Literature DB >> 30191714

Exploring the Uncharacterized Human Proteome Using neXtProt.

Paula Duek, Alain Gateau, Amos Bairoch, Lydie Lane.   

Abstract

20,230 protein-coding genes have been predicted from the analysis of the human genome (neXtProt release 2018-01-17), and about 10% of them are still lacking functional annotation, either predicted by bioinformatics tools or captured from experimental reports. A systematic exploration of the available literature on uncharacterized human genes/proteins led to proposal of functional annotations for 113 proteins and to consolidation of a list of 1,862 uncharacterized human proteins. The advanced search functionality of neXtProt was used extensively in order to examine the landscape of the uncharacterized human proteome in terms of subcellular locations, protein-protein interactions, tissue expression, association with diseases, and 3D structure. Finally, a deep data mining in various publicly available resources allowed building functional hypotheses for 26 uncharacterized human proteins validated at protein level (uPE1). These hypotheses cover the fields of cilia biology, male reproduction, metabolism, nervous system, immunity, inflammation, RNA metabolism, and chromatin biology. They will require experimental validation before they can be considered for annotation. Despite technological progresses, the pace of human protein characterization studies is still slow. It could be accelerated by a better integration of existing knowledge resources and by initiating large collaborative projects involving specialists of different biology fields. We hope that our analysis will contribute to set up the ground for such collaborative approaches and will be exploited by the HUPO Human Proteome Project teams committed to characterize uPE1 proteins.

Entities:  

Keywords:  SPARQL; biocuration; cilium biology; data mining; functional annotation; human protein; knowledge base; neXtProt; systems biology

Mesh:

Substances:

Year:  2018        PMID: 30191714     DOI: 10.1021/acs.jproteome.8b00537

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  9 in total

1.  Flexible and Fast Mapping of Peptides to a Proteome with ProteoMapper.

Authors:  Luis Mendoza; Eric W Deutsch; Zhi Sun; David S Campbell; David D Shteynberg; Robert L Moritz
Journal:  J Proteome Res       Date:  2018-09-28       Impact factor: 4.466

2.  Progress on Identifying and Characterizing the Human Proteome: 2019 Metrics from the HUPO Human Proteome Project.

Authors:  Gilbert S Omenn; Lydie Lane; Christopher M Overall; Fernando J Corrales; Jochen M Schwenk; Young-Ki Paik; Jennifer E Van Eyk; Siqi Liu; Stephen Pennington; Michael P Snyder; Mark S Baker; Eric W Deutsch
Journal:  J Proteome Res       Date:  2019-09-13       Impact factor: 4.466

3.  Blinded Testing of Function Annotation for uPE1 Proteins by I-TASSER/COFACTOR Pipeline Using the 2018-2019 Additions to neXtProt and the CAFA3 Challenge.

Authors:  Chengxin Zhang; Lydie Lane; Gilbert S Omenn; Yang Zhang
Journal:  J Proteome Res       Date:  2019-10-18       Impact factor: 4.466

4.  A hands-on introduction to querying evolutionary relationships across multiple data sources using SPARQL.

Authors:  Ana Claudia Sima; Christophe Dessimoz; Kurt Stockinger; Monique Zahn-Zabal; Tarcisio Mendes de Farias
Journal:  F1000Res       Date:  2019-10-29

5.  Predicting Functions of Uncharacterized Human Proteins: From Canonical to Proteoforms.

Authors:  Ekaterina Poverennaya; Olga Kiseleva; Anastasia Romanova; Mikhail Pyatnitskiy
Journal:  Genes (Basel)       Date:  2020-06-21       Impact factor: 4.096

6.  Protein kinase Cα regulates the nucleocytoplasmic shuttling of KRIT1.

Authors:  Elisa De Luca; Andrea Perrelli; Harsha Swamy; Mariapaola Nitti; Mario Passalacqua; Anna Lisa Furfaro; Anna Maria Salzano; Andrea Scaloni; Angela J Glading; Saverio Francesco Retta
Journal:  J Cell Sci       Date:  2021-02-04       Impact factor: 5.285

7.  Co-evolution based machine-learning for predicting functional interactions between human genes.

Authors:  Doron Stupp; Elad Sharon; Idit Bloch; Marinka Zitnik; Or Zuk; Yuval Tabach
Journal:  Nat Commun       Date:  2021-11-09       Impact factor: 14.919

8.  Combined RNA/tissue profiling identifies novel Cancer/testis genes.

Authors:  Soazik P Jamin; Feria Hikmet; Romain Mathieu; Bernard Jégou; Cecilia Lindskog; Frédéric Chalmel; Michael Primig
Journal:  Mol Oncol       Date:  2021-06-23       Impact factor: 6.603

9.  Evolution of Protein Functional Annotation: Text Mining Study.

Authors:  Ekaterina V Ilgisonis; Pavel V Pogodin; Olga I Kiseleva; Svetlana N Tarbeeva; Elena A Ponomarenko
Journal:  J Pers Med       Date:  2022-03-16
  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.