Detecting protein complexes in protein-protein interaction (PPI) networks is a challenging problem in computational biology. To uncover a PPI network into a complex structure, different meta-heuristic algorithms have been proposed in the literature. Unfortunately, many of such methods, including evolutionary algorithms (EAs), are based solely on the topological information of the network rather than on biological information. Despite the effectiveness of EAs over heuristic methods, more inherent biological properties of proteins are rarely investigated and exploited in these approaches. In this paper, we proposed an EA with a new mutation operator for complex detection problems. The proposed mutation operator is formulated under four expressions depending on the type of gene sub-ontology. To demonstrate the performance of the proposed evolutionary based complex detection algorithm, the Saccharomyces Cerevisiae (yeast) PPI network is used in the evaluation. The results reveal that the proposed algorithm achieves more accurate complex structures than the counterpart heuristic algorithms and the canonical evolutionary algorithm based on the topological-aware mutation operator.
إنّ التّأمّل في الدّراسات الأدبيّة النّقديّة الحديثة الّتي تنظر إلى النّصّ أنّه لوحة تتشكّل من مجموعة تداخلات نصّيّة سابقة للنصّ المُنتج أو مُعاصرة له، تدفع القارئ إلى الغوص في أعماق النّصوص وتحليلها والكشف عن الآليّات والإجراءات الّتي اعتمدت في إنتاجه، وإظهار الجماليّات الفنّيّة التي شكلت في مُجملها كائنا حيّا يُعبّر عن حالات إنسانيّة مُستمرة الحدوث رغم تقادم الأزمان.
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Change detection is a technology ascertaining the changes of
specific features within a certain time Interval. The use of remotely
sensed image to detect changes in land use and land cover is widely
preferred over other conventional survey techniques because this
method is very efficient for assessing the change or degrading trends
of a region. In this research two remotely sensed image of Baghdad
city gathered by landsat -7and landsat -8 ETM+ for two time period
2000 and 2014 have been used to detect the most important changes.
Registration and rectification the two original images are the first
preprocessing steps was applied in this paper. Change detection using
NDVI subtractive has been computed, subtrac