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At least 109 records · Page 6Linked to original sources
PubMed1991

A computer method for finding common base paired helices in aligned sequences: application to the analysis of random sequences.

We describe a new computer program that identifies conserved secondary structures in aligned nucleotide sequences of related single-stranded RNAs. The program employs a series of hash tables to identify and sort common base paired helices that are located in identical positions in more than one sequence. The program gives information on the total number of base paired helices that are conserved between related sequences and provides detailed information about common helices that have a minimum of one or more compensating base changes. The program is useful in the analysis of large biological sequences. We have used it to examine the number and type of complementary segments (potential base paired helices) that can be found in common among related random sequences similar in base composition to 16S rRNA from Escherichia coli. Two types of random sequences were analyzed. One set consisted of sequences that were independent but they had the same mononucleotide composition as the 16S rRNA. The second set contained sequences that were 80% similar to one another. Different results were obtained in the analysis of these two types of random sequences. When 5 sequences that were 80% similar to one another were analyzed, significant numbers of potential helices with two or more independent base changes were observed. When 5 independent sequences were analyzed, no potential helices were found in common. The results of the analyses with random sequences were compared with the number and type of helices found in the phylogenetic model of the secondary structure of 16S ribosomal RNA. Many more helices are conserved among the ribosomal sequences than are found in common among similar random sequences. In addition, conserved helices in the 16S rRNAs are, on the average, longer than the complementary segments that are found in comparable random sequences. The significance of these results and their application in the analysis of long non-ribosomal nucleotide sequences is discussed.

Base Composition↗
PubMed1982

Comparison of computer methods for taxonomy of some streptococci using gas chromatographic chemotaxonomic data.

Gas chromatographic fingerprints of eighty-three strains of Streptococcus were analysed by computer. Seven measures of association were compared for their ability to identify strains. The most effective measure was the Stack coefficient which correctly identified 68% of strains, mostly of oral origin. Clustering of strains was carried out by median, average, single-linkage, furthest neighbour, and centroid linkage, Andrew's plots, and Minimum Spanning Trees. Of the clustering methods, centroid linkage produced the most inclusive and compact clusters. Clusters of strains of S. mitis, S. mutans, S. salivarius and S. sanguis showed varying degrees of heterogeneity; while, S. milleri was comprised of three chemotypes corresponding to oral isolates, biochemically atypical vaginal isolates, and biochemically typical strains from other sources.

Chromatography, Gas↗
PubMed1993

An automatized computer-method utilizing Procomm Plus and DataEase (4.2) PC and SAS (6.06) mainframe software for isolated, perfused guinea-pig heart studies.

A powerful, time sharing and automatized method of a comprehensive data analysis for isolated, perfused guinea-pig heart studies is described. Data are collected using DataEase PC software (version 4.2) into forms with data fields specified for vital parameters consistently recorded in isolated, perfused heart studies (HR, CBF, PEAKPRESSURE, DPDT, MVO2). After running, DataEase reports the data and information is uploaded to an IBM 3081D mainframe computer on each day of heart experiment and data collection. The uploading process, the data archival and the statistical analyses are automatized by Procomm Plus commands written in Aspect Source Program (.ASP) Files for logging, data transforming and file management procedures. The ASPCOMP.EXE compiler compiles these .ASP files into Aspect Script eXecutable (.ASX) programs, which run on the PC in our laboratory and activate WYLBUR (IBM 3081D Batch-job service and Command file processor) edited files in the mainframe's electronic devices then upload, backup and save data into these files. SAS EXE files containing program instructions for the data analyzing system are then forced by Procomm Plus to operate over the data just uploaded. SAS reads the DATA files by its INFILE facility and performs comprehensive statistical analyses and produces hard output including graphics and JOB reports of dose-response- and logaritmic scale curves for delivery to team members. This computerized and automatized method developed for isolated, perfused guinea-pig heart studies is capable of performing multiple file transfer, sophisticated statistical analyses and graphic procedures after one keystroke on the PC (Alt-F5 in Procomm Plus section) and also facilitates a consistent and convenient method for planning, controlling and standardizing experiments. The method is based on an interactive computer conversation between the PC in the laboratory and the remote's WYLBUR editor. No human presence is needed; however, in case of failure, Procomm Plus gives one of the team members supervising the system a phone call in order to get human help.

Animals↗