A critical overview of computational approaches employed for COVID-19 drug discovery
COVID-19 has resulted in huge numbers of infections and deaths worldwide and brought
the most severe disruptions to societies and economies since the Great Depression …
the most severe disruptions to societies and economies since the Great Depression …
Biolink Model: A universal schema for knowledge graphs in clinical, biomedical, and translational science
Within clinical, biomedical, and translational science, an increasing number of projects are
adopting graphs for knowledge representation. Graph‐based data models elucidate the …
adopting graphs for knowledge representation. Graph‐based data models elucidate the …
The National COVID Cohort Collaborative (N3C): rationale, design, infrastructure, and deployment
Abstract Objective Coronavirus disease 2019 (COVID-19) poses societal challenges that
require expeditious data and knowledge sharing. Though organizational clinical data are …
require expeditious data and knowledge sharing. Though organizational clinical data are …
Broad-coverage biomedical relation extraction with SemRep
Background In the era of information overload, natural language processing (NLP)
techniques are increasingly needed to support advanced biomedical information …
techniques are increasingly needed to support advanced biomedical information …
RTX-KG2: a system for building a semantically standardized knowledge graph for translational biomedicine
Background Biomedical translational science is increasingly using computational reasoning
on repositories of structured knowledge (such as UMLS, SemMedDB, ChEMBL, Reactome …
on repositories of structured knowledge (such as UMLS, SemMedDB, ChEMBL, Reactome …
Knowledge-based biomedical data science
Knowledge-based biomedical data science involves the design and implementation of
computer systems that act as if they knew about biomedicine. Such systems depend on …
computer systems that act as if they knew about biomedicine. Such systems depend on …
The case for open science: rare diseases
Abstract The premise of Open Science is that research and medical management will
progress faster if data and knowledge are openly shared. The value of Open Science is …
progress faster if data and knowledge are openly shared. The value of Open Science is …
Why rare disease needs precision medicine—and precision medicine needs rare disease
M Might, AB Crouse - Cell Reports Medicine, 2022 - cell.com
With one in ten suffering from one of 10,000 rare diseases, precision medicine opens a path
toward identifying therapies for rare patients. Conversely, it is rare patients—through their …
toward identifying therapies for rare patients. Conversely, it is rare patients—through their …
[HTML][HTML] Fast healthcare interoperability resources (FHIR) as a meta model to integrate common data models: development of a tool and quantitative validation study
ER Pfaff, J Champion, RL Bradford… - JMIR medical …, 2019 - medinform.jmir.org
Background In a multisite clinical research collaboration, institutions may or may not use the
same common data model (CDM) to store clinical data. To overcome this challenge, we …
same common data model (CDM) to store clinical data. To overcome this challenge, we …
Progress toward a universal biomedical data translator
Clinical, biomedical, and translational science has reached an inflection point in the breadth
and diversity of available data and the potential impact of such data to improve human …
and diversity of available data and the potential impact of such data to improve human …