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4D bioinformatics: a new look at the ribosome as an example.

We have adapted the Java Molecular Viewer (JMV) to virtual reality display environments, through a number of extensions to the Java 3D code. Phylogenetic information derived from multiple alignments (temporal information) can be overlaid onto molecule structures (spatial information). The number of sequences included in the underlying multiple alignment can be changed instantaneously, resulting in dynamical updates of the displayed information. JMV was also extended to handle an infinite number of objects (molecules) in the same display. The objects can be manipulated in six degrees of freedom simultaneously or independently. We have used the small subunit ribosomal RNA to demonstrate the system (http:// cave.ucalgary.ca), which can be used for any molecule with a resolved structure.

Animals↗
PubMed2001

An HLA-directed molecular and bioinformatics approach identifies new HLA-A11 HIV-1 subtype E cytotoxic T lymphocyte epitopes in HIV-1-infected Thais.

Only limited cytotoxic T lymphocyte (CTL) epitope mapping has been done in nonsubtype B HIV-infected persons. We used molecular immunogenetic tools to determine HIV-specific CTL responses in HIV-1 Env subtype E-infected female sex workers (FSWs) from northern Thailand, where more than 50% of the population is HLA-A11 positive. EpiMatrix, a computer-based T cell epitope prediction algorithm, and a manual editing approach were used to predict 77 possible HLA-A11 CTL epitopes in HIV-1, some of which were conserved between subtypes B and E. MHC binding of these peptides was determined in an HLA-A11 stabilization assay, and binding peptides were tested for CTL recognition in eight HLA-A11-positive FSWs. Subtype E versions of known HLA-A2 subtype B HIV epitopes were also tested in four HLA-A2 positive FSWs. CTL responses were detected in all HLA-A11-positive and in three of four HLA-A2-positive persons. Among the 12 FSWs responses to peptides were found to Pol in 9 (75%), Env in 7 (58%), Nef in 5 (42%), and Gag in 5 (42%), and to conserved epitopes in 8 (67%). To identify HLA-A11 CTL epitopes in the absence of prediction tools, it would have been necessary to test almost 3000 10-mer peptides. EpiMatrix and manual predictions reduced this number to 77, of which 26 were MHC binding and 12 were CTL epitopes. Six of these HLA-A11 CTL epitopes have not been previously reported and are located in RT, gp120, and gp41. This report of CTL responses in subtype E-infected individuals defines epitopes that may be useful in HIV pathogenesis or vaccine studies.

Algorithms↗
PubMed2000

The untranslated regions of eukaryotic mRNAs: structure, function, evolution and bioinformatic tools for their analysis.

The crucial role of the non-coding portion of genomes is now widely acknowledged. In particular, mRNA untranslated regions are involved in many post-transcriptional regulatory pathways that control mRNA localisation, stability and translation efficiency. A review is given of the most recent research works on the functional characterisation of eukaryotic mRNA untranslated regions. In order to make possible a systematic and detailed sequence analysis of mRNA untranslated regions (UTRs), a non-redundant database of metazoan mRNA untranslated sequences annotated for the occurrence of specific functional elements, UTRdb, was devised. These elements, whose consensus structure has been devised on the basis of experimental assays and of comparative analyses, have been collected in the UTRsite database. A suitable pattern-matching software has been devised to search UTRsite patterns in user-submitted sequences, also assessing their statistical significance. Structural, compositional and evolutionary features of untranslated sequences of metazoan mRNAs have been investigated showing peculiar intra- and interspecific patterns.

Animals↗
PubMed2005

Bioinformatics approaches and resources for single nucleotide polymorphism functional analysis.

Since the initial sequencing of the human genome, many projects are underway to understand the effects of genetic variation between individuals. Predicting and understanding the downstream effects of genetic variation using computational methods are becoming increasingly important for single nucleotide polymorphism (SNP) selection in genetics studies and understanding the molecular basis of disease. According to the NIH, there are now more than four million validated SNPs in the human genome. The volume of known genetic variations lends itself well to an informatics approach. Bioinformaticians have become very good at functional inference methods derived from functional and structural genomics. This review will present a broad overview of the tools and resources available to collect and understand functional variation from the perspective of structure, expression, evolution and phenotype. Additionally, public resources available for SNP identification and characterisation are summarised.

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