Characterize Protein Functional Relationships Based on Mrna Expression Profile | Zendy

Wei Ding | Zendy; Luquan Wang | Zendy; Ping Qiu | Zendy; Jonathan Greene | Zendy; Marco Hernandez | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Characterize Protein Functional Relationships Based on Mrna Expression Profile

Author(s) -

Wei Ding,

Luquan Wang,

Ping Qiu,

Jonathan Greene,

Marco Hernandez

Publication year - 2002

Publication title -

the scientific world journal

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.453

H-Index - 93

eISSN - 2356-6140

pISSN - 1537-744X

DOI - 10.1100/tsw.2002.37

Subject(s) - messenger rna , expression (computer science) , protein expression , computational biology , computer science , microbiology and biotechnology , biology , genetics , gene , programming language

. Protein families are distinguished by members that exhibit sequence and biomedical function similarity. For most gene changes in protein abundance are related to changes in mRNA abundance, which are immensely informative about cell state and the activity of genes. LifeExpress RNA (LE) database (Incyte Genomics, Inc) is a large-scale genome expression database. Based on LE we derived the functional relationship of Pfam[1], a database of protein domain families, by studying the global expression profile of the corresponding genes of Pfam family members. The expression profiles for 135 largest Pfam families were summarized and relationships were analyzed. The study present a simple model for conceptualizing the complex genetic regulatory network.

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