Genetically diverse pathogens (such as Human Immunodeficiency virus type 1, HIV-1) are frequently stratified into phylogenetically or immunologically defined subtypes for classification purposes. Computational identification of such subtypes is helpful in surveillance, epidemiological analysis and detection of novel variants, e.g., circulating recombinant forms in HIV-1. A number of conceptually and technically different techniques have been proposed for determining the subtype of a query sequence, but there is not a universally optimal approach. We present a model-based phylogenetic method for automatically subtyping an HIV-1 (or other viral or bacterial) sequence, mapping the location of breakpoints and assigning parental sequences in recombinant strains as well as computing confidence levels for the inferred quantities. Our Subtype Classification Using Evolutionary ALgorithms (SCUEAL) procedure is shown to perform very well in a variety of simulation scenarios, runs in parallel when multiple sequences are being screened, and matches or exceeds the performance of existing approaches on typical empirical cases. We applied SCUEAL to all available polymerase (pol) sequences from two large databases, the Stanford Drug Resistance database and the UK HIV Drug Resistance Database. Comparing with subtypes which had previously been assigned revealed that a minor but substantial (approximately 5%) fraction of pure subtype sequences may in fact be within- or inter-subtype recombinants. A free implementation of SCUEAL is provided as a module for the HyPhy package and the Datamonkey web server. Our method is especially useful when an accurate automatic classification of an unknown strain is desired, and is positioned to complement and extend faster but less accurate methods. Given the increasingly frequent use of HIV subtype information in studies focusing on the effect of subtype on treatment, clinical outcome, pathogenicity and vaccine design, the importance of accurate, robust and extensible subtyping procedures is clear.

A homogeneous region in a protein sequence is a set of contiguous residues that share common features, concerning physico-chemical, structural and mutational information. This paper presents a method for identifying such homogeneous regions. From a profile describing a given type of biological information along the sequence, the algorithm allows the segmentation of the sequence by optimizing a criterion characterized by two user-defined control parameters: the 'homogenizing degree' of the regions and the 'site neighbourhood' size. We apply the method to the envelope proteins of the human immunodeficiency virus HIV-1, for the identification of homogeneous regions in a hydrophobicity profile and the delineation of variable and conserved regions in a variability profile.

This paper presents a method for the multiple alignment of a sequence set. The MASH algorithm uses a non-redundant database of common motifs and an 'alignment priority' criterion that depends on the length and the occurrence frequency of the patterns in the set of sequences. This user-defined criterion allows the determination of the series of the patterns to be aligned. This program is applied to a fragment of envelope gene env gp120 for 20 isolates of the immunodeficiency virus. The multiplicity of alignments obtained by modifying the criterion parameters reveals different aspects of similarity between the sequences.

We propose a new method, called 'size leap' algorithm, of search for motifs of maximum size and common to two fragments at least. It allows the creation of a reduced database of motifs from a set of sequences whose size obeys the series of Fibonacci numbers. The convenience lies in the efficiency of the motif extraction. It can be applied in the establishment of overlap regions for DNA sequence reconstruction and multiple alignment of biological sequences. The method of complete DNA sequence reconstruction by extraction of the longest motifs ('anchor motifs') is presented as an application of the size leap algorithm. The details of a reconstruction from three sequenced fragments are given as an example.