Gilbert S. Omenn*, Sandra Orchard, Lydie Lane, Cecilia Lindskog, Charles Pineau, Christopher M. Overall, Bogdan Budnik, Jonathan M. Mudge, Nicolle H. Packer, Susan T. Weintraub, Michael H. A. Roehrl, Edouard Nice, Tiannan Guo, Jennifer E. Van Eyk, Uwe Völker, Gong Zhang, Nuno Bandeira, Ruedi Aebersold, Robert L. Moritz and Eric W. Deutsch*,
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引用次数: 0
Abstract
The Human Proteome Project (HPP), the flagship initiative of the Human Proteome Organization (HUPO), has pursued two goals: (1) to credibly identify at least one isoform of every protein-coding gene and (2) to make proteomics an integral part of multiomics studies of human health and disease. The past year has seen major transitions for the HPP. neXtProt was retired as the official HPP knowledge base, UniProtKB became the reference proteome knowledge base, and Ensembl-GENCODE provides the reference protein target list. A function evidence FE1–5 scoring system has been developed for functional annotation of proteins, parallel to the PE1–5 UniProtKB/neXtProt scheme for evidence of protein expression. This report includes updates from neXtProt (version 2023–09) and UniProtKB release 2024_04, with protein expression detected (PE1) for 18138 of the 19411 GENCODE protein-coding genes (93%). The number of non-PE1 proteins (“missing proteins”) is now 1273. The transition to GENCODE is a net reduction of 367 proteins (19,411 PE1–5 instead of 19,778 PE1–4 last year in neXtProt). We include reports from the Biology and Disease-driven HPP, the Human Protein Atlas, and the HPP Grand Challenge Project. We expect the new Functional Evidence FE1–5 scheme to energize the Grand Challenge Project for functional annotation of human proteins throughout the global proteomics community, including π-HuB in China.
期刊介绍:
Journal of Proteome Research publishes content encompassing all aspects of global protein analysis and function, including the dynamic aspects of genomics, spatio-temporal proteomics, metabonomics and metabolomics, clinical and agricultural proteomics, as well as advances in methodology including bioinformatics. The theme and emphasis is on a multidisciplinary approach to the life sciences through the synergy between the different types of "omics".