- recipe psipred
Protein Secondary Structure Predictor
- Homepage:
- Documentation:
- Developer docs:
- License:
OTHER / CUSTOM (academic-only)
- Recipe:
- Links:
PSIPRED is a simple and accurate secondary structure prediction method, incorporating two feed-forward neural networks which perform an analysis on output obtained from [PSI-BLAST](http://www.ncbi.nlm.nih.gov/blast) (Position Specific Iterated - BLAST). Using a very stringent cross validation method to evaluate the method's performance, PSIPRED 3.2 achieves an average Q3 score of 81.6%. Predictions produced by PSIPRED were also submitted to the [CASP4](http://predictioncenter.llnl.gov/casp4/) evaluation and assessed during the CASP4 meeting, which took place in December 2000 at Asilomar. PSIPRED 2.0 achieved an average Q3 score of 80.6% across all 40 submitted target domains with no obvious sequence similarity to structures present in PDB, which ranked PSIPRED top out of 20 evaluated methods (an earlier version of PSIPRED was also ranked top in CASP3 held in 1998). It is important to realise, however, that due to the small sample sizes, the results from CASP are not statistically significant, although they do give a rough guide as to the current "state of the art". For a more reliable evaluation, the [EVA](http://pdg.cnb.uam.es/eva/) web site at Columbia University provides a continuous evaluation. NOTE that at the time of writing, the EVA site is no longer being updated. Downloads: The PSIPRED V3.2 software can be downloaded from [HERE](http://bioinfadmin.cs.ucl.ac.uk/downloads/psipred/). Please note that you should read the license terms given in the [README](http://bioinfadmin.cs.ucl.ac.uk/downloads/psipred/README) file if you wish to incorporate PSIPRED in another program or Web server. Older releases of PSIPRED can be downloaded here [HERE](http://bioinfadmin.cs.ucl.ac.uk/downloads/psipred/old/).
- package psipred¶
- Versions:
4.0-0,3.5-0- Depends:
on blast-legacy
on libgcc
>=13on tcsh
- Additional platforms:
linux-aarch64,osx-arm64
Installation¶
You need a conda-compatible package manager (currently either pixi, conda, or micromamba) and the Bioconda channel already activated (see Usage). Below, we show how to install with either pixi or conda (for micromamba and mamba, commands are essentially the same as with conda).
Pixi¶
With pixi installed and the Bioconda channel set up (see Usage), to install globally, run:
pixi global install psipred
to add into an existing workspace instead, run:
pixi add psipred
In the latter case, make sure to first add bioconda and conda-forge to the channels considered by the workspace:
pixi workspace channel add conda-forge
pixi workspace channel add bioconda
Conda¶
With conda installed and the Bioconda channel set up (see Usage), to install into an existing and activated environment, run:
conda install psipred
Alternatively, to install into a new environment, run:
conda create -n envname psipred
with envname being the name of the desired environment.
Container¶
Alternatively, every Bioconda package is available as a container image for usage with your preferred container runtime. For e.g. docker, run:
docker pull quay.io/biocontainers/psipred:<tag>
(see psipred/tags for valid values for <tag>).
Integrated deployment¶
Finally, note that many scientific workflow management systems directly integrate both conda and container based software deployment. Thus, workflow steps can be often directly annotated to use the package, leading to automatic deployment by the respective workflow management system, thereby improving reproducibility and transparency. Check the documentation of your workflow management system to find out about the integration.
Download stats¶
Link to this page¶
Render an 
badge with the following MarkDown:
[](http://bioconda.github.io/recipes/psipred/README.html)
