Mondo: Unifying diseases for the world, by the world

Autor: Nicole A Vasilevsky, Nicolas A Matentzoglu, Sabrina Toro, Joseph E Flack, Harshad Hegde, Deepak R Unni, Gioconda F Alyea, Joanna S Amberger, Larry Babb, James P Balhoff, Taylor I Bingaman, Gully A Burns, Orion J Buske, Tiffany J Callahan, Leigh C Carmody, Paula Carrio Cordo, Lauren E Chan, George S Chang, Sean L Christiaens, Michel Dumontier, Laura E Failla, May J Flowers, H. Alpha Garrett, Jennifer L Goldstein, Dylan Gration, Tudor Groza, Marc Hanauer, Nomi L Harris, Jason A Hilton, Daniel S Himmelstein, Charles Tapley Hoyt, Megan S Kane, Sebastian Köhler, David Lagorce, Abbe Lai, Martin Larralde, Antonia Lock, Irene López Santiago, Donna R Maglott, Adriana J Malheiro, Birgit H M Meldal, Monica C Munoz-Torres, Tristan H Nelson, Frank W Nicholas, David Ochoa, Daniel P Olson, Tudor I Oprea, David Osumi-Sutherland, Helen Parkinson, Zoë May Pendlington, Ana Rath, Heidi L Rehm, Lyubov Remennik, Erin R Riggs, Paola Roncaglia, Justyne E Ross, Marion F Shadbolt, Kent A Shefchek, Morgan N Similuk, Nicholas Sioutos, Damian Smedley, Rachel Sparks, Ray Stefancsik, Ralf Stephan, Andrea L Storm, Doron Stupp, Gregory S Stupp, Jagadish Chandrabose Sundaramurthi, Imke Tammen, Darin Tay, Courtney L Thaxton, Eloise Valasek, Jordi Valls-Margarit, Alex H Wagner, Danielle Welter, Patricia L Whetzel, Lori L Whiteman, Valerie Wood, Colleen H Xu, Andreas Zankl, Xingmin Aaron Zhang, Christopher G Chute, Peter N Robinson, Christopher J Mungall, Ada Hamosh, Melissa A Haendel

There are thousands of distinct disease entities and concepts, each of which are known by different and sometimes contradictory names. The lack of a unified system for managing these entities poses a major challenge for both machines and humans that

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::eb95e9f275c4c5ac6590aa22f6896dbb
https://doi.org/10.1101/2022.04.13.22273750

Quantitative metaproteomics of patient fecal microbiota identifies host and microbial proteins associated with ulcerative colitis

Autor: Sandip Chatterjee, Coyle Wj, Andrew I. Su, Janice H Xu, Ana Y. Wang, Dennis W. Wolan, Peter S. Thuy-Boun, Gregory S. Stupp, Crissien-Martinez A

Mass spectrometry-based metaproteomics technologies enable the direct observation of proteins within complex multi-organism environments. A major hurdle in mapping metaproteomic fragmentation spectra to their corresponding peptides is the need for la

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2665ba0de4a4ccab3a109815d8682cbe
https://doi.org/10.1101/2020.11.11.378836

Quantitative Metaproteomics and Activity-based Protein Profiling of Patient Fecal Microbiome Identifies Host and Microbial Serine-type Endopeptidase Activity Associated With Ulcerative Colitis

Autor: Peter S. Thuy-Boun, Ana Y. Wang, Ana Crissien-Martinez, Janice H. Xu, Sandip Chatterjee, Gregory S. Stupp, Andrew I. Su, Walter J. Coyle, Dennis W. Wolan

Publikováno v: Molecular & Cellular Proteomics. 21:100197

The gut microbiota plays an important yet incompletely understood role in the induction and propagation of ulcerative colitis (UC). Organism-level efforts to identify UC-associated microbes have revealed the importance of community structure, but les

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::29c274a5c89aa5631d15053a4ff26ca0
https://doi.org/10.1016/j.mcpro.2022.100197

Structured Reviews for Data and Knowledge Driven Research

Autor: Tong Shu Li, Núria Queralt-Rosinach, Maureen E Hoatlin, Benjamin M. Good, Gregory S. Stupp, Andrew I. Su, Matthew Might, Michael Mayers

MotivationHypothesis generation is a critical step in research and a cornerstone in the rare disease field. Research is most efficient when those hypotheses are based on the entirety of knowledge known to date. Systematic review articles are commonly

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ebf2287368821374b446dee86887036d

13C Metabolomics: NMR and IROA for Unknown Identification

Autor: Timothy J. Garrett, Arthur S. Edison, Bing Wang, Gregory S. Stupp, Chaevien S. Clendinen

Publikováno v: Current Metabolomics

background Isotopic Ratio Outlier Analysis (IROA) is an untargeted metabolomics method that uses stable isotopic labeling and LC-HRMS for identification and relative quantification of metabolites in a biological sample under varying experimental cond

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4223e6723ceb896b2bf07d475d838bbc
https://doi.org/10.2174/2213235x04666160407212156