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Fuzzy C means Based Evaluation Algorithms For Cancer Gene Expression Data Clustering
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The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, which is used to cluster genes. FCM allows an object to belong to two or more clusters with a membership grade between zero and one and the sum of belonging to all clusters of each gene is equal to one. This paradigm is useful when dealing with microarray data. The total time required to implement the first model is 22.2589 s. The second model combines FCM and particle swarm optimization (PSO) to obtain better results. The hybrid algorithm, i.e., FCM–PSO, uses the DB index as objective function. The experimental results show that the proposed hybrid FCM–PSO method is effective. The total time of implementation of this model is 89.6087 s. The third model combines FCM with a genetic algorithm (GA) to obtain better results. This hybrid algorithm also uses the DB index as objective function. The experimental results show that the proposed hybrid FCM–GA method is effective. Its total time of implementation is 50.8021 s. In addition, this study uses cluster validity indexes to determine the best partitioning for the underlying data. Internal validity indexes include the Jaccard, Davies Bouldin, Dunn, Xie–Beni, and silhouette. Meanwhile, external validity indexes include Minkowski, adjusted Rand, and percentage of correctly categorized pairings. Experiments conducted on brain tumor gene expression data demonstrate that the techniques used in this study outperform traditional models in terms of stability and biological significance.

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Publication Date
Tue Feb 28 2023
Journal Name
Iraqi Journal Of Science
Gentamicin Upregulates the Gene Expression of hla and nuc in Staphylococcus aureus
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The current study aimed to detect the effect of gentamicin stress on the expression of hla (encodes hemolysin) and nuc (encodes nuclease) genes of Staphylococcus aureus. Fifty-eight isolates identified as S. aureus were isolated locally from different clinical specimens. Disk diffusion method was used to detect the resistance to S. aureus. The minimum inhibitory concentration (MIC) of gentamicin was estimated by broth microdilution method. hla and nuc genes were determined by polymerase chain reaction technique. The biofilm was evaluated using the microtiter plate method in the presence and absence of gentamicin at sub-MIC. The results showed that 18 (31%) and 40 (69%) S. aureus isolates were sensitive and resistant to gentamicin, respectiv

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Publication Date
Thu Feb 27 2020
Journal Name
Iraqi Journal Of Science
Gene Expression of pelA and pslA in Pseudomonas Aeruginosa under Gentamicin Stress
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     Pseudomonas aeruginosa produces an extracellular biofilm matrix that consists of nucleic acids, exopolysaccharides, lipid vesicles, and proteins. Alginate, Psl and Pel are three exopolysaccharides that constitute the main components in biofilm matrix, with many biological functions attributed to them, especially concerning the protection of the bacterial cell from antimicrobial agents and immune responses. A total of 25 gentamicin-resistant P. aeruginosa selected isolates were enrolled in this study. Biofilm development was observed in 96% of the isolates. In addition, the present results clarified the presence of pelA and pslA in all the studied isolates. The expression of these genes was very low. Even though all biof

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Publication Date
Tue Jan 01 2019
Journal Name
Iraqi Journal Of Agricultural Sciences
Cloning and expression of a lipase gene from Pseudomonas aeruginosa into E.coli
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Fifteen local isolates of Pseudomonas were obtained from several sources such as soil, water and some high-fat foods (Meat, olives, coconuts, etc.). The ability of isolates to produce lipase was measured by the size of clear zone on Tween 20 solid medium and by measuring the enzymatic activity and specific activity. Isolate M3 (as named in this study) was found to be the most efficient for the production of the lipase with enzymatic activity reached 56.6 U/ml and specific activity of 305.94 U/mg. This isolate was identified through genetic analysis of the 16S rRNA gene. and it was shown that the isolate M3 belongs to Pseudomonas aeruginosa with 99% similarity. The DNA of isolate M3 was extracted and lipase gene was amplified through PCR tec

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Publication Date
Sun Mar 04 2012
Journal Name
Baghdad Science Journal
Using fuzzy logic for estimating monthly pan evaporation from meteorological data in Emara/ South of Iraq
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Evaporation is one of the major components of the hydrological cycle in the nature, thus its accurate estimation is so important in the planning and management of the irrigation practices and to assess water availability and requirements. The aim of this study is to investigate the ability of fuzzy inference system for estimating monthly pan evaporation form meteorological data. The study has been carried out depending on 261 monthly measurements of each of temperature (T), relative humidity (RH), and wind speed (W) which have been available in Emara meteorological station, southern Iraq. Three different fuzzy models comprising various combinations of monthly climatic variables (temperature, wind speed, and relative humidity) were developed

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Publication Date
Wed Oct 01 2008
Journal Name
2008 First International Conference On Distributed Framework And Applications
A strategy for Grid based t-way test data generation
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Publication Date
Wed Feb 06 2013
Journal Name
Eng. & Tech. Journal
A proposal to detect computer worms (malicious codes) using data mining classification algorithms
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Malicious software (malware) performs a malicious function that compromising a computer system’s security. Many methods have been developed to improve the security of the computer system resources, among them the use of firewall, encryption, and Intrusion Detection System (IDS). IDS can detect newly unrecognized attack attempt and raising an early alarm to inform the system about this suspicious intrusion attempt. This paper proposed a hybrid IDS for detection intrusion, especially malware, with considering network packet and host features. The hybrid IDS designed using Data Mining (DM) classification methods that for its ability to detect new, previously unseen intrusions accurately and automatically. It uses both anomaly and misuse dete

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Publication Date
Tue Oct 31 2023
Journal Name
Onkologia I Radioterapia
The prevalence of HSV1 expression in Iraqi patients with colorectal cancer
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Background: Colorectal Cancer (CRC) is one of the most serious health problems and Herpes viridae may hasten the progression of colon cancer. Aim: The purpose of conducting this research is to investigate the existence of Herpes Simplex Virus (HSV1) infection in samples of Colorectal Cancer (CRC) compared with normal tissue. Material and Methods: 40 samples of tissues (30 patients ) with CRC, and (10 samples) of normal tissue (without cancer) were obtained, for immunohistochemically analysis of Herpes Simplex Virus (HSV1) expression Results: The results showed no significant data to justify the link between both Herpes Simplex Virus (HSV1) and human colorectal cancer. Despite of presence of Herpes Simplex Virus (HSV1) found in

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Scopus
Publication Date
Tue Aug 01 2023
Journal Name
Biochemical And Cellular Archives
Interleukin-32(IL-32) gene expression in Iraqi chronic hepatitis B virus patients
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Hepatitis B infection is a prominent infectious disease caused by hepatitis B virus (HBV), which infect liver and is considered as the main cause of liver cirrhosis, fibrosis and liver cancer worldwide. A pro-inflammatory cytokine Interleukin32 is believed to have a role in chronic HBV infections. Since its role in CHB infections is remain unclear, this study was done to detect IL-32 gene expression in CHB patients in order to identify its exact role. A total number of 110 blood samples were collected from Gastroenterology and Hepatology Teaching Hospital in Baghdad Medical City from CHB patients for both males and females with different age groups according to the research ethics form then sent to Central Public Health Laboratory (CPHL),

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Publication Date
Sun Jul 01 2018
Journal Name
Journal Of Global Pharma Technology
Gentamicin Modulates the Gene Expression of hla in Methicillin Resistance Staphylococcus aureus Biofilm
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Objective: The present work was undertaken to investigate the impact of sub inhibitory concentration of gentamicin on hla gene expression in methicillin resistant Staphylococcus aureus isolates. Methods: The bacterial isolates used in this study represent 33 MRSA strains, previously isolated form patients visiting several hospitals in Baghdad. Gentamicin, vancomycin, and oxacillin MIC were determined using broth dilution method. Microtiter plate method was adopted to investigate the biofilm forming capacity. Alpha hemolysin was detected by culturing MRSA isolates on rabbit blood agar. Furthermore, hla gene was detected in MRSA isolates using conventional PCR technique; while, qRT-PCR method was performed to assay the hla expression in plank

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Publication Date
Sat Aug 02 2025
Journal Name
Engineering, Technology & Applied Science Research
A New Method for Face-Based Recognition Using a Fuzzy Face Deep Model
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Face recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security

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