Unleashing the power of knowledge extraction from scientific literature in catalysis

Y Zhang, C Wang, M Soukaseum… - Journal of Chemical …, 2022 - ACS Publications
Valuable knowledge of catalysis is often hidden in a large amount of scientific literature.
There is an urgent need to extract useful knowledge to facilitate scientific discovery. This …

Cascade processes with micellar reaction media: recent advances and future directions

C Tang, BT McInnes - Molecules, 2022 - mdpi.com
Reducing the use of solvents is an important aim of green chemistry. Using micelles self-
assembled from amphiphilic molecules dispersed in water (considered a green solvent) has …

A survey on event extraction for natural language understanding: Riding the biomedical literature wave

G Frisoni, G Moro, A Carbonaro - IEEE Access, 2021 - ieeexplore.ieee.org
Motivation: The scientific literature embeds an enormous amount of relational knowledge,
encompassing interactions between biomedical entities, like proteins, drugs, and symptoms …

Predictive chemistry augmented with text retrieval

Y Qian, Z Li, Z Tu, CW Coley, R Barzilay - arxiv preprint arxiv:2312.04881, 2023 - arxiv.org
This paper focuses on using natural language descriptions to enhance predictive models in
the chemistry field. Conventionally, chemoinformatics models are trained with extensive …

EnzChemRED, a rich enzyme chemistry relation extraction dataset

PT Lai, E Coudert, L Aimo, K Axelsen, L Breuza… - Scientific Data, 2024 - nature.com
Expert curation is essential to capture knowledge of enzyme functions from the scientific
literature in FAIR open knowledgebases but cannot keep pace with the rate of new …

Holistic approach for artificial intelligence implementation in pharmaceutical products lifecycle: a meta-analysis

KA Koshechkin, GS Lebedev, EN Fartushnyi… - Applied Sciences, 2022 - mdpi.com
Recent developments in Digital Medicine approaches concern pharmaceutical product
optimization. Artificial Intelligence (AI) has multiple applications for pharmaceutical products' …

Mining patents with large language models demonstrates congruence of functional labels and chemical structures

CW Kosonocky, CO Wilke, EM Marcotte… - arxiv preprint arxiv …, 2023 - arxiv.org
Predicting chemical function from structure is a major goal of the chemical sciences, from the
discovery and repurposing of novel drugs to the creation of new materials. Recently, new …

Mining patents with large language models elucidates the chemical function landscape

CW Kosonocky, CO Wilke, EM Marcotte… - Digital Discovery, 2024 - pubs.rsc.org
The fundamental goal of small molecule discovery is to generate chemicals with target
functionality. While this often proceeds through structure-based methods, we set out to …

Chemical identification and indexing in full-text articles: an overview of the NLM-Chem track at BioCreative VII

R Leaman, R Islamaj, V Adams, MA Alliheedi… - Database, 2023 - academic.oup.com
Abstract The BioCreative National Library of Medicine (NLM)-Chem track calls for a
community effort to fine-tune automated recognition of chemical names in the biomedical …

Ensemble of deep masked language models for effective named entity recognition in health and life science corpora

N Naderi, J Knafou, J Copara, P Ruch… - Frontiers in research …, 2021 - frontiersin.org
The health and life science domains are well known for their wealth of named entities found
in large free text corpora, such as scientific literature and electronic health records. To …