6 resultados para SEQUENCE

em Bucknell University Digital Commons - Pensilvania - USA


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Monobrominated polystyrene (PStBr) chains were prepared using standard atom transfer radical polymerization (ATRP) procedures at 80 °C in THF, with monomer conversions allowed to proceed to approximately 40%. At this time, additional copper catalyst, reducing agent, and ligand were added to the unpurified reaction mixture, and the reaction was allowed to proceed at 50 °C in an atom transfer radical coupling (ATRC) phase. During this phase, polymerization continued to occur as well as coupling; expected due to the substantial amount of residual monomer remaining. This was confirmed using gel permeation chromatography (GPC), which showed increases in molecular weight not matching a simple doubling of the PStBr formed during ATRP, and an increase in monomer conversion after the second phase. When the radical trap 2-methyl-2-nitrosopropane (MNP) was added to the ATRC phase, no further monomer conversion occurred and the resulting product showed a doubling of peak molecular weight (Mp), consistent with a radical trap-assisted ATRC (RTA-ATRC) reaction.

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Monobrominated polystyrene (PStBr) chains were prepared using standard atom transfer radical polymerization (ATRP) procedures at 80 degrees C in THF, with monomer conversions allowed to proceed to approximately 40%. At this time, additional copper catalyst, reducing agent, and ligand were added to the unpurified reaction mixture, and the reaction was allowed to proceed at 50 degrees C in an atom transfer radical coupling (ATRC) phase. During this phase, polymerization continued to occur as well as coupling; expected due to the substantial amount of residual monomer remaining. This was confirmed using gel permeation chromatography (GPC), which showed increases in molecular weight not matching a simple doubling of the PStBr formed during ATRP, and an increase in monomer conversion after the second phase. When the radical trap 2-methyl-2-nitrosopropane (MNP) was added to the ATRC phase, no further monomer conversion occurred and the resulting product showed a doubling of peak molecular weight (M-p), consistent with a radical trap-assisted ATRC (RTA-ATRC) reaction. (C) 2013 Elsevier Ltd. All rights reserved.

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Background: In protein sequence classification, identification of the sequence motifs or n-grams that can precisely discriminate between classes is a more interesting scientific question than the classification itself. A number of classification methods aim at accurate classification but fail to explain which sequence features indeed contribute to the accuracy. We hypothesize that sequences in lower denominations (n-grams) can be used to explore the sequence landscape and to identify class-specific motifs that discriminate between classes during classification. Discriminative n-grams are short peptide sequences that are highly frequent in one class but are either minimally present or absent in other classes. In this study, we present a new substitution-based scoring function for identifying discriminative n-grams that are highly specific to a class. Results: We present a scoring function based on discriminative n-grams that can effectively discriminate between classes. The scoring function, initially, harvests the entire set of 4- to 8-grams from the protein sequences of different classes in the dataset. Similar n-grams of the same size are combined to form new n-grams, where the similarity is defined by positive amino acid substitution scores in the BLOSUM62 matrix. Substitution has resulted in a large increase in the number of discriminatory n-grams harvested. Due to the unbalanced nature of the dataset, the frequencies of the n-grams are normalized using a dampening factor, which gives more weightage to the n-grams that appear in fewer classes and vice-versa. After the n-grams are normalized, the scoring function identifies discriminative 4- to 8-grams for each class that are frequent enough to be above a selection threshold. By mapping these discriminative n-grams back to the protein sequences, we obtained contiguous n-grams that represent short class-specific motifs in protein sequences. Our method fared well compared to an existing motif finding method known as Wordspy. We have validated our enriched set of class-specific motifs against the functionally important motifs obtained from the NLSdb, Prosite and ELM databases. We demonstrate that this method is very generic; thus can be widely applied to detect class-specific motifs in many protein sequence classification tasks. Conclusion: The proposed scoring function and methodology is able to identify class-specific motifs using discriminative n-grams derived from the protein sequences. The implementation of amino acid substitution scores for similarity detection, and the dampening factor to normalize the unbalanced datasets have significant effect on the performance of the scoring function. Our multipronged validation tests demonstrate that this method can detect class-specific motifs from a wide variety of protein sequence classes with a potential application to detecting proteome-specific motifs of different organisms.