Tag: cytoscape

Immune-related Prognostic Genes of ccRCC

Introduction Kidney cancer is one of the most commonly diagnosed tumors around the globe.1 According to the statistics from the World Health Organization, annually, there are more than 140,000 RCC-related deaths.2 ccRCC is the most typical subtype of kidney cancer and contributes to the majority of kidney cancer-related deaths.3,4 Until…

Continue Reading Immune-related Prognostic Genes of ccRCC

Identification of differentially expressed genes in AF

Defeng Pan,1,* Yufei Zhou,2,* Shengjue Xiao,1,* Yue Hu,3,* Chunyan Huan,1 Qi Wu,1 Xiaotong Wang,1 Qinyuan Pan,1 Jie Liu,1 Hong Zhu1 1Department of Cardiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, 221004, People’s Republic of China; 2Department of Cardiology, Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital and Institutes of…

Continue Reading Identification of differentially expressed genes in AF

Decoding gene regulation in the fly brain

1. Li, H. et al. Classifying Drosophila olfactory projection neuron subtypes by single-cell RNA sequencing. Cell 171, 1206–1220 (2017). CAS  PubMed  PubMed Central  Google Scholar  2. Davie, K. et al. A single-cell transcriptome atlas of the aging Drosophila brain. Cell 174, 982–998 (2018). CAS  PubMed  PubMed Central  Google Scholar  3….

Continue Reading Decoding gene regulation in the fly brain

Bioinformation Analysis Reveals IFIT1 as Potential Biomarkers in Centr

Introduction Tuberculosis (TB) is considered to be one of the top ten causes of death in the world, about a quarter of the world’s population is infected with M. tuberculosis.1 The World Health Organization (WHO) divides tuberculosis into pulmonary tuberculosis (PTB) and extra-pulmonary tuberculosis (EPTB). Although breakthroughs have been made…

Continue Reading Bioinformation Analysis Reveals IFIT1 as Potential Biomarkers in Centr

Bioinformatics analysis of long non-coding RNA-associated competing endogenous RNA network in schizophrenia

1. Marder, S. R. & Cannon, T. D. Schizophrenia. N. Engl. J. Med. 381, 1753–1761. doi.org/10.1056/NEJMra1808803 (2019). Article  PubMed  CAS  Google Scholar  2. Keshavan, M. S. et al. Neuroimaging in Schizophrenia. Neuroimaging Clin. N. Am. 30, 73–83. doi.org/10.1016/j.nic.2019.09.007 (2020). Article  PubMed  Google Scholar  3. McCutcheon, R. A., Reis Marques, T….

Continue Reading Bioinformatics analysis of long non-coding RNA-associated competing endogenous RNA network in schizophrenia

GeneTonic: an R/Bioconductor package for streamlining the interpretation of RNA-seq data | BMC Bioinformatics

1. Van den Berge K, Hembach KM, Soneson C, Tiberi S, Clement L, Love MI, Patro R, Robinson MD. RNA sequencing data: Hitchhikers guide to expression analysis. Annu Rev Biomed Data Sci. 2019;2(1):139–73. doi.org/10.1146/annurev-biodatasci-072018-021255. Article  Google Scholar  2. Conesa A, Madrigal P, Tarazona S, Gomez-Cabrero D, Cervera A, McPherson A,…

Continue Reading GeneTonic: an R/Bioconductor package for streamlining the interpretation of RNA-seq data | BMC Bioinformatics

Crosstalk between Venous Thromboembolism and Periodontal Diseases: A Bioinformatics Analysis

This article was originally published here Dis Markers. 2021 Dec 10;2021:1776567. doi: 10.1155/2021/1776567. eCollection 2021. ABSTRACT BACKGROUND: This current study applied bioinformatics analysis to reveal the crosstalk between venous thromboembolism (VTE) and periodontitis, as well as the potential role of immune-related genes in this context. METHODS: Expression data were downloaded…

Continue Reading Crosstalk between Venous Thromboembolism and Periodontal Diseases: A Bioinformatics Analysis

Adrenal aldosterone-producing adenoma | IJGM

Background Primary hyperaldosteronism (PA) is characterized by spontaneous secretion of excessive aldosterone and inhibition of plasma renin activity.1 The pathogenesis of adrenal aldosterone-producing adenoma (APA) involves the abnormal proliferation of adrenal cortex cells and the excessive secretion of aldosterone, accounting for nearly 30% of PA. Excessive secretion of aldosterone can…

Continue Reading Adrenal aldosterone-producing adenoma | IJGM

Establishment of sunitinib-resistant CDX model of ccRCC

Introduction Renal cell carcinoma (RCC) accounts for approximately 2–3% of all malignant tumors, and its prevalence is rising. Metastatic RCC accounts for 25–30% of all RCC cases, and has an exceedingly poor prognosis.1 In 2020, among approximately 430,000 newly discovered cases of RCC, 179,000 died.2 Clear cell renal cell carcinoma…

Continue Reading Establishment of sunitinib-resistant CDX model of ccRCC

[Analysis of the Differential Expression of circRNA in Acute Myeloid Leukemia by GEO Database]

Objective: To investigate the difference expression of circular RNA (circRNA) in acute myeloid leukemia (AML) by using bioinformatics method. Methods: The microarray chip data of AML was searched and downloaded from the Gene Expression Omnibus (GEO) of the National Center for Bioinformatics (NCBI). The differences between AML samples and control…

Continue Reading [Analysis of the Differential Expression of circRNA in Acute Myeloid Leukemia by GEO Database]

Bioinformatics Librarian job with University of Pennsylvania

Bioinformatics Librarian University Overview The University of Pennsylvania, the largest private employer in Philadelphia, is a world-renowned leader in education, research, and innovation. This historic, Ivy League school consistently ranks among the top 10 universities in the annual U.S. News & World Report survey. Penn has 12 highly-regarded schools that…

Continue Reading Bioinformatics Librarian job with University of Pennsylvania

Prognosis Biomarkers via WGCNA in HCC

Introduction According to the cancer statistics reported in 2020, hepatocellular carcinoma (HCC) is the main type of Primary Carcinoma of the Liver and the second leading causes of cancer-related death globally, with a five-year survival rate < 20%.1 Currently, surgical resection, a standard therapy for HCC, contributes to the prognosis…

Continue Reading Prognosis Biomarkers via WGCNA in HCC

Identification of Hub Genes in Patients with Alzheimer Disease and Obs

Introduction Alzheimer’s disease (AD) ranks first among the common dementia type of the world. According to epidemiological investigation from the International Alzheimer’s disease association, about 45 million people has been suffered from AD, and the number is expected to increase to 131 million in 2050.1 Despite the widespread prevalence of…

Continue Reading Identification of Hub Genes in Patients with Alzheimer Disease and Obs

Methods to virtually Knockout a gene from a network

Methods to virtually Knockout a gene from a network 0 Hello Everyone! I am wondering if there is any valid method that could be used to virtually knock out a gene from a gene-gene network and study its effect in the whole network? I am aware of this: apps.cytoscape.org/apps/interference Some…

Continue Reading Methods to virtually Knockout a gene from a network

ModuLand gives non-readable names to nodes

ModuLand gives non-readable names to nodes 0 Hello! Can you please help me with the following? I run ModuLand on the STRING-generated network. As a result I obtain small network, as expected, but the node names are STRING identifiers (like “9606.ENSP00000234798”), not readable gene names. Is there easy way to…

Continue Reading ModuLand gives non-readable names to nodes

Parallel genomic responses to historical climate change and high elevation in East Asian songbirds

Extreme environments present profound physiological stress. The adaptation of closely related species to these environments is likely to invoke congruent genetic responses resulting in similar physiological and/or morphological adaptations, a process termed “parallel evolution” (1). Existing evidence shows that parallel evolution is more common at the phenotypic level than at…

Continue Reading Parallel genomic responses to historical climate change and high elevation in East Asian songbirds

Divergence of Root Microbiota in Different Habitats based on Weighted Correlation Networks

Network analysis was applied to evaluate the association of various ecological microbial communities, such as soil, water and rhizosphere. Presented here is a protocol on how to use the WGCNA algorithm to analyze different co-occurrence networks that may occur in the microbial communities due to different ecological environments. This method…

Continue Reading Divergence of Root Microbiota in Different Habitats based on Weighted Correlation Networks

Identification of circRNA-miRNA-mRNA Regulatory Network and Autophagy Interaction Network in Atrial Fibrillation Based on Bioinformatics Analysis

Background: Circular RNA (circRNA) has been receiving increased attention in the research of atrial fibrillation (AF). Our study aims to find potential circRNAs and identify the circRNA-miRNA-mRNA regulatory network in AF based on bioinformatics analysis. Methods: GSE129409 was retrieved from the Gene Expression Omnibus (GEO) database, and we used R…

Continue Reading Identification of circRNA-miRNA-mRNA Regulatory Network and Autophagy Interaction Network in Atrial Fibrillation Based on Bioinformatics Analysis

correlation coefficient for node degree distribution

correlation coefficient for node degree distribution 0 Hi, I am trying to calculate correlation coefficient for node degree distribution in Cytoscape v3.8.2. For the obtained node table for my network, I have used “degree” column as x axis for fitting a power-law. However, I don’t understand from node table, which…

Continue Reading correlation coefficient for node degree distribution

Potenial biomarker in Crohn’s diease via bioinformatics

Introduction Crohn’s disease (CD) and ulcerative colitis are chronic inflammatory disorders of the gastrointestinal tract, with symptoms evolving in a relapsing and remitting manner that comprise the term inflammatory bowel disease (IBD).1 CD is characterized by the involvement of all parts of the intestine, the most common being the terminal…

Continue Reading Potenial biomarker in Crohn’s diease via bioinformatics

BINGO Cytoscape

BINGO Cytoscape 0 How do you interpret GO enrichment results from BINGO plugin in Cytoscape? There are many repetitive GO terms and simple terms e.g. Biological Process. Is there a way to reduce these repetitive terms? I am new to BINGO and GO analysis so any guidance will be really…

Continue Reading BINGO Cytoscape

The Construction and Comprehensive Analysis of a ceRNA Immunoregulator

1Department of Cardiology, Xiangtan Central Hospital, Xiangtan, Hunan, People’s Republic of China; 2Department of Cardiology, Guangxi Cardiovascular Institute, The First Affiliated Hospital of Guangxi Medical University, Guangxi, People’s Republic of China; 3Department of Critical Care Medicine, Zhuzhou Central Hospital, Zhuzhou, Hunan, People’s Republic of China Correspondence: Yiqian ZengDepartment of Critical…

Continue Reading The Construction and Comprehensive Analysis of a ceRNA Immunoregulator

Comprehensive analysis of ceRNA networks to determine genes related to prognosis, overall survival, and immune infiltration in clear cell renal carcinoma

Comput Biol Med. 2021 Nov 20:105043. doi: 10.1016/j.compbiomed.2021.105043. Online ahead of print. ABSTRACT BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is one of the common subtypes of kidney cancer. Circular RNAs (circRNAs) act as competing endogenous RNAs (ceRNAs) to affect the expression of microRNAs (miRNAs), and hence the expression of…

Continue Reading Comprehensive analysis of ceRNA networks to determine genes related to prognosis, overall survival, and immune infiltration in clear cell renal carcinoma

Construction of a circRNA-miRNA-mRNA Regulated Pathway Involved in EGFR-TKI Lung Adenocarcinoma Resistance

1 Introduction Lung cancer is the leading cause of cancer-related deaths worldwide, with adenocarcinoma as the most common histological subtype.1 In recent years, epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs), such as gefitinib (first generation) and osimertinib (third generation), have been widely used for lung adenocarcinoma patients harboring activated EGFR…

Continue Reading Construction of a circRNA-miRNA-mRNA Regulated Pathway Involved in EGFR-TKI Lung Adenocarcinoma Resistance

How to read WGCNA edge file output to find the hub genes_ GO ontology

How to read WGCNA edge file output to find the hub genes_ GO ontology 0 Dear Seniors and members, I am getting close to finish my analysis soon, but I would like to ask two more questions. Hope you do not mind me. Question 1 I have WGCNA edge file…

Continue Reading How to read WGCNA edge file output to find the hub genes_ GO ontology

Entrez Gene ID

Dear Seniors and all members, Me again!! I hope you do not mind me as a junior in RNAseq and tried to learn and finish my degree. Sorry for another question. I have done WGCNA and was able to identify the module associated with traits and exported data for Gene…

Continue Reading Entrez Gene ID

Bioinformatics analysis pinpoints the pathways involved in intestinal SARS/CoV-2 infection

Severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) is a positive-strand RNA virus, which appears spherical under a transmission electron microscope. Many studies have shown that SARS-CoV-2 infects host cells via the interaction between the viral spike protein and the host receptor, angiotensin-converting enzyme II (ACE2). SARS-CoV-2 can spread through…

Continue Reading Bioinformatics analysis pinpoints the pathways involved in intestinal SARS/CoV-2 infection

WGCNA Analysis Identifies Polycystic Ovary Syndrome-Associated Circula

Introduction Polycystic ovary syndrome (PCOS) is a common endocrine metabolic disorder in women of childbearing age.1 PCOS patients are typically characterized by androgen excess, polycystic ovaries and anovulation, and are often accompanied by insulin resistance and obesity.2 Consequently, patients with this syndrome not only suffer from infertility,3 but also have…

Continue Reading WGCNA Analysis Identifies Polycystic Ovary Syndrome-Associated Circula

Importing Network From Wgcna Into Cytoscape

Importing Network From Wgcna Into Cytoscape 2 I have performed wgcna analysis and have obtained 2 files for importing the network into cytoscape, one edge file and another node (attribute) file. The edge file has the following columns: fromNode toNode weight direction fromAltName toAltName Os.9416.1.S1at Os.11330.1.S2at 0.1920219249 undirected Os02g33110.1 Os03g28260.1…

Continue Reading Importing Network From Wgcna Into Cytoscape

How to make a species co-occurrence network in Cytoscape?

How to make a species co-occurrence network in Cytoscape? 2 I have list of microbes enriched in test and control samples along with their relative abundance. Now, I want to make a species co-occurrence network where positively (R>0.6; P<0.05) and negatively (R<-0.6; P<0.05) co-related microbes are connected with edges of…

Continue Reading How to make a species co-occurrence network in Cytoscape?

Pathways visualization as network

Pathways visualization as network 0 Hi, Using C2 pathways from Msigdb, can I draw a cytoscape type network In this each node would be a pathway and edges represent strength of overlap of genes in that pathway. I am aware that this can be done using enrichment map app in…

Continue Reading Pathways visualization as network

CYTOSCAPE AND BIOMARKERS : bioinformatics

Hello! I am a Biomedicine MSc student and it was asked of me to identify potential biomarkers from a set of down and up regulated genes from CSF fluid for Alzheimers Disease! I already did Gene Ontology and now I’m working on interactomes through Cytoscape… For my biomarkers, I downloaded…

Continue Reading CYTOSCAPE AND BIOMARKERS : bioinformatics

circRNA-miRNA-mRNA regulatory network in atrial fibrillation

Introduction Atrial fibrillation (AF) is the most common type of arrhythmia in clinical practice, with global prevalence continuing to increase primarily with age.1 In China, 6.5 persons out of every thousand suffer from AF, and there are about 3.9 million patients with AF who are over 60 years old, but…

Continue Reading circRNA-miRNA-mRNA regulatory network in atrial fibrillation

CRISPR screens unveil signal hubs for nutrient licensing of T cell immunity

1. Chapman, N. M., Boothby, M. R. & Chi, H. Metabolic coordination of T cell quiescence and activation. Nat. Rev. Immunol. 20, 55–70 (2020). CAS  PubMed  Google Scholar  2. Kim, J. & Guan, K. L. mTOR as a central hub of nutrient signalling and cell growth. Nat. Cell Biol. 21,…

Continue Reading CRISPR screens unveil signal hubs for nutrient licensing of T cell immunity

Genes and Pathways Involved in Postmenopausal Osteoporosis

Introduction Many postmenopausal women suffer from postmenopausal osteoporosis (PMO). A survey of 3247 Italian postmenopausal women found that according to bone mineral density (BMD) diagnostic criteria, the prevalence of osteoporosis was 36.6%.1 PMO patients may suffer from chronic pain and fractures, and as a result their quality of life is…

Continue Reading Genes and Pathways Involved in Postmenopausal Osteoporosis

[Analysis on the expression profile of circRNAs in hypertrophic myocardium mice]

Objective: To explore the differential expression of circRNAs and their potential impact on the pathophysiological process in cardiac hypertrophy. Methods: Six SPF C57BL/6J male mice, aged 8 to 10 weeks, were randomly divided into transverse aortic constriction (TAC) group (n=3) or sham operation(sham) group (n=3) according to random number table…

Continue Reading [Analysis on the expression profile of circRNAs in hypertrophic myocardium mice]

Correlation Network with Cytoscape

Correlation Network with Cytoscape 0 I performed differential expression analysis of two different diseases and I have a list of DE human genes. I also have the logfc and p values .I want to visualise these in Cytoscape (as a correlation network between the 2 diseases). Are the logfc and…

Continue Reading Correlation Network with Cytoscape

DEG visualisation with Cytoscape

DEG visualisation with Cytoscape 0 I performed differential expression analysis and I have a list of DE human genes. I want to visualise these in Cytoscape (showing up and down regulated proteins with different shapes and sizes and size of nodes on base of level of expression) but this requires…

Continue Reading DEG visualisation with Cytoscape

Comparing the whole genelist by GSEA GO BP terms to adjusted pvalue genelist by DAVID GO BP terms

Comparing the whole genelist by GSEA GO BP terms to adjusted pvalue genelist by DAVID GO BP terms 0 Say I have done DESeq2 on my RNA-Seq dataset: experimental vs. control DESeq2 has a column for BH – adjusted Pvalues and I plan to take the genes with less than…

Continue Reading Comparing the whole genelist by GSEA GO BP terms to adjusted pvalue genelist by DAVID GO BP terms

Candidate genes associated with synovial macrophages

Jia Xu,1 Ming-Ying Zhang,2 Wei Jiao,1 Cong-Qi Hu,1 Dan-Bin Wu,2 Jia-Hui Yu,1 Guang-Xing Chen2,3 1First Clinical Medical School, Guangzhou University of Chinese Medicine, Guangzhou, 510405, Guangdong, People’s Republic of China; 2Department of Rheumatology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510405, Guangdong, People’s Republic of China;…

Continue Reading Candidate genes associated with synovial macrophages

Bioconductor – Bioconductor 3.14 Released

Home Bioconductor 3.14 Released October 27, 2021 Bioconductors: We are pleased to announce Bioconductor 3.14, consisting of 2083 software packages, 408 experiment data packages, 904 annotation packages, 29 workflows and 8 books. There are 89 new software packages, 13 new data experiment packages, 10 new annotation packages, 1 new workflow,…

Continue Reading Bioconductor – Bioconductor 3.14 Released

Postdoctoral Researcher (Maastricht University) in Bioinformatics to make FAIR data analysis real

Postdoctoral Researcher in Bioinformatics to make FAIR data analysis real – FHML/NUTRIM/Department of Bioinformatics (BiGCaT) at Maastricht University. Deadline: 9 November 2021 Specifications: Postdoc / Natural sciences; Health / 36—40 hours per week / €2790—€4402 per month For more information and to apply, see Academic Transfer: AT2021.264 The department Bioinformatics…

Continue Reading Postdoctoral Researcher (Maastricht University) in Bioinformatics to make FAIR data analysis real

Postdoctoral Researcher in Bioinformatics to make FAIR data analysis real – FHML/NUTRIM/Department of Bioinformatics

The Department of Bioinformatics-BiGCaT is part of NUTRIM School of Nutrition and Translational Research in Metabolism at the Faculty of Health, Medicine and Life Sciences. It was founded in 2001 by Prof. dr. Chris Evelo aiming at employing bioinformatics approaches in systems biology to integrate experimental data and data with…

Continue Reading Postdoctoral Researcher in Bioinformatics to make FAIR data analysis real – FHML/NUTRIM/Department of Bioinformatics

About Differential gene expression analysis

About Differential gene expression analysis 0 i got a confusion in TF ,miRNA network generation.I determined my common DEG from two different dataset.After i did GRN I found the TF for all of my 4 common DEG but miRNA only found for one common DEG.So what should be the interpretation…

Continue Reading About Differential gene expression analysis

Postdoctoral Researcher in Bioinformatics/Toxicoinformatics, 1.0 fte (4yrs), Maastricht University

Postdoctoral Researcher in Bioinformatics/Toxicoinformatics, 1.0 fte (4yrs) – Faculty of Health, Medicine and Life Sciences/School NUTRIM/Department of Bioinformatics – BiGCaT, in collaboration with TNO-Utrecht Deadline: 19 November 2021 Apply: Academic Transfer AT2021.402 Safety assessment without laboratory animals requires a computational infrastructure. Maastricht University is looking for a postdoc to contribute…

Continue Reading Postdoctoral Researcher in Bioinformatics/Toxicoinformatics, 1.0 fte (4yrs), Maastricht University

Identification of Significant Genes in Lung Cancer of Nonsmoking Women via Bioinformatics Analysis

This article was originally published here Biomed Res Int. 2021 Oct 11;2021:5516218. doi: 10.1155/2021/5516218. eCollection 2021. ABSTRACT BACKGROUND: The aim of this study was to identify potential key genes, proteins, and associated interaction networks for the development of lung cancer in nonsmoking women through a bioinformatics approach. METHODS: We used…

Continue Reading Identification of Significant Genes in Lung Cancer of Nonsmoking Women via Bioinformatics Analysis

LncRNA MIAT services as a noninvasive biomarker

Introduction BC is the most common cancer among women that is responsible for the most of the cancer-related death in worldwide.1 The occurrence of BC accounts for 7–8% of the entire number of malignant tumors.2 Accumulating evidence have shown that immunoreaction plays an important role in oncogenesis and progression.3,4 However,…

Continue Reading LncRNA MIAT services as a noninvasive biomarker

Difference between string app and string database results

Difference between string app and string database results 0 Hello guys, I am using Cytoscape and I am importing the string results for the same input query from both string app and string database. But there is a difference between both string app and string database results for the same…

Continue Reading Difference between string app and string database results

Severe trauma and burns accompanied by sepsis

Introduction Trauma accounts for approximately 10% of deaths and 16% of disabilities worldwide.1 Billions of dollars have been spent on research into new biological therapeutics for severe injuries, as well as post-traumatic sepsis and septic shock.2 Burn injuries cause unpredictable trauma and sepsis is a complication associated with high morbidity…

Continue Reading Severe trauma and burns accompanied by sepsis

A TME-Related Signature as a Biomarker in Liver Cancer

Introduction As one of the most frequent causes of cancer deaths across the globe, liver cancer, characterized by high mortality, recurrence, metastasis and poor prognosis, is the only one of the top five deadliest cancers to have an annual percentage increase in occurrence.1 Surgery, local destructive therapies, and liver transplantation…

Continue Reading A TME-Related Signature as a Biomarker in Liver Cancer

how to plot correlation data in R

how to plot correlation data in R 0 Hi, I have got spearman’s correlation and P value like below in two separate files. Could anyone please suggest how I can make an input file after filtering strong, and significant correlation from these two files? I just want to take pVal<.01,abs(correlation)>.4….

Continue Reading how to plot correlation data in R

Identification of antineoplastic agents for oral squamous cell carcinoma: an integrated bioinformatics approach using differential gene expression and network biology

Abstract Oral squamous cell carcinoma (OSCC) is the most common malignant epithelial neoplasm and anatomical subtype of head and neck squamous cell carcinoma (HNSCC) with an average 5-year survival rate of less than 50%. To improve the survival rate of OSCC, the discovery of novel anti-cancer drugs is urgently needed….

Continue Reading Identification of antineoplastic agents for oral squamous cell carcinoma: an integrated bioinformatics approach using differential gene expression and network biology

ANGPTL8/betatrophin improves glucose tolerance | DMSO

Introduction Insulin resistance is a major risk factor for metabolic syndrome (MetS), including type 2 diabetes mellitus (T2DM).1 T2DM is characterized by insulin resistance in the liver.2 Insulin resistance is an abnormal physiological state that occurs when cells are unable to use insulin effectively, leading to T2DM, a major health…

Continue Reading ANGPTL8/betatrophin improves glucose tolerance | DMSO

Importing WGCNA edge and node files into Cytoscape

I’ve used the WGCNA packages (horvath.genetics.ucla.edu/html/CoexpressionNetwork/Rpackages/WGCNA/) to generate edge and node files for use in Cytoscape. cyt = exportNetworkToCytoscape(modTOM, edgeFile = file.path(“./environment”, paste(label, “_CytoscapeInput-edges-“, paste(modules, collapse=”-“), “.txt”, sep=””)), nodeFile = file.path(“./environment”, paste(label, “_CytoscapeInput-nodes-“, paste(modules, collapse=”-“), “.txt”, sep=””)), weighted = TRUE, threshold = 0.02, nodeNames = modProbes, altNodeNames = modGenes, nodeAttr…

Continue Reading Importing WGCNA edge and node files into Cytoscape

SNP-gene network

SNP-gene network 0 Hi everyone, I want to build a network like this using Cystoscope. I didn’t understand how SNPs are integrated into this network. What information do I need for that? All I have right now list of genes containing SNPs and SNP count per gene. Here’s the link…

Continue Reading SNP-gene network

What ever happened to CyAttributesUtils & giny ?

What ever happened to CyAttributesUtils & giny ? 1 Hi all, I’m in charge of porting a plugin from the version 2.x to a Cytoscape 3.x bundle app. It seems that the old version of cytoscape was dependent on giny, so for the new one what package I must use? I…

Continue Reading What ever happened to CyAttributesUtils & giny ?

Networks visualization

Networks visualization 0 Hi. I am new to Cytoscape and would appreciate some help. I am working with 3 networks each of which has the same nodes but different edges. I would like to visualize the networks, so that the nodes are positioned identically in each network, and edge differences…

Continue Reading Networks visualization

Cytochrome P450-2D6: A novel biomarker in liver cancer health disparity

This article was originally published here PLoS One. 2021 Oct 1;16(10):e0257072. doi: 10.1371/journal.pone.0257072. eCollection 2021. ABSTRACT Liver cancer morbidity and mortality rates differ among ethnic groups. In the United States, the burden of liver cancer in Asian Americans (AS) is higher compared to Caucasian Americans (CA). Research on liver cancer…

Continue Reading Cytochrome P450-2D6: A novel biomarker in liver cancer health disparity

Exclude pseudogenes and lncRNA’s from DE-analysis?

Hi all, Let’s start off to thank the ones that helped me lately. I almost feel bad for how many questions I have asked in the last weeks, but the answers were always of great help, so thanks for that! And yet I have another question. As described in my…

Continue Reading Exclude pseudogenes and lncRNA’s from DE-analysis?

Research software engineer supporting open-source bioinformatics software and services (0.6fte) at Department of BioInformatics-BiGCaT

Category Research / Academic Location Maastricht We are looking for a scientific programmer interested in joining our bioinformatics department. Your main responsibility will be to support our broad range of open-source bioinformatics software, workflows, and services. Our bioinformatics research aims to answer complex biological questions that cannot be answered with…

Continue Reading Research software engineer supporting open-source bioinformatics software and services (0.6fte) at Department of BioInformatics-BiGCaT

miRNAs and mRNAs in intestinal ischemia-reperfusion injury

Introduction Intestinal ischemia-reperfusion (II/R) injury is a severe clinical complication common in the Intensive Care Unit (ICU). It is associated with high morbidity and mortality.1 Usually, this problem is followed by various causes, including sepsis, shock, trauma, and so on.2 Intestinal ischemia-reperfusion injury destroys intestinal tissue and impairs the function…

Continue Reading miRNAs and mRNAs in intestinal ischemia-reperfusion injury

Identification of Prognosis-Associated Biomarkers in Thyroid Carcinoma

Introduction Thyroid cancer (TC) is a common endocrine malignancy with a rapidly increasing incidence worldwide, and the estimated new cases and deaths are notably higher in women than in men.1 Papillary thyroid carcinoma (PTC) is identified as the most common pathological type of TC, and accounts for approximately 80–85% of…

Continue Reading Identification of Prognosis-Associated Biomarkers in Thyroid Carcinoma

Classifiers for predicting coronary artery disease

Introduction Coronary artery disease (CAD) is a complex pathology associated with behavioral and environmental factors.1–3 CAD shows high prevalence and is associated with a high fatality rate among cardiovascular diseases. The main manifestations of CAD are stable or unstable angina pectoris and identifiable or unrecognized myocardial infarction.4 The main risk…

Continue Reading Classifiers for predicting coronary artery disease

How to depict edges as an indicator of no. of frames in which two residue interact in Residue interaction network using Cytoscape?

How to depict edges as an indicator of no. of frames in which two residue interact in Residue interaction network using Cytoscape? 1 I am using RIP-MD tool to generate Residue interaction network from MD trajectories. the tool generates GML files which I load in Cytoscape. I want to visualise…

Continue Reading How to depict edges as an indicator of no. of frames in which two residue interact in Residue interaction network using Cytoscape?

How to download data for visualising and analysing in RINalyzer in Cytoscape.

How to download data for visualising and analysing in RINalyzer in Cytoscape. 1 I am new to this plugin in Cytoscape. I want to visualise RIN from pdb and analyze the network. According to the tutorial we can download daat from RIN data websever. But when I am trying to…

Continue Reading How to download data for visualising and analysing in RINalyzer in Cytoscape.

Gene expression profiling of contralateral dorsal root gangl

Introduction Mirror-image pain (MIP) is a mysterious pain phenomenon which is accompanied with many clinical pain conditions.1 MIP develops from the healthy body region which is contralateral to the actual injured site.1–3 MIP is typically characterized by increased mechanical hypersensitivity on the uninjured mirror-image body side.4 It can be triggered…

Continue Reading Gene expression profiling of contralateral dorsal root gangl

How to construct circRNA-miRNA-mRNA network using cytoscape

How to construct circRNA-miRNA-mRNA network using cytoscape 1 Hi, If I have a selected set of circRNAs, miRNAs, mRNAs, then how can I construct an interaction network among them through Cytoscape. Is there any Cytoscape plugin for that and what should be the input file format? Please guide me to…

Continue Reading How to construct circRNA-miRNA-mRNA network using cytoscape

Problem of visualizing results of PPI network

Problem of visualizing results of PPI network 0 Hi,I want to visualize my PPI network into cytoscape or Network analyst .But my ppI node are 661 and edges are 680 and seeds are 15.So i feel problem of visualizing it into cytoscape or Network analyst.Because of huge number of nodes…

Continue Reading Problem of visualizing results of PPI network

Genome-wide synthetic lethal screen unveils novel CAIX-NFS1/xCT axis as a targetable vulnerability in hypoxic solid tumors

Abstract The metabolic mechanisms involved in the survival of tumor cells within the hypoxic niche remain unclear. We carried out a synthetic lethal CRISPR screen to identify survival mechanisms governed by the tumor hypoxia–induced pH regulator carbonic anhydrase IX (CAIX). We identified a redox homeostasis network containing the iron-sulfur cluster…

Continue Reading Genome-wide synthetic lethal screen unveils novel CAIX-NFS1/xCT axis as a targetable vulnerability in hypoxic solid tumors

WGCNA (TRAIT DATA)

WGCNA (TRAIT DATA) 0 I had already obtained a group of significant proteins after performing analysis on data obtained from LC-MS. I would like to perform network analysis on selected proteins using WGCNA package in R. Network analysis using WGCNA:- Removed outlier samples and Genes. Identified softpower (Beta) for singed…

Continue Reading WGCNA (TRAIT DATA)

Strategies to learn about a gene of interest from single-cell RNA-seq data

Strategies to learn about a gene of interest from single-cell RNA-seq data 0 Using a large public single-cell RNA-seq dataset from brain where cells are already segregated by brain region, cell type, marker gene cluster, etc. I am looking to do exploratory analyses to learn whatever I can about a…

Continue Reading Strategies to learn about a gene of interest from single-cell RNA-seq data

How do I start clue GO in R using the cytoscape REST API?

How do I start clue GO in R using the cytoscape REST API? 0 Hi there, I am trying to connect to open the Clue GO application in R using cytoscape REST API. I have the following code: port.number = 1234 host.address <- “localhost” cytoscape.base.url = paste(“http://”,host.address,”:”, toString(port.number), “/v3.11.1″, sep=””)…

Continue Reading How do I start clue GO in R using the cytoscape REST API?

How to merge the edited KEGG pathways in cytoscape

How to merge the edited KEGG pathways in cytoscape 1 I have learnt to import KEGG pathways to cytoscape and merge the pathways without any edits. but I want to differentiate the nodes of each pathways with different colours to understand the pathways of particular gene or molecule. when I…

Continue Reading How to merge the edited KEGG pathways in cytoscape

Bioinformatician — Biological data and network analysis

  EMBL is seeking to recruit a service Bioinformatician/data scientist at EMBL Heidelberg. The position is available in the group of Peer Bork, and will be integrated in the upcoming data science center at EMBL-Heidelberg from 2022 onwards. The successful candidate will be responsible for disseminating expertise, know-how, and guidance…

Continue Reading Bioinformatician — Biological data and network analysis