TUAT Kuroda Lab.


Sequence Input a single protein sequence
using single-letter AA code.
Input more than 120
and less than 2,000 residues.
You can use only AA code,
space and return keys for sequence.

Sample image is here.
Prediction result of 2cwg_A
SVMs SVM-All SVM-Long SVM-Short SVM-Joint Select SVMs
Threshold Threshold for output value of
candidate region
Offset Length of terminal region to be
ignored in prediction
Rank Number of predicted regions
for the result

DLP-SVM is a domain linker predictor.
It is composed of three loop-length dependent SVM predictors of domain linkers (SVM-All, SVM-Long and SVM-Short),
and SVM-Joint, which combines the results of SVM-Short and SVM-Long
into a single consolidated prediction (Ebina et al, 2009, Biopolymers ref 1).

The performances of our predictor appear to be largely related to the
quality of the domain data base, we developed in previous studies (ref 2 and 3).
An essential point of DLP is that only strictly-defined domain linkers were used to
train the predictor. Our definition of a domain linker is a loop sequence separating
two structural domains which can fold independently.

The training dataset is available here: LinkerList.txt

Ebina T, Toh H, Kuroda Y:
Loop-length dependent SVM prediction of domain linkers for high-throughput structural proteomics. Biopolymers 2009;92(1):1-8.

Copyright (c) 2011 TUAT Kuroda Lab All Rights Reserved.