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https://www.readbyqxmd.com/read/28742206/bioinformatics-analysis-of-rna-seq-data-revealed-critical-genes-in-colon-adenocarcinoma
#1
W-D Xi, Y-J Liu, X-B Sun, J Shan, L Yi, T-T Zhang
OBJECTIVE: RNA-seq data of colon adenocarcinoma (COAD) were analyzed with bioinformatics tools to discover critical genes in the disease. Relevant small molecule drugs, transcription factors (TFs) and microRNAs (miRNAs) were also investigated. MATERIALS AND METHODS: RNA-seq data of COAD were downloaded from The Cancer Genome Atlas (TCGA). Differential analysis was performed with package edgeR. False positive discovery (FDR) < 0.05 and |log2 (fold change)|>1 were set as the cut-offs to screen out differentially expressed genes (DEGs)...
July 2017: European Review for Medical and Pharmacological Sciences
https://www.readbyqxmd.com/read/28741222/network-of-anatomical-texts-nanatex-an-open-source-project-for-visualizing-the-interaction-between-anatomical-terms
#2
Ryusuke Momota, Aiji Ohtsuka
Anatomy is the science and art of understanding the structure of the body and its components in relation to the functions of the whole-body system. Medicine is based on a deep understanding of anatomy, but quite a few introductory-level learners are overwhelmed by the sheer amount of anatomical terminology that must be understood, so they regard anatomy as a dull and dense subject. To help them learn anatomical terms in a more contextual way, we started a new open-source project, the Network of Anatomical Texts (NAnaTex), which visualizes relationships of body components by integrating text-based anatomical information using Cytoscape, a network visualization software platform...
July 24, 2017: Anatomical Science International
https://www.readbyqxmd.com/read/28739725/high-efficient-screening-method-for-identification-of-key-genes-in-breast-cancer-through-microarray-and-bioinformatics
#3
Zihao Liu, Gehao Liang, Luyuan Tan, A N Su, Wenguo Jiang, Chang Gong
BACKGROUND/AIM: The aim of the present study was to identify key pathways and genes in breast cancer and develop a new method for screening key genes with abnormal expression based on bioinformatics. MATERIALS AND METHODS: Three microarray datasets GSE21422, GSE42568 and GSE45827 were downloaded from the Gene Expression Omnibus (GEO) database and differentially expressed genes (DEGs) were analyzed using GEO2R. The gene ontology (GO) and pathway enrichment analysis were established through DAVID database...
August 2017: Anticancer Research
https://www.readbyqxmd.com/read/28731857/cytomcs-a-multiple-maximum-common-subgraph-detection-tool-for-cytoscape
#4
Simon J Larsen, Jan Baumbach
Comparative analysis of biological networks is a major problem in computational integrative systems biology. By computing the maximum common edge subgraph between a set of networks, one is able to detect conserved substructures between them and quantify their topological similarity. To aid such analyses we have developed CytoMCS, a Cytoscape app for computing inexact solutions to the maximum common edge subgraph problem for two or more graphs. Our algorithm uses an iterative local search heuristic for computing conserved subgraphs, optimizing a squared edge conservation score that is able to detect not only fully conserved edges but also partially conserved edges...
July 21, 2017: Journal of Integrative Bioinformatics
https://www.readbyqxmd.com/read/28731166/screening-of-the-prognostic-targets-for-breast-cancer-based-co-expression-modules-analysis
#5
Huijuan Liu, Hui Ye
The purpose of the present study was to screen the prognostic targets for breast cancer based on a co-expression modules analysis. The microarray dataset GSE73383 was downloaded from the Gene Expression Omnibus (GEO) database, including 15 breast cancer samples with good prognosis and 9 breast cancer samples with poor prognosis. The differentially expressed genes (DEGs) were identified with the limma package. The Database for Annotation, Visualization and Integrated Discovery was used to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis...
July 21, 2017: Molecular Medicine Reports
https://www.readbyqxmd.com/read/28723760/bioinformatics-analysis-to-identify-the-critical-genes-micrornas-and-long-noncoding-rnas-in-melanoma
#6
Qian Zhang, Yang Wang, Jiulong Liang, Yaguang Tian, Yu Zhang, Kai Tao
Melanoma, which is usually induced by ultraviolet light exposure and the following DNA damage, is the most dangerous skin cancer. The purpose of the present study was to screen key molecules involved in melanoma.Microarray data of E-MTAB-1862 were downloaded from the ArrayExpress database, which included 21 primary melanoma samples and 11 benign nevus samples. In addition, the RNASeq version 2 and microRNA (miRNA) sequencing data of cutaneous melanoma were downloaded from The Cancer Genome Atlas database. After identifying the differentially expressed genes (DEGs) using Limma package, enrichment analysis and protein-protein interaction (PPI) network analysis were performed separately for them using DAVID software and Cytoscape software...
July 2017: Medicine (Baltimore)
https://www.readbyqxmd.com/read/28714020/potential-role-of-upregulated-microrna%C3%A2-146b-and-%C3%A2-21-in-renal-fibrosis
#7
Guangda Xin, Guangyu Zhou, Xiaofei Zhang, Wanning Wang
The aim of the present study was to identify candidate microRNAs (miRNAs) involved in the progression of renal fibrosis. Dataset GSE42716 of miRNAs extracted from kidneys from mice with unilateral ureteral obstruction (UUO), and mice without UUO was downloaded from the Gene Expression Omnibus database. The Limma package was used to identify differential expression between mice with and without UUO. Renal disease‑related miRNAs were predicted based on the miRWalk database. Thereafter, candidate miRNAs were screened by taking the intersection of differentially expressed miRNAs and predicted miRNAs, followed by screening of target genes using miRWalk and transcription factors using the TransmiR database...
September 2017: Molecular Medicine Reports
https://www.readbyqxmd.com/read/28714002/identification-of-key-genes-in-gram%C3%A2-positive-and-gram%C3%A2-negative-sepsis-using-stochastic-perturbation
#8
Zhenliang Li, Ying Zhang, Yaling Liu, Yanchun Liu, Youyi Li
Sepsis is an inflammatory response to pathogens (such as Gram‑positive and Gram‑negative bacteria), which has high morbidity and mortality in critically ill patients. The present study aimed to identify the key genes in Gram‑positive and Gram‑negative sepsis. GSE6535 was downloaded from Gene Expression Omnibus, containing 17 control samples, 18 Gram‑positive samples and 25 Gram‑negative samples. Subsequently, the limma package in R was used to screen the differentially expressed genes (DEGs). Hierarchical clustering was conducted for the specific DEGs in Gram‑negative and Gram‑negative samples using cluster software and the TreeView software...
September 2017: Molecular Medicine Reports
https://www.readbyqxmd.com/read/28713993/gene-microarray-analysis-of-expression-profiles-in-liver-ischemia-and-reperfusion
#9
Xiaoyang Zheng, Huaqiang Zhou, Zeting Qiu, Shaowei Gao, Zhongxing Wang, Liangcan Xiao
Liver ischemia and reperfusion (I/R) injury is of primary concern in cases of liver disease worldwide and is associated with hemorrhagic shock, resection and transplantation. Numerous studies have previously been conducted to investigate the underlying mechanisms of liver I/R injury, however these have not yet been fully elucidated. To determine the difference between ischemia and reperfusion in signaling pathways and the relative pathological mechanisms, the present study downloaded microarray data GSE10657 from the Gene Expression Omnibus database...
September 2017: Molecular Medicine Reports
https://www.readbyqxmd.com/read/28713977/analysis-of-gene-expression-profile-microarray-data-in-complex-regional-pain-syndrome
#10
Wulin Tan, Yiyan Song, Chengqiang Mo, Shuangjian Jiang, Zhongxing Wang
The aim of the present study was to predict key genes and proteins associated with complex regional pain syndrome (CRPS) using bioinformatics analysis. The gene expression profiling microarray data, GSE47603, which included peripheral blood samples from 4 patients with CRPS and 5 healthy controls, was obtained from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) in CRPS patients compared with healthy controls were identified using the GEO2R online tool. Functional enrichment analysis was then performed using The Database for Annotation Visualization and Integrated Discovery online tool...
September 2017: Molecular Medicine Reports
https://www.readbyqxmd.com/read/28713952/exploration-of-the-sequential-gene-changes-in-epithelial-ovarian-cancer-induced-by-carboplatin-via-microarray-analysis
#11
Shuqing Wei, Jianwu Liu, Yuxia Shi, Xi Zhang, Yongming Yang, Qingzhen Song
The purpose of the current study was to explore the carboplatin‑induced sequential changes in gene expression and screen out key genes, which were associated with effects of carboplatin on epithelial ovarian cancer (EOC). The microarray dataset GSE13525 was downloaded from the Gene Expression Omnibus database, including 6 EOC cell samples separately treated with carboplatin at 24, 30 and 36 h (case group), and 6 samples treated with phosphate‑buffered saline at the same time points (control group). A total of 3 sets of differentially expressed genes (DEGs) were respectively identified in case samples at 24, 30 and 36 h compared with the control group via the Limma package, and separately recorded as DEG‑24, DEG‑30 and DEG‑36...
September 2017: Molecular Medicine Reports
https://www.readbyqxmd.com/read/28713940/a-novel-method-to-identify-hub-pathways-of-rheumatoid-arthritis-based-on-differential-pathway-networks
#12
Shi-Tong Wei, Yong-Hua Sun, Shi-Hua Zong
The aim of the current study was to identify hub pathways of rheumatoid arthritis (RA) using a novel method based on differential pathway network (DPN) analysis. The present study proposed a DPN where protein‑protein interaction (PPI) network was integrated with pathway‑pathway interactions. Pathway data was obtained from background PPI network and the Reactome pathway database. Subsequently, pathway interactions were extracted from the pathway data by building randomized gene‑gene interactions and a weight value was assigned to each pathway interaction using Spearman correlation coefficient (SCC) to identify differential pathway interactions...
September 2017: Molecular Medicine Reports
https://www.readbyqxmd.com/read/28713939/microarray-analysis-reveals-key-genes-and-pathways-in-tetralogy-of-fallot
#13
Yue-E He, Hui-Xian Qiu, Jian-Bing Jiang, Rong-Zhou Wu, Ru-Lian Xiang, Yuan-Hai Zhang
The aim of the present study was to identify key genes that may be involved in the pathogenesis of Tetralogy of Fallot (TOF) using bioinformatics methods. The GSE26125 microarray dataset, which includes cardiovascular tissue samples derived from 16 children with TOF and five healthy age‑matched control infants, was downloaded from the Gene Expression Omnibus database. Differential expression analysis was performed between TOF and control samples to identify differentially expressed genes (DEGs) using Student's t‑test, and the R/limma package, with a log2 fold‑change of >2 and a false discovery rate of <0...
September 2017: Molecular Medicine Reports
https://www.readbyqxmd.com/read/28713898/identification-of-potential-biomarkers-and-therapeutic-targets-for-human-iga-nephropathy-and-hypertensive-nephropathy-by-bioinformatics-analysis
#14
Yingchun Cui, Shengmao Liu, Wenpeng Cui, Dan Gao, Wenhua Zhou, Ping Luo
In order to further elucidate the potential correlations and treatments of IgA nephropathy (IgAN) and hypertensive nephropathy (HT), bioinformatics analysis of IgAN and HT was performed. The mRNA expression profiles of human renal biopsy samples from patients with IgAN, patients with HT and pre‑transplant healthy living controls (LD) were downloaded from the Gene Expression Omnibus database. Then, the differentially expressed genes (DEGs) were identified and functions of DEGs were analyzed. Finally, the regulatory networks containing DEGs and related‑transcription factors (TFs) were constructed using Cytoscape software...
September 2017: Molecular Medicine Reports
https://www.readbyqxmd.com/read/28694847/arete-candidate-gene-prioritization-using-biological-network-topology-with-additional-evidence-types
#15
Artem Lysenko, Keith Anthony Boroevich, Tatsuhiko Tsunoda
BACKGROUND: Refinement of candidate gene lists to select the most promising candidates for further experimental verification remains an essential step between high-throughput exploratory analysis and the discovery of specific causal genes. Given the qualitative and semantic complexity of biological data, successfully addressing this challenge requires development of flexible and interoperable solutions for making the best possible use of the largest possible fraction of all available data...
2017: BioData Mining
https://www.readbyqxmd.com/read/28693226/screening-of-potentially-crucial-genes-and-regulatory-factors-involved-in-epithelial-ovarian-cancer-using-microarray-analysis
#16
Can Shi, Zhenyu Zhang
The present study aimed to screen potential genes implicated in epithelial ovarian cancer (EOC) and to further understand the molecular pathogenesis of EOC. In order to do this, datasets GSE14407 (containing 12 human ovarian cancer epithelia samples and 12 normal epithelia samples) and GSE29220 (containing 11 salivary transcriptomes from ovarian cancer patients with serous papillary adenocarcinoma and 11 matched controls) were obtained from the Gene Expression Omnibus. Differentially expressed genes (DEGs) within these datasets were screened using the Linear Models for Microarray Data package, and potential gene functions were predicted by functional and pathway enrichment analyses...
July 2017: Oncology Letters
https://www.readbyqxmd.com/read/28691013/identification-of-pharmacologically-tractable-protein-complexes-in-cancer-using-the-r-based-network-clustering-and-visualization-program-mcoder
#17
Sungjin Kwon, Hyosil Kim, Hyun Seok Kim
Current multiomics assay platforms facilitate systematic identification of functional entities that are mappable in a biological network, and computational methods that are better able to detect densely connected clusters of signals within a biological network are considered increasingly important. One of the most famous algorithms for detecting network subclusters is Molecular Complex Detection (MCODE). MCODE, however, is limited in simultaneous analyses of multiple, large-scale data sets, since it runs on the Cytoscape platform, which requires extensive computational resources and has limited coding flexibility...
2017: BioMed Research International
https://www.readbyqxmd.com/read/28677800/microrna-and-target-mrna-selection-through-invasion-and-cytotoxicity-cell-modeling-and-bioinformatics-approaches-in-esophageal-squamous-cell-carcinoma
#18
Mu Lu, Yaqin Song, Wenbo Fu, Yang Liu, Shitao Huai, Xiaobin Cui, Lijuan Pang, Lan Yang, Yutao Wei
This study analyzed microRNA (miRNA) and mRNA expression profiles and investigated the biological characteristics of ESCC by using invasion and cytotoxicity cell models. miRNA profiles were evaluated through miRNA microarray. Transwell chamber and nedaplatin (NDP) were used to construct invasion and cytotoxicity cell models. Invasion Transwell and cytotoxicity assays were performed to examine the invasiveness and proliferation in the cell models. Functional miRNAs were selected from dysregulated miRNAs through qRT-PCR...
June 30, 2017: Oncology Reports
https://www.readbyqxmd.com/read/28673327/special-role-of-jun-in-papillary-thyroid-carcinoma-based-on-bioinformatics-analysis
#19
Wenzheng Chen, Qingfeng Liu, Yunxia Lv, Debin Xu, Wanzhi Chen, Jichun Yu
BACKGROUND: Papillary thyroid carcinoma (PTC) is the most common malignancy in thyroid tissue, and the number of patients with PTC has been increasing in recent years. Discovering the mechanism of PTC genesis and progression and finding new potential diagnostic biomarkers/therapeutic target genes of PTC are of great significance. METHODS: In this work, the datasets GSE3467 and GSE3678 were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified with the limma package in R...
July 3, 2017: World Journal of Surgical Oncology
https://www.readbyqxmd.com/read/28670134/identification-of-key-genes-and-molecular-mechanisms-associated-with-dedifferentiated-liposarcoma-based-on-bioinformatic-methods
#20
Hongliang Yu, Dong Pei, Longyun Chen, Xiaoxiang Zhou, Haiwen Zhu
BACKGROUND: Dedifferentiated liposarcoma (DDLPS) is one of the most deadly types of soft tissue sarcoma. To date, there have been few studies dedicated to elucidating the molecular mechanisms behind the disease; therefore, the molecular mechanisms behind this malignancy remain largely unknown. MATERIALS AND METHODS: Microarray profiles of 46 DDLPS samples and nine normal fat controls were extracted from Gene Expression Omnibus (GEO). Quality control for these microarray profiles was performed before analysis...
2017: OncoTargets and Therapy
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