BACKGROUND: Whole genome sequence data is a step towards generating the 'parts list' of life to understand the underlying principles of Biocomplexity. Genome sequencing initiatives of human and model organisms are targeted efforts towards understanding principles of evolution with an application envisaged to improve human health. These efforts culminated in the development of dedicated resources. Whereas a large number of viral genomes have been sequenced by groups or individuals with an interest to study antigenic variation amongst strains and species. These independent efforts enabled viruses to attain the status of 'best-represented taxa' with the highest number of genomes. However, due to lack of concerted efforts, viral genomic sequences merely remained as entries in the public repositories until recently. RESULTS: VirGen is a curated resource of viral genomes and their analyses. Since its first release, it has grown both in terms of coverage of viral families and development of new modules for annotation and analysis. The current release (2.0) includes data for twenty-five families with broad host range as against eight in the first release. The taxonomic description of viruses in VirGen is in accordance with the ICTV nomenclature. A well-characterised strain is identified as a 'representative entry' for every viral species. This non-redundant dataset is used for subsequent annotation and analyses using sequenced-based Bioinformatics approaches. VirGen archives precomputed data on genome and proteome comparisons. A new data module that provides structures of viral proteins available in PDB has been incorporated recently. One of the unique features of VirGen is predicted conformational and sequential epitopes of known antigenic proteins using in-house developed algorithms, a step towards reverse vaccinology. CONCLUSION: Structured organization of genomic data facilitates use of data mining tools, which provides opportunities for knowledge discovery. One of the approaches to achieve this goal is to carry out functional annotations using comparative genomics. VirGen, a comprehensive viral genome resource that serves as an annotation and analysis pipeline has been developed for the curation of public domain viral genome data http://bioinfo.ernet.in/virgen/virgen.html. Various steps in the curation and annotation of the genomic data and applications of the value-added derived data are substantiated with case studies.

UNLABELLED: Eukaryotes have both 'intron containing' and 'intron less' genes. Several databases are available for 'intron containing' genes in eukaryotes. In this note, we describe a database for 'intron less' genes from eukaryotes. 'Intron less' eukaryotic genes having prokaryotic architecture will help to understand gene evolution in a much simpler way unlike 'intron containing' genes. AVAILABILITY: SEGE is available at http://intron.bic.nus.edu.sg/seg/ CONTACT: [email protected]

MOTIVATION: The recent rapid rise in the availability of whole genome DNA sequence data has led to bottlenecks in their complete analysis. Specifically, there is a need for software tools that will allow mining of gene and putative gene data at a whole genome level. These new tools will complement the current set already in use for studying specific aspects of individual genes and putative genes in detail. A key software challenge is to make them user-friendly, without losing their flexibility and capability for use in research. RESULTS: The creation of GeneOrder-a web-based interactive, computational tool-allows researchers to compare the order of genes in two genomes. It has been tested on full genome sequence data for viruses, mitochondria and chloroplasts that were obtained from the NCBI GenBank database. It is accessible at http://www.bif.atcc.org/GENEOrder/index.html. GeneOrder prepares the comparison in table form, listing the order of similar genes. Hyperlinks are provided from this output; these lead to the 'Protein Coding Regions' in the NCBI database.

A software is developed using genetic algorithms to predict the structure of a polypeptide chain. The algorithm is based on the principle of evolution and it improves the solution of the posed problem by genetic operations crossovers and mutations. Dihedral angles (/spl phi/,/spl psi/) are taken as the basic variables for the structure of the molecules and genetic operations are carried over on a population of binary strings of (/spl phi/,/spl psi/) angles. First, a sequential code is developed in FORTRAN on a standard workstation. A parallel version of the program is implemented on a distributed computing platform PARAM, developed by CDAC. The methodology and the practical aspects of the algorithm is presented with case studies of a dipeptide and an octapeptide. The usefulness of the migration model, developed for the first time, in achieving efficiency is stressed. The migration model proved to be more efficient and the minimisation for the octapeptide improved from 2% to 10%. This improvement is expected to be more pronounced for larger molecules.

A software package that allows one to carry out multiple alignment of protein and nucleic acid sequences of almost unlimited length and number of sequences is developed on C-DAC parallel computer--a transputer-based machine. The farming approach is used for data parallelization. The speed gains are almost linear when the number of transputers is increased from 4 to 64. The software is used to carry out multiple alignment of 100 sequences each of alpha-chain and beta-chain of hemoglobin and 83 cytochrome c sequences. The signature sequence of cytochrome c was found to be PGTKMXF. The single parameter, multiple alignment score, S, has been used to categorize proteins in different subfamilies and groups.

An algorithm using the graph theoretical approach to predict secondary structures of large nucleic acids is discussed. Reliability of prediction can be improved by incorporating available experimental data and sequence homology information. As a case study, this algorithm is applied to predict the secondary structure of the 16S-23S rRNA complex from E. coli. It was found that several structures of the complex can coexist. The computer program developed to predict the secondary structure of large RNAs can be run on IBM PC/AT compatible systems.

A simple computer program has been developed to locate repeating subsequences of all possible lengths in a given nucleic acid. The observed number of repeats of subsequences was compared with the expected number of such repeats in several RNAs. The analysis showed that, in the case of rRNAs, there are no constraints in the choice of the fourth and the higher order nucleotides, while the selection is maximum at the level of nearest neighbour. This is, however, not true for RNAs coding for proteins, where the constraints are also found at the level of nucleotides containing five or more bases.