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Artigo Acesso aberto Produção Nacional
BIBTEX RIS

Reference Data Based Insights Expand Understanding of Human Metabolomes

2020; RELX Group (Netherlands); Linguagem: Inglês

10.2139/ssrn.3661950

ISSN

1556-5068

Autores

Julia M. Gauglitz, Wout Bittremieux, Candace L. Williams, Kelly C. Weldon, Morgan Panitchpakdi, Francesca Di Ottavio, Christine M. Aceves, Elizabeth A. R. Brown, Nicole Sikora, Alan K. Jarmusch, Cameron Martino, Anupriya Tripathi, Erfan Sayyari, Justin P. Shaffer, Roxana Coras, Fernando Vargas, Lindsay DeRight Goldasich, Tara Schwartz, MacKenzie Bryant, Gregory Humphrey, Abigail J. Johnson, Katharina Spengler, Pedro Belda‐Ferre, Edgar Diaz, Daniel McDonald, Qiyun Zhu, Dominic Nguyen, Emmanuel O. Elijah, Mingxun Wang, Clarisse Marotz, Kate E. Sprecher, Daniela Vargas-Robles, Dana Withrow, Gail Ackermann, Lourdes Herrera, B.J. Bradford, Lucas Maciel Mauriz Marques, Juliano Geraldo Amaral, Rodrigo Moreira da Silva, Flávio Protaso Veras, Thiago M. Cunha, Renê Donizeti Ribeiro de Oliveira, Paulo Louzada‐Júnior, Robert H. Mills, Douglas Galasko, Parambir S. Dulai, Curt Wittenberg, David J. Gonzalez, Robert Terkeltaub, Megan M. Doty, Jaehwan Kim, Kyung E. Rhee, Julia Beauchamp‐Walters, Kenneth P. Wright, María Gloria Domínguez-Bello, Mark Manary, Michelli F. Oliveira, Brigid S. Boland, Norberto Peporine Lopes, Mónica Gumá, Austin D. Swafford, Rachel J. Dutton, Rob Knight, Pieter C. Dorrestein,

Tópico(s)

Bioinformatics and Genomic Networks

Resumo

The human metabolome has remained largely unknown, with most studies annotating ~10% of features. In nucleic acid sequencing, annotating transcripts by source has proven essential for understanding gene function. Here we generalize this concept to stool, plasma, urine and other human metabolomes, discovering that food-based annotations increase the interpreted fraction of molecular features 7-fold, providing a general framework for expanding the interpretability of human metabolomic "dark matter."

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