Detection of New Motifs Properties in Biodata


  • Nooruldeen Nasih Qader College of Science and Technology, University of Human Development, Sulaymaniyah, Kurdistan Region, Iraq
  • Hussein K. Al-Khafaji Alrafidain University College, Baghdad, Iraq



Motif model, mining, DNA, biodata, sequence, genome, k-mers, structure, Bioinformatics, monad, composite, Background Frequency


Biodata are rich of information. Knowing the properties of biological sequence can be valuable in analyzing data and making appropriate conclusions. This research applied naturalistic methodology to investigate the structural properties of biological sequences (i.e., DNA). The research implemented in the field of motif finding. Two new motifs properties were discovered named identical neighbors and adjacent neighbors.  The analysis is done in different situations of background frequency and motif model, using distinctive real data set of varied data size. The analysis demonstrated the strong existence of the properties. Exploiting of these properties considers significant steps towards developing powerful algorithms in molecular biology.


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