Biomedical subjects

Tobias P Mann

Publications and source records attributed to Tobias P Mann.

3 recordsLinked to original sources

PubMed2006

Efficient identification of DNA hybridization partners in a sequence database.

MOTIVATION: The specific hybridization of complementary DNA molecules underlies many widely used molecular biology assays, including the polymerase chain reaction and various types of microarray analysis. In order for such an assay to work well, the primer or probe must bind to its intended target, without also binding to additional sequences in the reaction mixture. For any given probe or primer, potential non-specific binding partners can be identified using state-of-the-art models of DNA binding stability. Unfortunately, these models rely on dynamic programming algorithms that are too slow to apply on a genomic scale. RESULTS: We present an algorithm that efficiently scans a DNA database for short (approximately 20-30 base) sequences that will bind to a query sequence. We use a filtering approach, in which a series of increasingly stringent filters is applied to a set of candidate k-mers. The k-mers that pass all filters are then located in the sequence database using a precomputed index, and an accurate model of DNA binding stability is applied to the sequence surrounding each of the k-mer occurrences. This approach reduces the time to identify all binding partners for a given DNA sequence in human genomic DNA by approximately three orders of magnitude, from two days for the ENCODE regions to less than one minute for typical queries. Our approach is scalable to large DNA sequences. Our method can scan the human genome for medium strength binding sites to a candidate PCR primer in an average of 34.5 minutes. AVAILABILITY: Software implementing the algorithms described here is available at http://noble.gs.washington.edu/proj/dna-binding.

Algorithms↗

PubMed2006

Automated validation of polymerase chain reaction amplicon melting curves.

The polymerase chain reaction (PCR) is a fundamental tool of molecular biology. Quantitative PCR is the gold-standard methodology for determination of DNA copy numbers, quantitating transcription, and numerous other applications. A major barrier to large-scale application of PCR for quantitative genomic analyses is the current requirement for manual validation of individual PCRs to ensure generation of a single product. This typically requires visual inspection either of gel electrophoreses or temperature dissociation ("melting") curves of individual PCRs--a time-consuming and costly process. Here we describe a robust computational solution to this fundamental problem. Using a training set of 10 080 reactions comprising multiple quantitative PCRs from each of 1728 unique human genomic amplicons, we developed a support vector machine classifier capable of discriminating single-product PCRs with better than 99% accuracy. This approach has broad utility, and eliminates a major bottleneck to widespread application of PCR for high-throughput genomic applications.

Algorithms↗

PubMed2005

Automated validation of polymerase chain reactions using amplicon melting curves.

PCR, the polymerase chain reaction, is a fundamental tool of molecular biology. Quantitative PCR is the gold-standard methodology for determination of DNA copy numbers, quantitating transcription, and numerous other applications. A major barrier to large-scale application of PCR for quantitative genomic analyses is the current requirement for manual validation of individual PCR reactions to ensure generation of a single product. This typically requires visual inspection either of gel electrophoreses or temperature dissociation ("melting") curves of individual PCR reactions - a time-consuming and costly process. Here we describe a robust computational solution to this fundamental problem. Using a training set of 10,080 reactions comprising multiple quantitative PCR reactions from each of 1,728 unique human genomic amplicons, we developed a support vector machine classifier capable of discriminating single-product PCR reactions with better than 99% accuracy. This approach has broad utility, and eliminates a major bottleneck to widespread application of PCR for high-throughput genomic applications.

Algorithms↗