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Katalymov LL Evstigneev DA 《Rossi?skii fiziologicheski? zhurnal imeni I.M. Sechenova / Rossi?skaia akademiia nauk》2004,90(2):181-186
When cathode subthreshold impulse was turned off, excitable membranes of isolated nerve fibres and nervous trunk show postelectrotonic depolarisation (PED), that is a slow recovery of membrane potential to the resting level. PED of the single nodes of Ranvier and nervous trunk is registered not only in normal conditions, but also after complete block of sodium channels. The size and duration of nervous trunk PED under subthreshold depolarising current increase along with duration of applied depolarisation: when cathode current 1 ms in duration was used, they were 0.093 +/- +/- 0.004 mV and 7.123 +/- 0.576 ms, respectively; when current was 5 ms in duration, they were 0.189 +/- 0.005 mV and 23.212 +/- 1.186 ms, whereas a 10-ms depolarisation yields values of 0.220 +/- 0.011 mV and 68.721 +/- 3.389 ms. Application of the train of catelectrotonic impulses leads to PED built-up. As PED is found not only in normal conditions but also after complete block of sodium channels, it is reasonable to suggest that the most probable reason for PED is an outward potassium current. 相似文献
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Background
Distance-based methods are popular for reconstructing evolutionary trees thanks to their speed and generality. A number of methods exist for estimating distances from sequence alignments, which often involves some sort of correction for multiple substitutions. The problem is to accurately estimate the number of true substitutions given an observed alignment. So far, the most accurate protein distance estimators have looked for the optimal matrix in a series of transition probability matrices, e.g. the Dayhoff series. The evolutionary distance between two aligned sequences is here estimated as the evolutionary distance of the optimal matrix. The optimal matrix can be found either by an iterative search for the Maximum Likelihood matrix, or by integration to find the Expected Distance. As a consequence, these methods are more complex to implement and computationally heavier than correction-based methods. Another problem is that the result may vary substantially depending on the evolutionary model used for the matrices. An ideal distance estimator should produce consistent and accurate distances independent of the evolutionary model used. 相似文献7.
Background
Profile hidden Markov model (HMM) techniques are among the most powerful methods for protein homology detection. Yet, the critical features for successful modelling are not fully known. In the present work we approached this by using two of the most popular HMM packages: SAM and HMMER. The programs' abilities to build models and score sequences were compared on a SCOP/Pfam based test set. The comparison was done separately for local and global HMM scoring. 相似文献8.
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