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DisLocate specifications

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Unique identifier OMICS_18496
Name DisLocate
Interface Web user interface
Restrictions to use None
Input data A protein sequence.
Input format FASTA
Output data The predicted connectivity pattern corresponding to the input sequence.
Computer skills Basic
Stability Stable
Maintained Yes

Maintainer


  • person_outline Piero Fariselli

Publication for DisLocate

DisLocate citations

 (2)
library_books

Protein disulfide topology determination through the fusion of mass spectrometric analysis and sequence based prediction using Dempster Shafer theory

2013
BMC Bioinformatics
PMCID: 3549834
PMID: 23368815
DOI: 10.1186/1471-2105-14-S2-S20

[…] not all sequence-based methods find this bond. the table also highlights the fact that methods (and underlying models) which work well in some cases don't work equally well in others. for instance, dislocate, which utilizes protein subcellular localization to determine the s-s bonds, can find only one bond. however, on the spxx data sets [], this method has been shown to outperform […]

library_books

Prediction of disulfide connectivity in proteins with machine learning methods and correlated mutations

2013
BMC Bioinformatics
PMCID: 3548674
PMID: 23368835
DOI: 10.1186/1471-2105-14-S1-S10

[…] pattern predictor based on svr+icov+mip when the bonding state of cysteines is not known but it is predicted. for this purpose, we adopted the bonding state predictor previously introduced in dislocate which is based on grammatical-restrained hidden conditional random fields [] and protein subcellular localization []. in this case, we used the grhcrf part of dislocate to predict […]


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DisLocate institution(s)
Biocomputing Group, University of Bologna, CIRI-Life Science and Health Technologies and Department of Biology, Bologna, Italy; Department of Computer Science, Bologna, Italy; Externautics s.p.a., Department of Bioinformatics, Siena, Italy
DisLocate funding source(s)
Supported by MIUR-FIRB grant number RBLA039M7M for the LIBI project.

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