Cognitive analysis of metabolomics data for systems biology

Erica L.-W. Majumder, Elizabeth M. Billings, H. Paul Benton, Richard L. Martin, Amelia Palermo, Carlos Guijas, Markus M. Rinschen, Xavier Domingo-Almenara, J. Rafael Montenegro-Burke, Bradley A. Tagtow, Robert S. Plumb, Gary Siuzdak

Published: 2021-01-21 DOI: 10.1038/s41596-020-00455-4

Cognitive Computing

Metabolomics

NLP

Systems Biology

Biomarker Discovery

AI 解读

Author Correction: Full-length sequencing of circular DNA viruses and extrachromosomal circular DNA using CIDER-Seq

Generation of heart-forming organoids from human pluripotent stem cells

Design and fabrication of wearable electronic textiles using twisted fiber-based threads

Activation of mechanoluminescent nanotransducers by focused ultrasound enables light delivery to deep-seated tissue in vivo

Chromatin accessibility profiling by ATAC-seq

Deoxyfluorination of phenols for chemoselective18F-labeling of peptides

Author Correction: cfSNV: a software tool for the sensitive detection of somatic mutations from cell-free DNA

Human primordial germ cell-like cells specified from resetting precursors develop in human hindgut organoids

An inexpensive semi-automated sample processing pipeline for cell-free RNA extraction

Application of CHyMErA Cas9-Cas12a combinatorial genome-editing platform for genetic interaction mapping and gene fragment deletion screening

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Cognitive computing is revolutionizing the way big data are processed and integrated, with artificial intelligence (AI) natural language processing (NLP) platforms helping researchers to efficiently search and digest the vast scientific literature. Most a
Introduction
Materials
Procedure 1
Procedure 2
- Biological contextualization of metabolomics-predicted pathways
Procedure 3
- Metabolome-level disease comparison for biomarker discovery
- Comparison of scores across sets
Procedure 4
- Metabolome-level disease comparison for drug repurposing
Troubleshooting
Timing
Anticipated results
References
ACKNOWLEDGMENTS

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Cognitive analysis of metabolomics data for systems biology

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