title: Uncovering multiloci-ordering by algebraic property of Laplacian matrix and its Fiedler vector.
abstract: The loci-ordering, based on two-point recombination fractions for a pair of loci, is the most important step in constructing a reliable and fine genetic map.
  
  
  
  Using the concept from complex graph theory, here we propose a Laplacian ordering approach which uncovers the loci-ordering of multiloci simultaneously. The algebraic property for a Fiedler vector of a Laplacian matrix, constructed from the recombination fraction of the loci-ordering for 26 loci of barley chromosome IV, 846 loci of Arabidopsis thaliana and 1903 loci of Malus domestica, together with the variable threshold uncovers their loci-orders. It offers an alternative yet robust approach for ordering multiloci.
  
  
  
  Source code program with data set is available as supplementary data and also in a software category of the website (http://biophysics.dgist.ac.kr)
  
  
  
  crkim@pusan.ac.kr or iksoochang@dgist.ac.kr
  
  
  
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Creative Research Initiatives Center for Proteome Biophysics, Department of Brain and Cognitive Sciences, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 711-873, Korea and.
authors.forename: Mookyung
authors.initials: M
authors.lastname: Cheon
authors.affiliation: Department of Statistics, Pusan National University, Busan 609-735, Korea.
authors.forename: Choongrak
authors.initials: C
authors.lastname: Kim
authors.affiliation: Creative Research Initiatives Center for Proteome Biophysics, Department of Brain and Cognitive Sciences, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 711-873, Korea and.
authors.forename: Iksoo
authors.initials: I
authors.lastname: Chang
mesh_terms: D012984:Software