Cancer is in general not a result of an abnormality of a single gene but a consequence of changes in many genes, it is therefore of great importance to understand the roles of different oncogenic and tumor suppressor pathways in tumorigenesis. In recent years, there have been many computational models developed to study the genetic alterations of different pathways in the evolutionary process of cancer. However, most of the methods are knowledge-based enrichment analyses and inflexible to analyze user-defined pathways or gene sets. In this paper, we develop a nonparametric and data-driven approach to testing for the dynamic changes of pathways over the cancer progression. Our method is based on an expansion and refinement of the pathway being studied, followed by a graph-based multivariate test, which is very easy to implement in practice. The new test is applied to the rich Cancer Genome Atlas data to study the (epi)genetic alterations of 186 KEGG pathways in the development of serous ovarian cancer. To make use of the comprehensive data, we incorporate three data types in the analysis representing gene expression level, copy number and DNA methylation level. Our analysis suggests a list of nine pathways that are closely associated with serous ovarian cancer progression, including cell cycle, ERBB, JAK-STAT signaling and p53 signaling pathways. By pairwise tests, we found that most of the identified pathways contribute only to a particular transition step. For instance, the cell cycle and ERBB pathways play key roles in the early-stage transition, while the ECM receptor and apoptosis pathways contribute to the progression from stage III to stage IV. The proposed computational pipeline is powerful in detecting important pathways and gene sets that drive cancers at certain stage(s). It offers new insights into the understanding of molecular mechanism of cancer initiation and progression. © 2020 Elsevier Ltd
The research seeks to identify the factors affecting the monopoly and the possibility of measuring the phenomenon of economic ( monopolistic profit) accounted for and that the importance of research topic arising from the transformation of the majority of developing countries to the market economy, which represents the image of the capitalist economy, which is a monopoly, a stages that economy in its various forms, whether Market Worldwide sales monopoly or monopoly, which generates absolute monopolistic profits, which more or less affect on the overall economy of those countries than they should study the phenomenon of monopoly and its impact on the economies of those countries that still love to find her site reinforces its pos
... Show MoreThe geophysical testing is increasingly being employed in many geotechnical applications. It is preferred in monitoring the mechanical characteristics of the ground because of its economy, not time consuming and non-destructive nature. Seismic wave test is one of the geophysical methods which showed a potential in observing the general behaviour of the reinforced soil with stone columns. Findings in most cases showed that the seismic wave measurements was integrated with or compared to the conventional tests such as standard penetration test or cone penetration test. There was a noticeable success in identifying the enhancement achieved to the ground upon the strengthening with the column, specifically when the associated surveys can produc
... Show MoreTchebichef polynomials (TPs) play a crucial role in various fields of mathematics and applied sciences, including numerical analysis, image and signal processing, and computer vision. This is due to the unique properties of the TPs and their remarkable performance. Nowadays, the demand for high-quality images (2D signals) is increasing and is expected to continue growing. The processing of these signals requires the generation of accurate and fast polynomials. The existing algorithms generate the TPs sequentially, and this is considered as computationally costly for high-order and larger-sized polynomials. To this end, we present a new efficient solution to overcome the limitation of sequential algorithms. The presented algorithm us
... Show MoreAbstract The purpose of this study, teach the art of performing Olympic lifts (snatch and, clean and jerk) using the two methods are instructional (self-learning associated with the model) and (reverse style of partial way). Identify the effectiveness of these methods in learning the art of performance and style of the best Olympic lifting in the learning and retention of novice for Olympic lifts. The research sample consisted of 16 lifters were selected purposively representing specialist center for the care of athletic talent to weightlifting for ages 14 years. The sample was divided into two experimental, Each group (8) eight weightlifters. The experimental group used the style of the first self-learning associated with the m
... Show MoreAlterations of trace element concentrations adversely affect biological processes and could promote carcinogenesis. Trace element deficiency or excess is implicated in the development or progression of some cancers like colorectal cancer. The aim of the present study was to compare the serum copper (Cu) and zinc (Zn) concentrations in patients with colorectal cancer from Iraqi male patient with those of healthy subjects. During the period of March 2015 until august 2015, a total of 25 patients with metastatic colon cancer and 20 healthy volunteers were enrolled from the Al-Kadhimia Teaching Hospital after the diagnosis using a histopathological examination for the malignant tumor; their age was between (38-60) years. Higher levels o
... Show MoreDisease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature
... Show MoreThe study included the collection of 75 bronchial wash samples from patients suspected to have lung cancer. These samples were subjected to a diagnostic cytological study to detect the dominant type of lung cancer. It was noticed that 33 patients proved to have a lung cancer out of 75 (44%) of these, 19 cases (57.6%)were diagnosed having Squamus cell carcinoma,7cases (21.21%) showed Adenocarcinoma ,6 cases (18.18%) were having small cell carcinoma while only one case (3.03%)was large cell carcinoma .Nearly 70% of cases were correlated with smokers .Bacteria were isolated from 53 patients in which 33 isolates were associated with the cancer cases while 20 of them from non infected patients. By using different morphological ,biochemical test
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