A Fast Heuristic Algorithm for a Probe Mapping Problem

Anewheuristic algorithm is presented for mapping probes to locations along the genome,given noisy pairwise distance data as input. Themodel consideredis quite general: Theinput consists of a collection of probepairs and a confidenceinterval for the genomicdistance separating each pair. Because the distance intervals are only known with someconfidence level, somemaybe erroneons and must be removedin order to find a consistent map. A novel randomized technique for detecting and removingbad distance intervals is described. Thetechnique could be useful in other contexts wherepartially erroneousdata is inconsistent with the remaining data. These algorithms were motivated by the goal of making probe mapswith inter-probe distance confidence intervals estimated from fluorescence insitu hybridization (FISH) experiments. Experimentationwasdone on synthetic data sets (with and without errors) and FISHdata from a region of humanchromosome4. Problems with up to 100probes could be solved in several...

• Type: Conference
• Year: 1997
• Where: ISMB
• Authors: Brendan Mumey
• Keywords: Computational Biology, Distance Confidence Intervals, Distance Intervals, ISMB 1997, Noisy Pairwise Distance