Predotar: A tool for rapidly screening proteomes for N‐terminal targeting sequences

By Ian Small, N. Peeters, F. Legeai, C. Lurin. Proteomics, 2004

903 citations recorded by the source corpus.

Subfields: Molecular Biology, Oncology, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/2c316ac81d00230bdf1c5e19077e7c92082eeb73

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Citations in the corpus

Comprehending crystalline β-carotene accumulation by comparing engineered cell models and the natural carotenoid-rich system of citrus (2011, neutral): “Sequence analysis with the two independent prediction tools Predotar (Small et al., 2004) and TargetP (Emanuelsson et al.”
Genome-Wide Analysis of Arabidopsis Pentatricopeptide Repeat Proteins Reveals Their Essential Role in Organelle Biogenesis (2004, methodology): “Overall, the percentage of observed false negative results using Predotar or TargetP is ;20 to 30% (Emanuelsson et al., 2000; Small et al., 2004) (i.e., not very different than the number of apparently untargeted PPR proteins).”
Cell-PLoc 2.0: an improved package of web-servers for predicting subcellular localization of proteins in various organisms (2010, methodology): “For instance, the cutoff threshold to reduce the homology bias for the benchmark dataset used in Predotar [111] was set at 80%, meaning that only those sequences which have 80%  pairwise sequence identity to any other in a same subset were excluded [111]; while for the benchmark dataset used in Tar”
Some remarks on protein attribute prediction and pseudo amino acid composition (2010, methodology): “Different cutoff threshold values were used, such as 90% (Reinhardt and Hubbard, 1998), 80% (Small et al., 2004), 40% (Shen and Chou, 2007a), and 25% (Chou and Shen, 2010a; Chou and Shen, 2010c).”
A New Method for Predicting the Subcellular Localization of Eukaryotic Proteins with Both Single and Multiple Sites: Euk-mPLoc 2.0 (2010, neutral): “, [1,2,3,4,5,6,7,8] as well as a long list of references cited in two comprehensive review articles [9,10]).”
A multicolored set of in vivo organelle markers for co-localization studies in Arabidopsis and other plants. (2007, background): “Programs used to predict subcellular localization were WolfPSORT (Horton et al., ª 2007 The Authors Journal compilation ª 2007 Blackwell Publishing Ltd, The Plant Journal, (2007), 51, 1126–1136 2006), PSORT (Nakai and Kanehisa, 1991), iPSORT (Bannai et al., 2002), TargetP.1 (Emanuelsson et al., 2000”
Genome Annotation in Plants and Fungi: EuGene as a Model Platform (2008, methodology): “This basic ab initio variant was enhanced by the integration of an N-terminal targeting sequence detection software tool, Predotar [42].”
Plant-mPLoc: A Top-Down Strategy to Augment the Power for Predicting Plant Protein Subcellular Localization (2010, methodology): “Actually, even if tested by a benchmark dataset within the scope that can be covered by TargetP [6] or Predotar [8], the success rate by the current Plant-mPLoc predictor is also much higher than those by the two predictors, as demonstrated below.”