The SLiMDisc server: short, linear motif discovery in proteins.
The SLiMDisc server: short, linear motif discovery in proteins.
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DOI:
10.1093/nar/gkm400
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发表时间:
2007-07
影响因子:
14.9
通讯作者:
Shields DC
中科院分区:
文献类型:
--
作者:
Davey NE;Edwards RJ;Shields DC
Short, linear motifs (SLiMs) play a critical role in many biological processes, particularly in protein–protein interactions. Overrepresentation of convergent occurrences of motifs in proteins with a common attribute (such as similar subcellular location or a shared interaction partner) provides a feasible means to discover novel occurrences computationally. The SLiMDisc (Short, Linear Motif Discovery) web server corrects for common ancestry in describing shared motifs, concentrating on the convergently evolved motifs. The server returns a listing of the most interesting motifs found within unmasked regions, ranked according to an information content-based scoring scheme. It allows interactive input masking, according to various criteria. Scoring allows for evolutionary relationships in the data sets through treatment of BLAST local alignments. Alongside this ranked list, visualizations of the results improve understanding of the context of suggested motifs, helping to identify true motifs of interest. These visualizations include alignments of motif occurrences, alignments of motifs and their homologues and a visual schematic of the top-ranked motifs. Additional options for filtering and/or re-ranking motifs further permit the user to focus on motifs with desired attributes. Returned motifs can also be compared with known SLiMs from the literature. SLiMDisc is available at: http://bioware.ucd.ie/~slimdisc/.
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影响因子:
9.8
作者:
Neduva V;Linding R;Su-Angrand I;Stark A;de Masi F;Gibson TJ;Lewis J;Serrano L;Russell RB
通讯作者:
Russell RB
影响因子:
5.8
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通讯作者:
Floratos, A
影响因子:
5.8
作者:
Dosztányi, Z;Csizmok, V;Simon, I
通讯作者:
Simon, I
影响因子:
14.9
作者:
Neduva V;Russell RB
通讯作者:
Russell RB
影响因子:
14.9
作者:
Davey NE;Shields DC;Edwards RJ
通讯作者:
Edwards RJ