116 research outputs found
SCHeMa: Scheduling Scientific Containers on a Cluster of Heterogeneous Machines (presentation)
No full textThis is the presentation of the paper "SCHeMa: Scheduling Scientific Containers on a Cluster of Heterogeneous Machines" at the 33rd International Conference on Scientific and Statistical Database Management (SSDBM 2021).
Paper details:
Thanasis Vergoulis, Konstantinos Zagganas, Loukas Kavouras, Martin Reczko, Stelios Sartzetakis, Theodore Dalamagas:
SCHeMa: Scheduling Scientific Containers on a Cluster of Heterogeneous Machines
multispecies dynamic Flux Balance Analysis
No full textAdapt the multispecies dynamic flux balance analysis (msdFBA) algorithm for simulation of the human gut microbiome. Integrate human multi tissue models (Recon, Harvey+Harvetta) into simulation
multispecies dynamic Flux Balance Analysis
No full textAdapt the multispecies dynamic flux balance analysis (msdFBA) algorithm for simulation of the human gut microbiome. Integrate human multi tissue models (Recon, Harvey+Harvetta) into simulation
multispecies dynamic Flux Balance Analysis
No full textAdapt the multispecies dynamic flux balance analysis (msdFBA) algorithm for simulation of the human gut microbiome. Integrate human multi tissue models (Recon, Harvey+Harvetta) into simulation
Prediction of the subcellular localization of eukaryotic proteins using sequence signals and composition
No full textUpdate on ELIXIR CONVERGE, communities, focus groups and Local EGA progesss
No full textBrief update on Greek node participation in ELIXIR Converge, communities, focus groups and implementation studies. Update on progress for Greek local EGA instance
The benefit of cooperation: Identifying growth-efficient interacting strains of Escherichia coli using metabolic flux balance models
No full textBiomass distances from personalized multispecies dynamic flux balance analysis of the human gut microbiome identify dietary influences for patients with and without inflammatory bowel disease
No full textA parallelized version of a multispecies dynamic flux balance analysis (msdFBA) algorithm is implemented and applied to the AGORA collection of genome-scale metabolic reconstructions for 818 members of the human gut microbiome. The msdFBA method assumes the well stirred interaction mode of all organisms to exchange external metabolites. In each msdFBA simulation, the biomasses the gut microbiome composition of one of 149 patients from NIH Human Microbiome Project is used for initialization in combination with one of 11 different diets used as substrates as defined in the Virtual Metabolic Human database. The union of all species in the patient data comprises 255 different microbes. The patients are either healthy or suffer from inflammatory bowel disease (IBD). The msdFBA simulation is performed for 50 time steps. For all combinations of patients and time steps, the euclidean distance between the vector of the biomasses of the 255 patient species and the evolving vector of biomasses for the same species is calculated, providing the information about the biomass distance to each patient during each simulation. To quantify the overall influence of a diet for all patients, a diet score is defined as the sum of the reciprocal distances to the closest patient at the last time step, in case the closest patient is diseased, subtracted from the respective sum for the case that the closest patient is healthy. With this score, the known beneficial influences both of a high fiber and a gluten free diet for IBD is verified. Noteworthy is the utility of a Mediterranean diet in this context, having similar distance patterns. The proposed method provides an universal platform for the in-silico analysis of different environmental influences like diets for different microbiotas defined by metagenomic quantifications from individual patients and has the potential to generate additional dietary recommendations for the management of various other diseases
A Positive Regulatory Loop between a Wnt-Regulated Non-coding RNA and ASCL2 Controls Intestinal Stem Cell Fate
No full textSummaryThe canonical Wnt pathway plays a central role in stem cell maintenance, differentiation, and proliferation in the intestinal epithelium. Constitutive, aberrant activity of the TCF4/β-catenin transcriptional complex is the primary transforming factor in colorectal cancer. We identify a nuclear long non-coding RNA, termed WiNTRLINC1, as a direct target of TCF4/β-catenin in colorectal cancer cells. WiNTRLINC1 positively regulates the expression of its genomic neighbor ASCL2, a transcription factor that controls intestinal stem cell fate. WiNTRLINC1 interacts with TCF4/β-catenin to mediate the juxtaposition of its promoter with the regulatory regions of ASCL2. ASCL2, in turn, regulates WiNTRLINC1 transcriptionally, closing a feedforward regulatory loop that controls stem cell-related gene expression. This regulatory circuitry is highly amplified in colorectal cancer and correlates with increased metastatic potential and decreased patient survival. Our results uncover the interplay between non-coding RNA-mediated regulation and Wnt signaling and point to the diagnostic and therapeutic potential of WiNTRLINC1
Integrated analysis of microRNA and mRNA expression and association with HIF binding reveals the complexity of microRNA expression regulation under hypoxia
No full textBACKGROUND: In mammalians, HIF is a master regulator of hypoxia gene expression through direct binding to DNA, while its role in microRNA expression regulation, critical in the hypoxia response, is not elucidated genome wide. Our aim is to investigate in depth the regulation of microRNA expression by hypoxia in the breast cancer cell line MCF-7, establish the relationship between microRNA expression and HIF binding sites, pri-miRNA transcription and microRNA processing gene expression. METHODS: MCF-7 cells were incubated at 1% Oxygen for 16, 32 and 48 h. SiRNA against HIF-1α and HIF-2α were performed as previously published. MicroRNA and mRNA expression were assessed using microRNA microarrays, small RNA sequencing, gene expression microarrays and Real time PCR. The Kraken pipeline was applied for microRNA-seq analysis along with Bioconductor packages. Microarray data was analysed using Limma (Bioconductor), ChIP-seq data were analysed using Gene Set Enrichment Analysis and multiple testing correction applied in all analyses. RESULTS: Hypoxia time course microRNA sequencing data analysis identified 41 microRNAs significantly up- and 28 down-regulated, including hsa-miR-4521, hsa-miR-145-3p and hsa-miR-222-5p reported in conjunction with hypoxia for the first time. Integration of HIF-1α and HIF-2α ChIP-seq data with expression data showed overall association between binding sites and microRNA up-regulation, with hsa-miR-210-3p and microRNAs of miR-27a/23a/24-2 and miR-30b/30d clusters as predominant examples. Moreover the expression of hsa-miR-27a-3p and hsa-miR-24-3p was found positively associated to a hypoxia gene signature in breast cancer. Gene expression analysis showed no full coordination between pri-miRNA and microRNA expression, pointing towards additional levels of regulation. Several transcripts involved in microRNA processing were found regulated by hypoxia, of which DICER (down-regulated) and AGO4 (up-regulated) were HIF dependent. DICER expression was found inversely correlated to hypoxia in breast cancer. CONCLUSIONS: Integrated analysis of microRNA, mRNA and ChIP-seq data in a model cell line supports the hypothesis that microRNA expression under hypoxia is regulated at transcriptional and post-transcriptional level, with the presence of HIF binding sites at microRNA genomic loci associated with up-regulation. The identification of hypoxia and HIF regulated microRNAs relevant for breast cancer is important for our understanding of disease development and design of therapeutic interventions
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