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Mar 31, 2023Open    Access

Identification of Hub Genes in Prostate Cancer by Bioinformatics Analysis

Rui Zhang, Wenhua Guo, Luhong Yang
Objective: To identify the candidate hub genes of prostate cancer (PCa) and investigate the relevance of the genes on the development of PCa by bioinformatics methods. Methods: The mRNA expression profile datasets GSE103512 was collected from GEO database, and find out differential expression genes (DEGs) between PCa and normal tissues using the GEO2R tool. Subsequently, to further elucidate the interaction of DEGs and screen the hub genes, we conducted GO and KEGG enrichment analysis by DAVID 6...
Open Access Library J.   Vol.10, 2023
Doi:10.4236/oalib.1109747


Nov 30, 2022Open    Access

Distribution Estimation of Invasive Species Based on Crowdsourcing Reports

Yuxin Shi, Siyuan Liu, Tingzhen Liu
Species invasion will cause certain harm to the local ecosystem. Vespa mandarinia, discovered on Vancouver Island, is harmful to agriculture and predators of European honeybees. The government tried to use a crowdsourcing system to collect information and formulate policies to eliminate Vespa mandarinia. However, the information provided by the local population about Vespa mandarinia is not entirely accurate. For this problem, we build a method to mine trusted informat...
Open Access Library J.   Vol.9, 2022
Doi:10.4236/oalib.1109474


May 23, 2022Open    Access

A Bibliometric Analysis of the Research about Radical S-Adenosyl-Methionine Enzymes in 1999-2020

Pan Jiang, Huan Zhao, Lei Liu, Yuting Zhao, Ting Su, Yufan Yang, Xue Li
This paper aims to clarify the current research status and hot spots, as well as to predict future research trends about radical S-adenosyl-methionine (SAM) enzymes. We conducted this study based on 649 research papers about radical SAM enzymes published in the years of 1999 to 2020 on the Web of Science. Tools like CiteSpace were employed for statistical and visual network analysis of the time of publication, national cooperative relations, core authors, and co-word networks. Our findings inclu...
Open Access Library J.   Vol.9, 2022
Doi:10.4236/oalib.1108701


Sep 01, 2020Open    Access

A Consensus Mechanism Based on an Improved Genetic Algorithm

Chen Yang, Tao Wang, Kun Wang
An important feature of blockchain technology is that all participants jointly maintain transaction data and can achieve mutual trust relationships without integrated control, which relies on distributed consensus algorithms. Practical Byzantine Fault Tolerant algorithm (PBFT) is a fault-tolerant algorithm based on state machine replication, which solves the Byzantine error, that is, the malicious behavior of nodes. In PBFT, all participating nodes are divided into the primary node and backup no...
Open Access Library J.   Vol.7, 2020
Doi:10.4236/oalib.1106713


Jun 24, 2020Open    Access

Study on Patterns of Human Cancer Using SSN Method

Chaoyu Zhang
Human cancer, which has complex pathogenesis, is generally relative to the dysfunction of biological systems. Thus, our research is not at molecular level, but at system level, i.e. molecular network. In this paper, specially, we use PPI network. In order to construct a PPI network, we used the SSN method which is proposed by Professor X. Liu and others. The SSN method is distinct from the traditional network methods, especially in screening differential expressed genes. Besides, the traditional...
Open Access Library J.   Vol.7, 2020
Doi:10.4236/oalib.1106453


Mar 15, 2018Open    Access

Detection of Horizontal Transfer of Housekeeping and Hydrocarbons Catabolism Genes in Bacterial Genus with Potential to Application in Bioremediation Process

Edmo Montes Rodrigues, Fernanda de Souza Freitas, Tatiane de Paula Siqueira
In silico analysis can be useful to infer about the horizontal gene transfer (HGT) as well as to deduce about the evolutionary relations of catabolic genes. In this study, we performed the analysis of two housekeeping genes (fabD and rpoD) and two catabolic gene
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Open Access Library J.   Vol.5, 2018
Doi:10.4236/oalib.1104454


Mar 12, 2018Open    Access

Different Protocols of Physical Training: Effect on Markers of Oxidative Stress in Erythrocytes in Rats

Marcelo Costa-Junior, Wener Barbosa-Resende, Michel Barbosa de Araújo, Rodrigo Augusto Dalia, Leandro Pereira de Moura, Luciana Alves de Medeiros, Lucas Moreira Cunha, Eliete Luciano
The imbalance between oxidant molecules and antioxidant agents is characterized as oxidative stress (OS) and may lead to severe damage to the organism. In contrast, the physical training of aerobic and resistive character promotes increases of the antioxidant response, resulting in a balance and/or minimizing damage. Therefore, the objective of the study is to verify the effect of aerobic training, resistive training and concurren
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Open Access Library J.   Vol.5, 2018
Doi:10.4236/oalib.1104411


Jul 29, 2016Open    Access

Comprehensive Analysis of rsSNPs Associated with Hypertension Using In-Silico Bioinformatics Tools

Alsadig Gassoum, Nahla E. Abdelraheem, Nehad Elsadig
Genetic epidemiological studies have suggested that several genetic variants increase the risk for hypertension. It is likely that a number of genes rather than a single gene account for the heritability of this complex disorder. However, the genetic analysis of hypertension produced complex, inconsistent and nonreproducible results, which makes it difficult to draw conclusions about the association between specific genes and hype
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Open Access Library J.   Vol.3, 2016
Doi:10.4236/oalib.1102839


Mar 30, 2016Open    Access

Gapped Motif Discovery with Multi-Objective Genetic Algorithm

U. Angela Makolo, Salihu O. Suberu
Motif discovery is one of the fundamental problems that have important applications in identifying drug targets and regulatory sites. Regulatory sites on DNA sequence normally correspond to shared conservative sequence patterns among the regulatory regions of correlated genes. These conserved sequence patterns are called motifs. Identifying motifs and corresponding instances is very important, so biologists can investigate the interactions between DNA and proteins, gene regulation, cell developm...
Open Access Library J.   Vol.3, 2016
Doi:10.4236/oalib.1102293


Sep 24, 2014Open    Access

Comparative Analysis of Different Classifiers for the Wisconsin Breast Cancer Dataset

Leena Vig
The Wisconsin Breast Cancer Dataset has been heavily cited as a benchmark dataset for classification. Neural Network techniques such as Neural Networks, Probabilistic Neural Networks, and Regression Neural Networks have been shown to perform very well on this dataset. However, despite its obvious practical importance and implications for cancer research, a thorough investigation of all modern classification techniques on this dataset remains to be done. In this paper we examine the efficacy of c...
Open Access Library J.   Vol.1, 2014
Doi:10.4236/oalib.1100660


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