Biomedical subjects
Publications and source records attributed to A Lyall.
UNLABELLED: The paper reports on programs, organization and Hypertext Mark-up Language (HTML) presentation provided by the Hierarchical Automated Gene Identification System (HAGIS) designed for managing sequencing projects. AVAILABILITY: On request from the authors. CONTACT: st23646@ggr.co.uk
SUMMARY: A Java interface to radiation hybrid (RH) mapping software is described which enables users to build and interactively refine RH maps over the web. AVAILABILITY: The Java applets described here are available on the internet at http://www.oxmol.com/biolib/webmap/.
A method of estimating distances between pairs of genetic markers is described that directly uses their observed joint frequency distribution in a panel of radiation hybrids (RHs). The distance measure is based on the strength of association between marker pairs, which is high for close markers and decays with distance. These distances are then submitted to a previous method that generates linear coordinates for the markers directly from the intermarker distance matrix. This method of map building from RH data is simpler than others, because it uses only the observed joint frequency distributions of markers in the panel, and does not attempt to model unobserved quantities such as the retention of different sized fragments that contain the markers. It also incorporates directly the observed variation in retention of different markers, without needing a model for differential fragment retention dependent on chromosomal location, which is generally not known. Only small, precise distances are used in map construction, thereby reducing any effects of different fragment retention frequencies and local variations in X-ray sensitivity. The method is tested by simulation, and known marker distances and locations are successfully recovered from RH raw data. The method is also applied to publicly available data sets related to the recent transcript map of the human genome.
The great advances in human healthcare that are presaged by the Human Genome Project can be realized by the pharmaceutical industry. A prerequisite for this will be the successful integration of bioinformatics into most aspects of drug discovery. Although, from a scientific viewpoint, this is not a difficult problem, there are formidable technological obstacles. Once these are overcome, rapid progress can be expected.
Many sequence analysis problems involve consideration of a multiple sequence alignment where the 3-dimensional structure of one (or more) of the aligned sequences is known. In such cases, it is useful to map the sequence variability onto the atomic co-ordinates of known structure. If the structure also includes a bound ligand (or the location of the active site is known), each column position in the multiple sequence alignment may be annotated with its 'distance' from the binding site. These annotations, together with a measure of sequence variability, provide additional insights into drug specificity, for example among viral mutants. This paper describes several useful programs that automate this analysis.
A general method of assessing the significance of scored best local alignments, particularly suited to protein sequence comparisons, is described. The method establishes the parameters describing the distribution of the best results from any search program, provided that the set is sufficiently large and the majority of the alignments arise from unrelated sequences. The expected frequency of occurrence of any score can then be calculated, together with the number of standard deviations above expectation. These provide sensible measures of significance without additional search operations. However the biological significance of any alignment or set of alignments does not solely depend on the improbability of the alignment, but on all relevant factors known to the biologist.
The rational design of enzyme catalysts for chiral chemistry and of drugs which bind to proteins would be facilitated if rules for the recognition of one partner by the other could be formulated. This communication suggests and tests one generalization: arginine forms a tighter ion pair with a carboxylate group than does lysine and is always used for ion-pairs which are not broken during turnover in naturally-occurring enzymes.
BIOLOG contains facilities for the analysis of nucleic acid sequences. These facilities are available through queries and commands of the underlying implementation language PROLOG. Familiarity with PROLOG is gained by using the built-in BIOLOG functions. This experience should enable the user to extend the current system and define new facilities.
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