Multi-omics integration in biomedical research–A metabolomics-centric review
Recent advances in high-throughput technologies have enabled the profiling of multiple
layers of a biological system, including DNA sequence data (genomics), RNA expression …
layers of a biological system, including DNA sequence data (genomics), RNA expression …
ConSIG: consistent discovery of molecular signature from OMIC data
The discovery of proper molecular signature from OMIC data is indispensable for
determining biological state, physiological condition, disease etiology, and therapeutic …
determining biological state, physiological condition, disease etiology, and therapeutic …
[HTML][HTML] Lipidomic signatures align with inflammatory patterns and outcomes in critical illness
Alterations in lipid metabolism have the potential to be markers as well as drivers of
pathobiology of acute critical illness. Here, we took advantage of the temporal precision …
pathobiology of acute critical illness. Here, we took advantage of the temporal precision …
[HTML][HTML] Bayesian network analysis reveals the interplay of intracranial aneurysm rupture risk factors
Clinical decision making regarding the treatment of unruptured intracranial aneurysms (IA)
benefits from a better understanding of the interplay of IA rupture risk factors. Probabilistic …
benefits from a better understanding of the interplay of IA rupture risk factors. Probabilistic …
The Florida Scoring System for stratifying children with suspected Sjögren's disease: a cross-sectional machine learning study
W Zeng, A Thatayatikom, N Winn… - The Lancet …, 2024 - thelancet.com
Summary Background Childhood Sjögren's disease is a rare, underdiagnosed, and poorly-
understood condition. By integrating machine learning models on a paediatric cohort in the …
understood condition. By integrating machine learning models on a paediatric cohort in the …
[HTML][HTML] Causal effects in microbiomes using interventional calculus
Causal inference in biomedical research allows us to shift the paradigm from investigating
associational relationships to causal ones. Inferring causal relationships can help in …
associational relationships to causal ones. Inferring causal relationships can help in …
[HTML][HTML] Essential regression: a generalizable framework for inferring causal latent factors from multi-omic datasets
High-dimensional cellular and molecular profiling of biological samples highlights the need
for analytical approaches that can integrate multi-omic datasets to generate prioritized …
for analytical approaches that can integrate multi-omic datasets to generate prioritized …
Towards Automated Causal Discovery: a case study on 5G telecommunication data
We introduce the concept of Automated Causal Discovery (AutoCD), defined as any system
that aims to fully automate the application of causal discovery and causal reasoning …
that aims to fully automate the application of causal discovery and causal reasoning …
Cellular and transcriptional profiles of peripheral blood mononuclear cells pre-vaccination predict immune response to preventative MUC1 vaccine
A single arm trial (NCT007773097) and a double-blind, placebo controlled randomized trial
(NCT02134925) were conducted in individuals with a history of advanced colonic adenoma …
(NCT02134925) were conducted in individuals with a history of advanced colonic adenoma …
Artificial intelligence and the risk for intuition decline in clinical medicine
A Duarte-Rojo, E Sejdic - Official journal of the American College …, 2022 - journals.lww.com
Artificial intelligence (AI) is revolutionizing big data analytics. In this issue of The American
Journal of Gastroenterology, Ahn et al. introduce the AI-cirrhosis-electrocardiogram score …
Journal of Gastroenterology, Ahn et al. introduce the AI-cirrhosis-electrocardiogram score …