disulfinder - cysteines disulfide bonding state and connectivity predictor

       Ceroni A, Passerini A, Vullo A, Frasconi P.

       Packaging by Laszlo Kajan <lkajan@rostlab.org>

       GPL

       'disulfinder' is for predicting the disulfide bonding state of cysteines and their disulfide connectivity
       starting from sequence alone. Disulfide bridges play a major role in the stabilization of the folding
       process for several proteins. Prediction of disulfide bridges from sequence alone is therefore useful for
       the study of structural and functional properties of specific proteins. In addition, knowledge about the
       disulfide bonding state of cysteines may help the experimental structure determination process and may be
       useful in other genomic annotation tasks.  'disulfinder' predicts disulfide patterns in two computational
       stages: (1) the disulfide bonding state of each cysteine is predicted by a BRNN-SVM binary classifier;
       (2) cysteines that are known to participate in the formation of bridges are paired by a Recursive Neural
       Network to obtain a connectivity pattern.

       "disulfinder     -a     1     -p    /usr/share/doc/disulfinder/examples/res_id_41483.blastPsiMatTmb    -o
       ./disulfinder_results_dir"

/usr/share/disulfinder
           default package data directory

       ~/disulfinder
           default work directory

       disulfinder - cysteines disulfide bonding state and connectivity predictor

       -a, --alternatives=NUMBER
           alternative connectivity patterns (default=3)

       -o, --output=DIR
           output dir where predictions will be saved (default=$PWD)

       -p, --psi2=FILE|DIR
           input  in  psi2  format (PSI-BLAST Matrix in ASCII), either a single file or a directory(?). Generate
           this with "blastpgp -j <N> -Q FILE" where N >= 2.

       -r, --rootdir=DIR
           work directory (default=~/disulfinder)

       -k, --pkgdatadir=DIR
           package data directory containing Models (default=/usr/share/disulfinder)

       -F, --format={html|ascii}
           output format type (default=ascii)

       -d --blastdb=DIR
           blastpgp -d option (default=/data/sp+trembl)

       -c, --cleanpred
           cleanup intermediate prediction files (default=false)

       -P, --usepssm
           use pssm instead of counts for profiles (default=false)

       -C, --knownbondingstate
           assume    bonding    state    is    known    (one    file    for    each    chain    in     directory
           <rootdir>/Predictions/Bondstate/Viterbi)     (default=false)

       -v, --version
           disulfinder version

       -?, --help
           help screen

       A. Ceroni, A. Passerini, A. Vullo and P. Frasconi. DISULFIND: a Disulfide Bonding State and Cysteine
       Connectivity Prediction Server, Nucleic Acids Research, 34(Web Server issue):W177-W181, 2006.

       For the disulphide connectivity predictor see:

       A. Vullo and P. Frasconi. Disulfide Connectivity Prediction using Recursive Neural Networks and
       Evolutionary Information, Bioinformatics, 20, 653-659, 2004.

       For the cystein bonding state predictor see:

       P. Frasconi, A. Passerini, and A. Vullo. A Two-Stage SVM Architecture for Predicting the Disulfide
       Bonding State of Cysteines, Proc. IEEE Workshop on Neural Networks for Signal Processing, pp.25-34, 2002.
       A.Ceroni, P.Frasconi, A.Passerini and A.Vullo. Predicting the Disulfide Bonding State of Cysteines with
       Combinations of Kernel Machines, Journal of VLSI Signal Processing, 35, 287-295, 2003.

       The work directory is not cleaned up automatically.

       See official web site for help:
           <http://disulfind.dsi.unifi.it/>

       DISULFIND: a disulfide bonding state and cysteine connectivity prediction server:
           <http://www.ncbi.nlm.nih.gov/pubmed/?term=16844986[uid]>

1.2.11                                             2022-01-20                                     DISULFINDER(1)

       disulfinder [OPTIONS]