New developments in RiPP discovery, enzymology and engineering
M Montalbán-López, TA Scott, S Ramesh… - Natural product …, 2021 - pubs.rsc.org
Covering: up to June 2020 Ribosomally-synthesized and post-translationally modified
peptides (RiPPs) are a large group of natural products. A community-driven review in 2013 …
peptides (RiPPs) are a large group of natural products. A community-driven review in 2013 …
[HTML][HTML] Artificial intelligence in cancer target identification and drug discovery
Artificial intelligence is an advanced method to identify novel anticancer targets and discover
novel drugs from biology networks because the networks can effectively preserve and …
novel drugs from biology networks because the networks can effectively preserve and …
Applications of deep learning in molecule generation and molecular property prediction
WP Walters, R Barzilay - Accounts of chemical research, 2020 - ACS Publications
Conspectus Recent advances in computer hardware and software have led to a revolution
in deep neural networks that has impacted fields ranging from language translation to …
in deep neural networks that has impacted fields ranging from language translation to …
[HTML][HTML] Network pharmacology databases for traditional Chinese medicine: review and assessment
The research field of systems biology has greatly advanced and, as a result, the concept of
network pharmacology has been developed. This advancement, in turn, has shifted the …
network pharmacology has been developed. This advancement, in turn, has shifted the …
[HTML][HTML] A deep-learning system bridging molecule structure and biomedical text with comprehension comparable to human professionals
To accelerate biomedical research process, deep-learning systems are developed to
automatically acquire knowledge about molecule entities by reading large-scale biomedical …
automatically acquire knowledge about molecule entities by reading large-scale biomedical …
[HTML][HTML] Big data and artificial intelligence modeling for drug discovery
H Zhu - Annual review of pharmacology and toxicology, 2020 - annualreviews.org
Due to the massive data sets available for drug candidates, modern drug discovery has
advanced to the big data era. Central to this shift is the development of artificial intelligence …
advanced to the big data era. Central to this shift is the development of artificial intelligence …
[HTML][HTML] Review of drug repositioning approaches and resources
Drug discovery is a time-consuming, high-investment, and high-risk process in traditional
drug development. Drug repositioning has become a popular strategy in recent years …
drug development. Drug repositioning has become a popular strategy in recent years …
Toward autonomous laboratories: Convergence of artificial intelligence and experimental automation
The ever-increasing demand for novel materials with superior properties inspires retrofitting
traditional research paradigms in the era of artificial intelligence and automation. An …
traditional research paradigms in the era of artificial intelligence and automation. An …
MolTrans: molecular interaction transformer for drug–target interaction prediction
Motivation Drug–target interaction (DTI) prediction is a foundational task for in-silico drug
discovery, which is costly and time-consuming due to the need of experimental search over …
discovery, which is costly and time-consuming due to the need of experimental search over …
A multimodal deep learning framework for predicting drug–drug interaction events
Abstract Motivation Drug–drug interactions (DDIs) are one of the major concerns in
pharmaceutical research. Many machine learning based methods have been proposed for …
pharmaceutical research. Many machine learning based methods have been proposed for …