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Improving the Reliability of Evolutionary Algorithm for Complex Detection in Noisy Protein-Protein Interaction Networks
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Evolutionary algorithms are better than heuristic algorithms at finding protein complexes in protein-protein interaction networks (PPINs). Many of these algorithms depend on their standard frameworks, which are based on topology. Further, many of these algorithms have been exclusively examined on networks with only reliable interaction data. The main objective of this paper is to extend the design of the canonical and topological-based evolutionary algorithms suggested in the literature to cope with noisy PPINs. The design of the evolutionary algorithm is extended based on the functional domain of the proteins rather than on the topological domain of the PPIN. The gene ontology annotation in each molecular function, biological process, and cellular component is used to get the functional domain. The reliability of the proposed algorithm is examined against the algorithms proposed in the literature. To this end, a yeast protein-protein interaction dataset is used in the assessment of the final quality of the algorithms. To make fake negative controls of PPIs that are wrongly informed and are linked to the high-throughput interaction data, different noisy PPINs are created. The noisy PPINs are synthesized with a different and increasing percentage of misinformed PPIs. The results confirm the effectiveness of the extended evolutionary algorithm design to utilize the biological knowledge of the gene ontology. Feeding EA design with GO annotation data improves reliability and produces more accurate detection results than the counterpart algorithms.

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Publication Date
Sat Feb 02 2019
Journal Name
Journal Of The College Of Education For Women
The Role of Woman In Improving Society: The Role of Woman In Improving Society
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Abstract:
One of the most prominent historical stage feature that is well- known
nowadays in the world is democracy issue. This issue gives man the right to
reflect his concept and notions . It,s the world of freedom , human right and
liberation of women. This leads to the principle of equality between women
and men which is put in the top of liberty and Improvement lists .
Improvement can be defined as a group of means and ways that is
used to direct human work to improve their level of life economically and
socially .
This study contains three sections, the first presents the social state of
women in pre-history period . And the second section presents the theory of
improvement as an important social ph

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Publication Date
Mon Mar 15 2021
Journal Name
Journal Of Baghdad College Of Dentistry
Depression status in relation to dental caries and salivary C-Reactive Protein among 17 years old secondary school female in Baghdad City/Iraq.
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Background: Depression is a state of low mood and aversion to activity, it can affect a person's thoughts, behavior and sense of well-being. It can affect oral health and lead to an increased risk of dental caries. Dental caries is the most common oral infectious diseases that stresses the immune system and causes changes in cellular and molecular components of peripheral blood and C-Reactive Protein is one of these components, considered a key biomarker of inflammation. This study was conducted to assess the effect of depression status on dental caries among 17 years old secondary school female students in relation to salivary C-Reactive Protein. Materials and Methods: A cross sectional study was carried and the whole sample composed of

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Publication Date
Fri Oct 02 2015
Journal Name
American Journal Of Applied Sciences
Advances in Document Clustering with Evolutionary-Based Algorithms
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Document clustering is the process of organizing a particular electronic corpus of documents into subgroups of similar text features. Formerly, a number of conventional algorithms had been applied to perform document clustering. There are current endeavors to enhance clustering performance by employing evolutionary algorithms. Thus, such endeavors became an emerging topic gaining more attention in recent years. The aim of this paper is to present an up-to-date and self-contained review fully devoted to document clustering via evolutionary algorithms. It firstly provides a comprehensive inspection to the document clustering model revealing its various components with its related concepts. Then it shows and analyzes the principle research wor

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Publication Date
Mon Jul 06 2026
Journal Name
Iraqi Journal For Computer Science And Mathematics
Enhanced Intrusion Detection Using Recurrent Neural Networks with Amino Acid Codon Features
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Intrusion Detection Systems (IDS) is the main defense mechanism deployed by the current networks to prevent cyber threats. Recurrent Neural Network (RNN) are also a novel IDS structure that replaces the conventional training and testing mechanism. The strategy encodes network traffic data as biological sequences using amino acid codons in such a fashion that the RNN is capable of effectively analyzing temporal and sequence data patterns. RNN architecture design adopts embedding layers to handle codon representations and Long Short-Term Memory (LSTM) layers to perform sequential data learning, which is followed by a fully connected network to perform classification functions, which preserve high feature extraction and classification

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Publication Date
Fri May 01 2020
Journal Name
Journal Of Physics: Conference Series
Bayesian Inference for Reliability Function of Gompertz Distribution
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Abstract<p>In this paper, some Bayes estimators of the reliability function of Gompertz distribution have been derived based on generalized weighted loss function. In order to get a best understanding of the behaviour of Bayesian estimators, a non-informative prior as well as an informative prior represented by exponential distribution is considered. Monte-Carlo simulation have been employed to compare the performance of different estimates for the reliability function of Gompertz distribution based on Integrated mean squared errors. It was found that Bayes estimators with exponential prior information under the generalized weighted loss function were generally better than the estimators based o</p> ... Show More
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Publication Date
Thu Aug 01 2019
Journal Name
مجلة العلوم الاقتصادية والإدارية
Improving" Jackknife Instrumental Variable Estimation method" using A class of immun algorithm with practical application
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Improving" Jackknife Instrumental Variable Estimation method" using A class of immun algorithm with practical application

Publication Date
Sun Aug 30 2026
Journal Name
Journal Of Baghdad College Of Dentistry
The role of topical application of bone morphogenetic protein 7 (BMP7) on bone healing on rabbits (Immunohistochemical study on TGF-β 3 & IGF-1R)
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Background: Bone is essentially a highly vascular, living, constantly changing mineralized connective tissue. It is remarkable for its hardness, resilience and regenerative capacity, as well as its characteristic growth mechanisms. This study aimed to: 1. To evaluate the effect of bone morphogenetic protein7 (BMP7) on bone healing in artificially created intrabony defect in rabbits upper diastema, histologically. 2. To study the immunohistochemical expression of TGF-β3 and IGF-1R as bone formation markers in experimental and control groups during bone healing. Material and method: Forty male rabbits, was used in this study, 8 rabbits for each healing interval (3 days, 1,2 ,4 and 6 weeks). In each rabbit two bone holes were created on th

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Publication Date
Wed Oct 03 2018
Journal Name
University Of Plymouth
Green networking: analyses of power consumption of real and complex IFFT/FFT used in Next-Generation Networks and optical Orthogonal Frequency Division Multiplexing
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he Orthogonal Frequency Division Multiplexing is a promising technology for the Next Generation Networks. This technique was selected because of the flexibility for the various parameters, high spectral efficiency, and immunity to ISI. The OFDM technique suffers from significant digital signal processing, especially inside the Inverse/ Fast Fourier Transform IFFT/FFT. This part is used to perform the orthogonality/De-orthogonality between the subcarriers which the important part of the OFDM system. Therefore, it is important to understand the parameter effects on the increase or to decrease the FPGA power consumption for the IFFT/FFT. This thesis is focusing on the FPGA power consumption of the IFFT/FFT uses in the OFDM system. This researc

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Publication Date
Tue Oct 01 2024
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Assessment &lt;b&gt;&lt;/b&gt;of Serum P53 Protein Level in Adult Patients with Acute Myeloid Leukemia in Correlation with Response to Treatment
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Background: Acute myeloid leukemia (AML) is an adult leukemia characterized by rapid proliferation of undifferentiated myeloid precursors, leading to bone marrow (BM) failure and impaired erythropoiesis. The p53 tumor suppressor protein regulates cell division and inhibits tumor development by preventing cell proliferation of altered or damaged DNA. It orchestrates various cellular reactions, including cell cycle arrest, DNA repair, and antioxidant properties. Objectives: To investigate the relationship of P53 serum level with hematological findings, remission, and survival status in de novo AML patients. Methods: This is a cross-sectional study that enrolled 63 newly diagnosed de novo AML patients, and 15 sex- and age-matched healt

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Publication Date
Sun Jan 01 2017
Journal Name
Pertanika Journal Of Science & Technology
Modified Kohonen network algorithm for selection of the initial centres of Gustafson-Kessel algorithm in credit scoring
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Credit risk assessment has become an important topic in financial risk administration. Fuzzy clustering analysis has been applied in credit scoring. Gustafson-Kessel (GK) algorithm has been utilised to cluster creditworthy customers as against non-creditworthy ones. A good clustering analysis implemented by good Initial Centres of clusters should be selected. To overcome this problem of Gustafson-Kessel (GK) algorithm, we proposed a modified version of Kohonen Network (KN) algorithm to select the initial centres. Utilising similar degree between points to get similarity density, and then by means of maximum density points selecting; the modified Kohonen Network method generate clustering initial centres to get more reasonable clustering res

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