of …, 2017 - Springer
Abstract Background The Chemistry Development Kit (CDK) is a widely used open source
cheminformatics toolkit, providing data structures to represent chemical concepts along with …

Sha** the interaction landscape of bioactive molecules

D Gfeller, O Michielin, V Zoete - Bioinformatics, 2013 - academic.oup.com
Motivation: Most bioactive molecules perform their action by interacting with proteins or other
macromolecules. However, for a significant fraction of them, the primary target remains …

ChemMine tools: an online service for analyzing and clustering small molecules

TWH Backman, Y Cao, T Girke - Nucleic acids research, 2011 - academic.oup.com
ChemMine Tools is an online service for small molecule data analysis. It provides a web
interface to a set of cheminformatics and data mining tools that are useful for various …

Computational biology in the 21st century: Scaling with compressive algorithms

B Berger, NM Daniels, YW Yu - Communications of the ACM, 2016 - dl.acm.org
Computational biology in the 21st century: scaling with compressive algorithms Page 1 72
COMMUNICATIONS OF THE ACM | AUGUST 2016 | VOL. 59 | NO. 8 review articles DOI:10.1145/2957324 …

Predicting cancer drug response using a recommender system

C Suphavilai, D Bertrand, N Nagarajan - Bioinformatics, 2018 - academic.oup.com
Motivation As we move toward an era of precision medicine, the ability to predict patient-
specific drug responses in cancer based on molecular information such as gene expression …

Polyketide and nonribosomal peptide retro-biosynthesis and global gene cluster matching

CA Dejong, GM Chen, H Li, CW Johnston… - Nature chemical …, 2016 - nature.com
Polyketides (PKs) and nonribosomal peptides (NRPs) are profoundly important natural
products, forming the foundations of many therapeutic regimes. Decades of research have …

Making sense of chemical space network shows signs of criticality

N Amoroso, N Gambacorta, F Mastrolorito, MV Togo… - Scientific Reports, 2023 - nature.com
Chemical space modelling has great importance in unveiling and visualising latent
information, which is critical in predictive toxicology related to drug discovery process. While …