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PredAlgo

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Welcome to the "PredAlgo" server!

The website provides an interface to the PredAlgo program, a new multi-subcellular localization prediction tool dedicated to Algae. PredAlgo has been developed by Marianne Tardif, Ariane Atteia, Michael Specht, Cogne Guillaume, Norbert Rolland, Sabine Brugière, Michael Hippler, Myriam Ferro, Christophe Bruley, Gilles Peltier, Olivier Vallon, and Laurent Cournac, from various institutions mostly in France and in Germany (Tardif et al. 2012, Mol. Biol. Evol. 29: 3625-3639). The PredAlgo algorithm is based on a neural network trained to recognize transit peptide sequences. The neural network was trained using highly curated sets of proteins, for which subcellular locations were known, from the green alga Chlamydomonas reinhardtii. PredAlgo predicts whether a given protein is targeted to three pertinent compartments: the mitochondrion, the chloroplast, and the secretory pathway. It also predicts the transit peptide sequence. Predictions are currently most reliable for Chlamydomonas and related green algae species (Chlorophyta).

Please, send any feedback and/or suggestions about this website to Olivier Vallon, Institut de Biologie Physico−Chimique (IBPC), Paris, France.


Run PredAlgo on your sequence(s)

PredAlgo computations take a few seconds per sequence, and may take several minutes or hours on large datasets.

Choose type of job to run:

 Limited to a maximum of 100 sequences

 Unlimited. Enter your e-mail address to receive results: 


Paste one or more protein sequences in FASTA format below:

Or upload a protein sequence file in FASTA format: 

Example of FASTA input:

>seq1
EAPVPIPVWPWTQQE
PCVLRAQRPFTAKRS
...
>seq2
TRQDEGGILPQGGHF
AAAADGHFFKLPPIT
...


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