A Coordinated Approach by Public Domain Bioinformatics Resources to Aid the Fight Against Alzheimer’s Disease Through Expert Curation of Key Protein Targets | Zendy

Lionel Breuza | Zendy; Cecilia Arighi | Zendy; Ghislaine ArgoudPuy | Zendy; Cristina CasalsCasas | Zendy; Anne Estreicher | Zendy; Maria Livia Famiglietti | Zendy; George P. Georghiou | Zendy; Arnaud Gos | Zendy; Nadine Gruaz-Gumowski | Zendy; Ursula Hinz | Zendy; Nevila HykaNouspikel | Zendy; Barbara Kramarz | Zendy; Ruth C. Lovering | Zendy; Yvonne Lussi | Zendy; Michele Magrane | Zendy; Patrick Masson | Zendy; Livia Perfetto | Zendy; Sylvain Poux | Zendy; M. Rodríguez-López | Zendy; Christian J. Stoeckert | Zendy; Shyamala Sundaram | Zendy; LiSan Wang | Zendy; Elizabeth Wu | Zendy; Sandra Orchard | Zendy

Open Access

A Coordinated Approach by Public Domain Bioinformatics Resources to Aid the Fight Against Alzheimer’s Disease Through Expert Curation of Key Protein Targets

Author(s) -

Lionel Breuza,

Cecilia Arighi,

Ghislaine ArgoudPuy,

Cristina CasalsCasas,

Anne Estreicher,

Maria Livia Famiglietti,

George P. Georghiou,

Arnaud Gos,

Nadine Gruaz-Gumowski,

Ursula Hinz,

Nevila HykaNouspikel,

Barbara Kramarz,

Ruth C. Lovering,

Yvonne Lussi,

Michele Magrane,

Patrick Masson,

Livia Perfetto,

Sylvain Poux,

M. Rodríguez-López,

Christian J. Stoeckert,

Shyamala Sundaram,

LiSan Wang,

Elizabeth Wu,

Sandra Orchard

Publication year - 2020

Publication title -

journal of alzheimer s disease

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.677

H-Index - 139

eISSN - 1875-8908

pISSN - 1387-2877

DOI - 10.3233/jad-200206

Subject(s) - uniprot , identifier , ontology , computer science , gene ontology , data curation , data science , domain (mathematical analysis) , annotation , key (lock) , computational biology , information retrieval , gene , biology , artificial intelligence , genetics , mathematical analysis , philosophy , gene expression , mathematics , epistemology , programming language , computer security

The analysis and interpretation of data generated from patient-derived clinical samples relies on access to high-quality bioinformatics resources. These are maintained and updated by expert curators extracting knowledge from unstructured biological data described in free-text journal articles and converting this into more structured, computationally-accessible forms. This enables analyses such as functional enrichment of sets of genes/proteins using the Gene Ontology, and makes the searching of data more productive by managing issues such as gene/protein name synonyms, identifier mapping, and data quality.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research