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Kavosh: a new algorithm for finding network motifs |
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| Authors: | Zahra Razaghi Moghadam Kashani Hayedeh Ahrabian Elahe Elahi Abbas Nowzari-Dalini Elnaz Saberi Ansari Sahar Asadi Shahin Mohammadi Falk Schreiber Ali Masoudi-Nejad |
| Affiliation: | (1) Laboratory of Systems Biology and Bioinformatics, Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran;(2) School of Mathematics and Computer Science, University of Tehran, Tehran, Iran;(3) Center of Excellence in Biomathematics, University of Tehran, Tehran, Iran;(4) School of Biology, University of Tehran, Tehran, Iran;(5) Institute for Computer Science, Martin-Luther-University Halle-Wittenberg, Halle, Germany;(6) Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany |
| Abstract: | BackgroundComplex networks are studied across many fields of science and are particularly important to understand biological processes. Motifs in networks are small connected sub-graphs that occur significantly in higher frequencies than in random networks. They have recently gathered much attention as a useful concept to uncover structural design principles of complex networks. Existing algorithms for finding network motifs are extremely costly in CPU time and memory consumption and have practically restrictions on the size of motifs. |
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