Detection of viral sequence fragments of HIV-1 subfamilies yet unknown

Background: Methods of determining whether or not any particular HIV-1 sequence stems - completely or in part - from some unknown HIV-1 subtype are important for the design of vaccines and molecular detection systems, as well as for epidemiological monitoring. Nevertheless, a single algorithm only, the Branching Index (BI), has been developed for this task so far. Moving along the genome of a query sequence in a sliding window, the BI computes a ratio quantifying how closely the query sequence clusters with a subtype clade. In its current version, however, the BI does not provide predicted boundaries of unknown fragments. Results: We have developed Unknown Subtype Finder (USF), an algorithm based on a probabilistic model, which automatically determines which parts of an input sequence originate from a subtype yet unknown. The underlying model is based on a simple profile hidden Markov model (pHMM) for each known subtype and an additional pHMM for an unknown subtype. The emission proba...

• Type: Journal
• Year: 2011
• Where: BMCBI
• Authors: Thomas Unterthiner, Anne-Kathrin Schultz, Jan Bulla, Burkhard Morgenstern, Mario Stanke, Ingo Bulla
• Keywords: Artificial Intelligence, BMCBI 2011, Hiv-1 Sequences, Unknown Hiv-1 Subtype, Unknown Subtypes