Rapid advances in the genomic sequencing of bacteria and viruses over the past few years have made it possible to consider sequencing the genomes of all pathogens that affect humans and the crops and livestock upon which our lives depend. Recent events make it imperative that full genome sequencing be accomplished as soon as possible for pathogens that could be used as weapons of mass destruction or disruption. This sequence information must be exploited to provide rapid and accurate diagnostics to identify pathogens and distinguish them from harmless near-neighbours and hoaxes. The Chem-Bio Non-Proliferation (CBNP) programme of the US Department of Energy (DOE) began a large-scale effort of pathogen detection in early 2000 when it was announced that the DOE would be providing bio-security at the 2002 Winter Olympic Games in Salt Lake City, Utah. Our team at the Lawrence Livermore National Lab (LLNL) was given the task of developing reliable and validated assays for a number of the most likely bioterrorist agents. The short timeline led us to devise a novel system that utilised whole-genome comparison methods to rapidly focus on parts of the pathogen genomes that had a high probability of being unique. Assays developed with this approach have been validated by the Centers for Disease Control (CDC). They were used at the 2002 Winter Olympics, have entered the public health system, and have been in continual use for non-publicised aspects of homeland defence since autumn 2001. Assays have been developed for all major threat list agents for which adequate genomic sequence is available, as well as for other pathogens requested by various government agencies. Collaborations with comparative genomics algorithm developers have enabled our LLNL team to make major advances in pathogen detection, since many of the existing tools simply did not scale well enough to be of practical use for this application. It is hoped that a discussion of a real-life practical application of comparative genomics algorithms may help spur algorithm developers to tackle some of the many remaining problems that need to be addressed. Solutions to these problems will advance a wide range of biological disciplines, only one of which is pathogen detection. For example, exploration in evolution and phylogenetics, annotating gene coding regions, predicting and understanding gene function and regulation, and untangling gene networks all rely on tools for aligning multiple sequences, detecting gene rearrangements and duplications, and visualising genomic data. Two key problems currently needing improved solutions are: (1) aligning incomplete, fragmentary sequence (eg draft genome contigs or arbitrary genome regions) with both complete genomes and other fragmentary sequences; and (2) ordering, aligning and visualising non-colinear gene rearrangements and inversions in addition to the colinear alignments handled by current tools.

We present a set of programs and a website designed to facilitate protein structure comparison and protein structure modeling efforts. Our protein structure analysis and comparison services use the LGA (local-global alignment) program to search for regions of local similarity and to evaluate the level of structural similarity between compared protein structures. To facilitate the homology-based protein structure modeling process, our AL2TS service translates given sequence–structure alignment data into the standard Protein Data Bank (PDB) atom records (coordinates). For a given sequence of amino acids, the AS2TS (amino acid sequence to tertiary structure) system calculates (e.g. using PSI-BLAST PDB analysis) a list of the closest proteins from the PDB, and then a set of draft 3D models is automatically created. Web services are available at .

There has been a significant increase, fueled by technologies from the human genome project, in the availability of nucleic acid sequence information for viruses and bacteria. This paper presents a computer-assisted process that begins with nucleic acid sequence information and produces highly specific pathogen signatures. When combined with instrumentation using the polymerase chain reaction, the resulting diagnostics are both specific and sensitive. The computational and engineering aspects of converting raw sequence data into pathogen-specific and instrument-ready assays are presented. Examples and data are presented for specific pathogens, including foot-and-mouth disease virus and the human immunodeficiency virus.

This paper introduces the IMAGEne suite of tools, which clusters ESTs around known genes, then ranks each clone within a cluster. IMAGEne filters data from known gene sequence databases and the GenBank's EST database (Boguski and Shuler, 1995, Nature Genet., 10, 369-371). It applies biological criteria in connection with judicious use of the BLAST (Altschul et al., 1990, J. Mol. Biol., 215), FASTA (Pearson and Lipman, 1988, Proc. Natl Acad. Sci. USA, 85, 2444-2448; Pearson, 1990, Methods Enzymol., 183, 63-98; Gusfield, 1997, Algorithms on Strings, Trees, and Sequences, Cambridge University Press), and SIM (Huang et al., 1990, Comput. Appl. Biosci., 6, 373-381) tools to form known gene clusters. It then applies criteria derived from experienced biologists to select the best representative I.M.A.G.E. clone for a gene. The tool provides an intuitive Java interface for query and display of the gene and its associated clones, thus directing researchers in selecting a clone that will best enhance their research. An important product is a listing of clones that best represent all known genes. The listing will be used for re-arraying clones into minimally redundant Master Arrays. Both the listings and Master Arrays will be made available to the public, which will be a valuable resource to the genomic community in furthering discovery in the area of gene function.

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