AI Medical Compendium Journal:
Chemical science

Showing 41 to 50 of 55 articles

Learning continuous and data-driven molecular descriptors by translating equivalent chemical representations.

Chemical science
There has been a recent surge of interest in using machine learning across chemical space in order to predict properties of molecules or design molecules and materials with the desired properties. Most of this work relies on defining clever feature r...

Nucleotide and structural label identification in single RNA molecules with quantum tunneling spectroscopy.

Chemical science
Although a number of advances have been made in RNA sequencing and structural characterization, the lack of a method for directly determining the sequence and structure of single RNA molecules has limited our ability to probe heterogeneity in gene ex...

Antimicrobial peptide based magnetic recognition elements and Au@Ag-GO SERS tags with stable internal standards: a three in one biosensor for isolation, discrimination and killing of multiple bacteria in whole blood.

Chemical science
In this study, a new biosensor based on a sandwich structure has been developed for the isolation and detection of multiple bacterial pathogens magnetic separation and SERS tags. This novel assay relies on antimicrobial peptide (AMP) functionalized ...

Machine learning of optical properties of materials - predicting spectra from images and images from spectra.

Chemical science
As the materials science community seeks to capitalize on recent advancements in computer science, the sparsity of well-labelled experimental data and limited throughput by which it can be generated have inhibited deployment of machine learning algor...

Atomic structure of boron resolved using machine learning and global sampling.

Chemical science
Boron crystals, despite their simple composition, must rank top for complexity: even the atomic structure of the ground state of β-B remains uncertain after 60 years' study. This makes it difficult to understand the many exotic photoelectric properti...

Machine learning for the structure-energy-property landscapes of molecular crystals.

Chemical science
Molecular crystals play an important role in several fields of science and technology. They frequently crystallize in different polymorphs with substantially different physical properties. To help guide the synthesis of candidate materials, atomic-sc...

MoleculeNet: a benchmark for molecular machine learning.

Chemical science
Molecular machine learning has been maturing rapidly over the last few years. Improved methods and the presence of larger datasets have enabled machine learning algorithms to make increasingly accurate predictions about molecular properties. However,...

Machine learning for quantum dynamics: deep learning of excitation energy transfer properties.

Chemical science
Understanding the relationship between the structure of light-harvesting systems and their excitation energy transfer properties is of fundamental importance in many applications including the development of next generation photovoltaics. Natural lig...

Synthesis of poly(1,2-glycerol carbonate)-paclitaxel conjugates and their utility as a single high-dose replacement for multi-dose treatment regimens in peritoneal cancer.

Chemical science
Current chemotherapeutic dosing strategies are limited by the toxicity of anticancer agents and therefore rely on multiple low-dose administrations. As an alternative, we describe a novel sustained-release, biodegradable polymeric nanocarrier as a si...

Teixobactin analogues reveal enduracididine to be non-essential for highly potent antibacterial activity and lipid II binding.

Chemical science
Teixobactin is a highly promising antibacterial depsipeptide consisting of four d-amino acids and a rare l--enduracididine amino acid. l--Enduracididine is reported to be important for the highly potent antibacterial activity of teixobactin. However,...