Pre-trained language models in biomedical domain: A systematic survey
Pre-trained language models (PLMs) have been the de facto paradigm for most natural
language processing tasks. This also benefits the biomedical domain: researchers from …
language processing tasks. This also benefits the biomedical domain: researchers from …
Unexplored therapeutic opportunities in the human genome
A large proportion of biomedical research and the development of therapeutics is focused
on a small fraction of the human genome. In a strategic effort to map the knowledge gaps …
on a small fraction of the human genome. In a strategic effort to map the knowledge gaps …
Galactica: A large language model for science
Information overload is a major obstacle to scientific progress. The explosive growth in
scientific literature and data has made it ever harder to discover useful insights in a large …
scientific literature and data has made it ever harder to discover useful insights in a large …
A knowledge graph to interpret clinical proteomics data
Implementing precision medicine hinges on the integration of omics data, such as
proteomics, into the clinical decision-making process, but the quantity and diversity of …
proteomics, into the clinical decision-making process, but the quantity and diversity of …
BioBERT: a pre-trained biomedical language representation model for biomedical text mining
Motivation Biomedical text mining is becoming increasingly important as the number of
biomedical documents rapidly grows. With the progress in natural language processing …
biomedical documents rapidly grows. With the progress in natural language processing …
miRBase: from microRNA sequences to function
A Kozomara, M Birgaoanu… - Nucleic acids …, 2019 - academic.oup.com
Abstract miRBase catalogs, names and distributes microRNA gene sequences. The latest
release of miRBase (v22) contains microRNA sequences from 271 organisms: 38 589 …
release of miRBase (v22) contains microRNA sequences from 271 organisms: 38 589 …
Pretrained language models for biomedical and clinical tasks: understanding and extending the state-of-the-art
A large array of pretrained models are available to the biomedical NLP (BioNLP) community.
Finding the best model for a particular task can be difficult and time-consuming. For many …
Finding the best model for a particular task can be difficult and time-consuming. For many …
DrugCentral 2021 supports drug discovery and repositioning
DrugCentral is a public resource (http://drugcentral. org) that serves the scientific community
by providing up-to-date drug information, as described in previous papers. The current …
by providing up-to-date drug information, as described in previous papers. The current …
Deep learning with word embeddings improves biomedical named entity recognition
Motivation Text mining has become an important tool for biomedical research. The most
fundamental text-mining task is the recognition of biomedical named entities (NER), such as …
fundamental text-mining task is the recognition of biomedical named entities (NER), such as …
The SIDER database of drugs and side effects
Unwanted side effects of drugs are a burden on patients and a severe impediment in the
development of new drugs. At the same time, adverse drug reactions (ADRs) recorded …
development of new drugs. At the same time, adverse drug reactions (ADRs) recorded …