MultiLoc.org

Assigning subcellular localization to a protein is an important step towards elucidating its interaction partners, function, and potential role(s) in the cellular machinery. Computational tools offer an attractive complement to time-consuming and laborious experimental methods.

We have designed several systems for predicting the subcellular localization of eukaryotic proteins from the amino acid sequence:

		YLoc (2010) YLoc is a highly interpretable subcellular localization predictor that performes comparable to current state-of-the-art predictors. For every prediction, YLoc gives a reasoning why this prediction was made and which biological properties of the protein lead to this prediction. A confidence scores helps users to rate their trust in the prediction. In addition, it predicts the localization sites of multiple-targeted proteins.
		SherLoc2 (2009) SherLoc2 combines the amino acid information, knowledge on domains, and phylogenetic profiles with text-based information. It predicts 11 locations of eukaryotic cells with very high prediction accuracy. In addition, it offers users to include background knowledge by describing their protein.
		MultiLoc2 (2009) MultiLoc2 is a high-accuracy subcellular localization predictor. Similar to its predecessor, it combines information on amino acid composition and N-terminal targeting signals. In addition, knowledge on domains in form of GO terms and phylogenetic profiles are used to gain a higher prediction performance. It is available in two versions: A low-resultion version is specialized on predicting the location of globular proteins. A high-resolution version predicts all 11 main locations of eukaryotic cells.
		SherLoc (2006) SherLoc combines the information obtained from MultiLoc such as amino acid composition and N-terminal sorting signals with text-based information from PubMed abstracts. It supports 11 eukaryotic localizations.
		MultiLoc (2006) MultiLoc integrates several sources of sequence-based information in order to assign subcellular localization and supports 11 eukaryotic localizations. MultiLoc integrates several sources of relevant sequence-based information i.e. N-terminal targeting sequences, amino acid composition, and sequence motifs, in order to provide reliable predictions on a proteome-wide scale. MultiLoc is based on support vector machines (SVMs). TargetLoc, the low resolution version of MultiLoc, was constructed to distinguish globular proteins and support 4 and 3 localizations for plant and non-plant, respectively.

References

• Briesemeister S, Rahnenführer J, and Kohlbacher, O (2010)
  Going from where to why - interpretable prediction of protein subcellular localization
  to be submitted
• Briesemeister, S, Blum, T, Brady, S, Lam, Y, Kohlbacher, O, and Shatkay, H (2009).
  SherLoc2: a high-accuracy hybrid method for predicting subcellular localization of proteins
  J. Proteome Res., 8(11):5363–5366.
• Blum, T, Briesemeister, S, and Kohlbacher, O (2009).
  MultiLoc2: integrating phylogeny and Gene Ontology terms improves subcellular protein localization prediction
  BMC Bioinformatics, 10:274.
• Shatkay, H, Höglund, A, Brady, S, Blum, T, Dönnes, P, and Kohlbacher, O (2007).
  SherLoc: High-Accuracy Prediction of Protein Subcellular Localization by Integrating Text and Protein Sequence Data.
  Bioinformatics, 23(11):1410-1417.
• Höglund, A, Blum, T, Brady, S, Dönnes, P, Miguel, JS, Rocheford, M, Kohlbacher, O, and Shatkay, H (2006).
  Significantly improved prediction of subcellular localization by integrating text and protein sequence data
  In: Proceedings of the Pacific Symposium on Biocomputing (PSB 2006), PSB
• Höglund, A, Doennes, P, Blum, T, Adolph, H W, and Kohlbacher, O (2006).
  MultiLoc: prediction of protein subcellular localization using N-terminal targeting sequences, sequence motifs, and amino acid composition
  BMC Bioinformatics, 22(10):1158-6