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Mining the human proteome: Experience with the human lymphoid protein database
Author(s) -
Hanash Samir M.,
Teichroew Daniel
Publication year - 1998
Publication title -
electrophoresis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.666
H-Index - 158
eISSN - 1522-2683
pISSN - 0173-0835
DOI - 10.1002/elps.1150191119
Subject(s) - database , proteome , polyacrylamide gel electrophoresis , biology , in vitro , cell , lymphoid leukemia , computational biology , leukemia , computer science , immunology , bioinformatics , biochemistry , enzyme
We have undertaken an effort in the past five years aimed at developing a database of lymphoid proteins detectable by two‐dimensional (2‐D) polyacrylamide gel electrophoresis. The database contains 2‐D patterns and derived information pertaining to: (i) polypeptide constituents of unstimulated and stimulated mature T cells and immature thymocytes; (ii) cultured T cells and cell lines that have been manipulated by transfection with a variety of constructs or by treatment with specific agents; (iii) single cell‐derived T and B cell clones; (iv) cells obtained from patients with lymphoproliferative disorders and leukemia; and (v) a variety of other relevant cell populations. The database has experienced a substantial expansion in 2‐D patterns it contains, numbering currently 9167 individual 2‐D patterns. This number represents a fraction of the 30682 2‐D patterns maintained in our databases. The capacity to design and undertake experiments, produce high‐quality 2‐D patterns, and to undertake simple or rudimentary analyses of 2‐D patterns to meet the basic needs of the experiments for which the 2‐D gels were produced has exceeded the capacity to fully and uniformly integrate information generated from any gel image or experiment, across all images and experiments. While only a fraction of the information in the 2‐D patterns contained in the lymphoid database has been mined, novel findings derived from querying the database point to the merits of this protein based approach. Additional resources have recently been put into place to mine more effectively data pertaining to protein expression in lymphoid cells.