One of the recent significant but challenging research studies in computational biology and bioinformatics is to unveil protein complexes from protein-protein interaction networks (PPINs). However, the development of a reliable algorithm to detect more complexes with high quality is still ongoing in many studies. The main contribution of this paper is to improve the effectiveness of the well-known modularity density ( ) model when used as a single objective optimization function in the framework of the canonical evolutionary algorithm (EA). To this end, the design of the EA is modified with a gene ontology-based mutation operator, where the aim is to make a positive collaboration between the modularity density model and the proposed

Background: Toxoplasmosis is a very common infection caused by the obligate intracellular protozoan parasite. This parasite is called Toxoplasma gondii widely distributed around the world . Toxoplasma gondii can be vertically transmitted to the fetus during pregnancy and may cause wide range of clinical manifestations in the offspring.

Objective: To determine seroprevalence Immunoglobulin G (IgG) and Immunoglobulin M  (IgM ) to toxoplasma gondii among pregnant women and to identify the risk factors.

Type of the study: A cross-sectional study.

Methods: A total of 110 blood samples of pregnant women were collected from

Molecular farming has become one of the most significant implementations of modern biotechnology to generate modified plant crops to produce medicinal proteins. Agrobacterium is one plant genetic engineering tool that integrates genes of interest inside a host plant.  In recent years, the need to produce recombinant proteins as therapeutics has growing rapidly, and human glucocerebrosidase is one of the proteins that is need to treat disease. In this study, specific primers were designed to amplify Hu-GBA1 gene from constructed pGEM-GBA plasmid which was cloned into the plant expression vector pCAMBIA1304. The generated recombinant pCAMBIA1304-GBA plasmid was used to transform A. tumefaciens LBA4404

Objective: Assessment the psychological problems in patients with colorectal cancer, and to find out the
relationship between socio-demographic characteristics such as (age, sex, marital status, educational level,
and occupation) and psychological problems for those patients.
Methodology: A descriptive design is employed through the present study from 1
st July 2011 to 25
th December
2011 in order to study the quality of life in colorectal cancer patients with psychological problems.
A purposive (non probability) sample is selected for the study which includes (60) patients diagnosed with
colorectal cancer were treated in Mosul Oncology and Nuclear Medicine hospital or the patients who visited
the outpatient cl

It is considered as one of the statistical methods used to describe and estimate the relationship between randomness (Y) and explanatory variables (X). The second is the homogeneity of the variance, in which the dependent variable is a binary response takes two values  (One when a specific event occurred and zero when that event did not happen) such as (injured and uninjured, married and unmarried) and that a large number of explanatory variables led to the emergence of the problem of linear multiplicity that makes the estimates inaccurate, and the method of greatest possibility and the method of declination of the letter was used in estimating A double-response logistic regression model by adopting the Jackna

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, whic

It is considered as one of the statistical methods used to describe and estimate the relationship between randomness (Y) and explanatory variables (X). The second is the homogeneity of the variance, in which the dependent variable is a binary response takes two values  (One when a specific event occurred and zero when that event did not happen) such as (injured and uninjured, married and unmarried) and that a large number of explanatory variables led to the emergence of the problem of linear multiplicity that makes the estimates inaccurate, and the method of greatest possibility and the method of declination of the letter was used in estimating A double-response logistic regression model by adopting the Jackna