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strategies to search for sequence homologs in archaea: HMM-based profile queries and probabilistic methods with seed words.
We describe two strategies to identify homologs of protein sequences in archaea. One strategy computes scores for all possible multiple alignments of each query sequence with the sequences stored in a database. The other strategy uses a database of seed words, produced by searching a database of proteins with a series of hidden Markov models (HMMs) of different lengths, to determine the most likely segment of the query sequence that matches the seed words. The two strategies are compared in terms of accuracy, sensitivity and specificity. This allows us to establish, in general, which strategy is better for which class of queries. The tests use a database of 830 sequences of proteins from the three domains of life. There are two tests. In the first test, each of the query sequences is compared with all other sequences in the database. This gives an overall picture of the performance of the database. In the second test, the queries are split into three broad categories based on the frequency of occurrence of the output of the algorithm, and the test is repeated for each category. The results show that the first test gives similar results to those of a probabilistic method with HMMs, while the second test provides insight into the regions of the sequence that are responsible for homology, and also into the accuracy of the procedure.Assessment of the effect of filtration on the distribution of vancomycin in man.
In order to assess the relevance of potential intercompartmental transfer of vancomycin in patients with impaired kidney function, we studied the pharmacokinetics of this antibiotic after intravenous administration to ten patients with normal kidney function and to 15 patients with impaired kidney function, which was characterized by a creatinine clearance below the standard
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