QSAR without borders
EN Muratov, J Bajorath, RP Sheridan… - Chemical Society …, 2020 - pubs.rsc.org
Prediction of chemical bioactivity and physical properties has been one of the most
important applications of statistical and more recently, machine learning and artificial …
important applications of statistical and more recently, machine learning and artificial …
Machine learning‐driven biomaterials evolution
Biomaterials is an exciting and dynamic field, which uses a collection of diverse materials to
achieve desired biological responses. While there is constant evolution and innovation in …
achieve desired biological responses. While there is constant evolution and innovation in …
High-throughput methods in the discovery and study of biomaterials and materiobiology
The complex interaction of cells with biomaterials (ie, materiobiology) plays an increasingly
pivotal role in the development of novel implants, biomedical devices, and tissue …
pivotal role in the development of novel implants, biomedical devices, and tissue …
Materials genome in action: identifying the performance limits of physical hydrogen storage
The Materials Genome is in action: the molecular codes for millions of materials have been
sequenced, predictive models have been developed, and now the challenge of hydrogen …
sequenced, predictive models have been developed, and now the challenge of hydrogen …
Machine learning for polymeric materials: an introduction
Polymers are incredibly versatile materials and have become ubiquitous. Increasingly,
researchers are using data science and polymer informatics to design new materials and …
researchers are using data science and polymer informatics to design new materials and …
Automation and data-driven design of polymer therapeutics
Polymers are uniquely suited for drug delivery and biomaterial applications due to tunable
structural parameters such as length, composition, architecture, and valency. To facilitate …
structural parameters such as length, composition, architecture, and valency. To facilitate …
A user's guide to machine learning for polymeric biomaterials
The development of novel biomaterials is a challenging process, complicated by a design
space with high dimensionality. Requirements for performance in the complex biological …
space with high dimensionality. Requirements for performance in the complex biological …
Understanding the roles of the “two QSARs”
T Fujita, DA Winkler - Journal of chemical information and …, 2016 - ACS Publications
Quantitative structure–activity relationship (QSAR) modeling has matured over the past 50
years and has been very useful in discovering and optimizing drug leads. Although its roots …
years and has been very useful in discovering and optimizing drug leads. Although its roots …
Materials for stem cell factories of the future
Polymeric substrates are being identified that could permit translation of human pluripotent
stem cells from laboratory-based research to industrial-scale biomedicine. Well-defined …
stem cells from laboratory-based research to industrial-scale biomedicine. Well-defined …
High-throughput routes to biomaterials discovery
F Soheilmoghaddam, M Rumble… - Chemical …, 2021 - ACS Publications
Many existing clinical treatments are limited in their ability to completely restore decreased
or lost tissue and organ function, an unenviable situation only further exacerbated by a …
or lost tissue and organ function, an unenviable situation only further exacerbated by a …