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Projects: ZucAt, Modelling COVID-19 epidemics
Institutions: Institute of Cytology and Genetics, Novosibirsk State University
Expertise: Systems Biology, molecular genetic systems, gene networks, gene expression, Modeling
Tools: Java, Vaadin, Kinetic Modeling
I am staff scientist in the lab of molecular-genetic systems at the Department of Systems Biology, Institute of Cytology and Genetics SB RAS and Postdoc Research Fellow at San Diego State University. My research focus is dynamical modeling of gene network functioining.
Projects: WineSys, INBioPharm, BioZEment 2.0, CoolWine, Auromega
Institutions: Norwegian University of Science and Technology

Expertise: Systems Biology
Tools: network theory
Projects: EmPowerPutida
Institutions: University of Stuttgart
Projects: EmPowerPutida
Institutions: Wageningen University & Research
Expertise: Synthetic Biology
Expertise: Bioinformatics, Computational Systems Biology, Data Management, Databases, Python, R, Transcriptomics, Image analysis, Genomics, Molecular Biology, Microbiology, Data analysis, Genetics
Tools: qPCR, Isolation purification and separation, Genomics, Data Science, RNA / DNA Techniques, Transcriptomics, Microbiology, Molecular Biology, Databases
I am a biochemist & bio-informatician working in phytobacteriology at the Plant Sciences Unit of ILVO, the Flanders Research Institute for Agricultural, Fisheries and Food Research. The focus is on genomics-based research and diagnostics for Plant Health.
My expertise is 'wet-lab' work (microbiology, sequencing, molecular biology, design & validation of diagnostics assays using qPCR/LAMP, automatisation) and 'dry-lab' work such as bio-informatics/data analysis (e.g. scripting analysis ...
Projects: EmPowerPutida
Institutions: ETH Zurich
Projects: SilicoTryp, Multiscale modelling of state transitions in the host-microbiome-brain network, MESI-STRAT, PoLiMeR - Polymers in the Liver: Metabolism and Regulation
Institutions: University of Groningen

I am a Professor in Medical Systems Biology and the University Medical Centre Groningen. The research in my lab is focused on complex regulation of mammalian lipid and carbohydrate metabolism, eventually aiming at network-based therapies. We combine dynamic computer simulations with quantitative metabolomics, 13C fluxomics, proteomics and transcriptome analysis, and in depth biochemical analysis. This allows to predict and understand ‘emergent’ properties, those properties that are counterintuitive ...
Projects: EmPowerPutida
Institutions: Wageningen University & Research
Projects: EmPowerPutida
Institutions: LifeGlimmer GmbH
Projects: testproject
Institutions: University Medical Center Göttingen, Department of Medical Informatics
Projects: SCaRAB, STREAM, SYSTERACT, INBioPharm
Institutions: SINTEF, Norwegian University of Science and Technology
Expertise: Bioinformatics, Microarray analysis, Data analysis, Pseudomonas, Streptomyces, Stoichiometric modelling, Prokaryotic genetics, Analytical chemistry
Tools: Transcriptomics, Perl, Fermentation, GC and LC analysis of metabolites, Pathway Tools, MS imaging, Mass spectrometry (LC-MS/MS), Mass spectrometry, FT-ICR-MS, Field Flow Fractionation
Senior Research Scientist at SINTEF, Dept. of Biotechnology and Nanomedicine, Research Group Mass Spectrometry
Projects: middle ear
Institutions: Technische Universität Dresden

Projects: STREAM, SCaRAB, WineSys, INBioPharm
Institutions: SINTEF, Norwegian University of Science and Technology
Expertise: Metabolomics
Cell biological and proteogenomic study of the chloroplast of the marine, bloom-forming dinoflagellate P. cordatum
Programme: Independent Projects
Public web page: Not specified
Organisms: Not specified
Test data amaizing
Programme: Independent Projects
Public web page: Not specified
Organisms: Not specified
Programme: Independent Projects
Public web page: Not specified
Programme: Independent Projects
Public web page: Not specified
Organisms: Not specified
Programme: Independent Projects
Public web page: Not specified
Organisms: Not specified
Programme: Independent Projects
Public web page: Not specified
Organisms: Not specified
LIMAQUA results in an innovative process for converting and recirculating aquaculture side-streams (sludge and wastewater) in algae (Galdieria sulphuraria)-based feed production for aquacultures. In conventional aquaculture, feed production is responsible for 50% of greenhouse gas (GHG) emission. The aim is to substantially reduce GHG emission by considering geographic and site-specific characteristics (temperature, sunshine duration etc.) and to design site-specific phototrophic or heterotrophic ...
Programme: Independent Projects
Public web page: https://www.foscera.net/en/foscera/projects/climaqua.htm
Organisms: Not specified
Programme: Independent Projects
Public web page: Not specified
Organisms: Not specified
Project Overview
Databases of biomedical knowledge are rapidly proliferating and growing, with recent advances (such as the RTX-KG2 knowledge-base that we have recently developed; (Wood et al. 2022)) increasingly focusing on integration of knowledge under a standardized schema and semantic layer (i.e., controlled vocabularies for types of concepts and types of relationships, for example, the Biolink standard (Unni et al. 2022)). The rise of standardized knowledge-bases sets the stage for the ...
Programme: Independent Projects
Public web page: https://github.com/RTXteam/RTX
Start date: 1st Jan 2020
End date: 28th Nov 2023
Organisms: Homo sapiens
MESI-STRAT Review
Programme: Independent Projects
Public web page: Not specified
Organisms: Not specified
Programme: Independent Projects
Public web page: Not specified
Organisms: Not specified
Endometriosis research done by the Griffith lab (MIT) and the Goods lab (Dartmouth)
Programme: Independent Projects
Public web page: Not specified
Organisms: Not specified
Programme: Independent Projects
Public web page: Not specified
Organisms: Not specified
Trabajo de Fin de Master
Programme: Independent Projects
Public web page: Not specified
Organisms: Not specified
Programme: Independent Projects
Public web page: Not specified
Organisms: Not specified
Programme: Independent Projects
Public web page: Not specified
Organisms: Not specified
supplementary materials
Programme: Independent Projects
Public web page: Not specified
Organisms: Not specified
Developing a placenta on a chip
Programme: Independent Projects
Public web page: https://www.iplacenta.eu/
Start date: 1st Jan 2018
End date: 31st May 2022
Organisms: Homo sapiens
Programme: Independent Projects
Public web page: Not specified
Organisms: Not specified
This work aims to identify the biochemical pathways of THP-1 human monocytes infected by different Leishmania infantum clinical isolates from patients with either resistance or with TF outcome, using whole cell differential Mass Spectrometry proteomics. Network enrichment analysis was adopted to integrate the transcriptomics and the proteomic results of infected cells studies. Transferrin Receptor C and Nucleoside Diphosphate Kinase 3 were discovered as overexpressed proteins in THP-1 cells ...
Programme: Independent Projects
Public web page: Not specified
Organisms: Not specified
Snapshots: No snapshots
This investigation serves as supplementary material for a SWAT4HCLS publication that describes minimum metadata and provenance requirements for reproducible enrichment analysis results.
Functional enrichment analysis is an essential downstream process in high throughput omics studies, such as transcriptomics and proteomics. By using the Gene Ontology (GO) and its annotations (GOA), underlying functional patterns of over-representation can be identified, leading to ...
Snapshots: No snapshots
Aims: The immune response is important for mediating the benefit of cardiac cell therapies. The role of varied immune responses in influencing the outcome of cardiomyocyte cell transplantation after myocardial infarction was investigated. Methods and Results: Cardiac flow cytometric analysis of C57BL/6J and T- and B cell deficient Rag2del mice revealed varied CD11b, natural killer and dendritic cell responses following sham injection and a disparate macrophage response after myocardial infarction. ...
Submitter: Markus Wolfien
Studies: Single nuclei data analysis
Snapshots: No snapshots
Members of the genus Aromatoleum are cosmopolitan in diverse habitats and utilize a broad range of recalcitrant organic molecules coupled to denitrification or O2-respiration. To gain a holistic understanding of the model organism A. aromaticum EbN1T, we here studied its catabolic network dynamics in response to 3-(4-hydroxyphenyl)propanoate, phenylalanine, 3-hydroxybenzoate, benzoate and acetate utilized under nitrate-reducing vs. oxic conditions. Multi-OMICS (transcriptome, proteome and metabolome) ...
Submitter: Meina Neumann-Schaal
Studies: Experimental multi-OMICS, Genome re-annotation, Metabolic Modelling
Assays: CoA LC/MS Data, Cultivation for multi-OMICS, EbN1 Genome re-annotation, Metabolic modeling of EbN1, Proteomic data, Scenario files for Metano metabolic modeling, Transcriptomic data, non-volatile metabolites GC/MS
Snapshots: Snapshot 1
Snapshots: No snapshots
- To develop a whole-cell dynamic model framework of the metabolism of M. pneumoniae
- To build upon M. pneumoniae models to develop a genome-scale, constraint-based model of M. hyopneumoniae for vaccine optimization
- To deploy the metabolic model(s) to: 1) the rational design and optimization of the vaccine chassis; 2) aid the development of a higher-growth rate chassis; 3) assist the development of a nutrient optimized a serum-free growth medium and; 4) assess, at genome scale, the metabolic ...
Submitter: Niels Zondervan
Studies: Core Model predictions, Core Model training, Core model predicting combined mutations and perturbations, Genome-scale, constraint-based metabolic modeling of M. hyopneumonia, Metabolomics measurements, Proteomics analysis, Transcriptomics of M. pneumoniae at different times of growth
Assays: 40 samples data analysis - metabolite correlation, 40 samples, OE mutants of glycolysis and pyruvate metabolism enzymes com..., All samples data, Comparison of Kcat values from the model and values from literature, Construction and training of the core model, Construction of a Genome Scale Metabolitic model of M. hyopneumoniae, Dynamic model simmulation pipeline, Metabolic control analysis (local and global), Metabolomics external metabolites measurements, Metabolomics internal metabolites, time series measurements, Proteomics assay, Transcriptomics assay of M. pneumoniae at diferent times of growth, Validation by simulating independent mutant and perturbation samples
Snapshots: Snapshot 1, Snapshot 2, Snapshot 3
Submitter: Lars Wöhlbrand
Investigation: 1 hidden item
Assays: Additional data related to microscopic investigations, Additional data related to proteomic investigations, Cellular and nuclear fractions of P. cordatum analyzed by GeLC iontrap M..., Cellular and nuclear fractions of P. cordatum analyzed by timsTOF MS/MS
Snapshots: No snapshots
This study describes the results of a survey on enrichment analysis tool usage and provenance reporting for a corpus of SARS-CoV2 data.
Submitter: Yi Chen
Investigation: FAIR Functional Enrichment: Assessing and Model...
Assays: FAIR Functional Enrichment
Snapshots: No snapshots
This study contains the singele nuclei data analysis part of the Bl6 and Rag2del comparison. Here, we used Seurat, harmony, and monocle for an in-depth analysis.
Submitter: Markus Wolfien
Investigation: Disparate immune responses lead to varied outco...
Snapshots: No snapshots
Submitter: Meina Neumann-Schaal
Investigation: Systems biology investigation of aromatic compo...
Assays: CoA LC/MS Data, Cultivation for multi-OMICS, Proteomic data, Transcriptomic data, non-volatile metabolites GC/MS
Snapshots: No snapshots
Submitter: Meina Neumann-Schaal
Investigation: Systems biology investigation of aromatic compo...
Assays: EbN1 Genome re-annotation
Snapshots: No snapshots
Submitter: Meina Neumann-Schaal
Investigation: Systems biology investigation of aromatic compo...
Assays: Metabolic modeling of EbN1, Scenario files for Metano metabolic modeling
Snapshots: No snapshots
Single-cell RNA-sequencing (scRNA-seq) provides high-resolution insights into complex tissues. Cardiac tissue, however, poses a major challenge due to the delicate isolation process and the large size of mature cardiomyocytes. Regardless of the experimental technique, captured cells are often impaired and some capture sites may contain multiple or no cells at all. All this refers to “low quality” potentially leading to data misinterpretation. Common standard quality control parameters involve the ...
Submitter: Markus Wolfien
Investigation: 1 hidden item
Assays: scRNA-Seq of in vitro "induced sinoatrial bodies" and ex vivo sinoatrial...
Snapshots: No snapshots
This study contains our snRNA-Seq based comparison of whole hearts from Fzt.DU and Bl6 mice published in Cardiovascular Research.
Submitter: Markus Wolfien
Investigation: 1 hidden item
Assays: Single nuclei RNA-Seq analysis of Fzt:DU and BL6 mice
Snapshots: Snapshot 1
This study includes the single snRNA-seq in whole adult murine hearts from an inbred (C57BL/6NRj) and an outbred (Fzt:DU) mouse strain in comparison to publicly available scRNA-seq data of the tabula muris project.
Submitter: Anne-Marie Galow
Investigation: 1 hidden item
Assays: integrative cluster analysis of single cell and single nuclei data
Snapshots: Snapshot 1
This study contains our single nuclei characterisation of whole hearts from Fzt.DU mice published in Cells.
Submitter: Markus Wolfien
Investigation: 1 hidden item
Snapshots: Snapshot 1
Predictions made using the core model for combinatorial perturbations to the model simulating combined effects from OE, KO mutants, perturbations and time series concentrations.
Submitter: Niels Zondervan
Investigation: Modelling of M. pneumoniae metabolism
Assays: 40 samples, OE mutants of glycolysis and pyruvate metabolism enzymes com...
Snapshots: No snapshots
Internal metabolites concentrations for time series data (not pulse experiments) and for mutant OE, KO mutants and perturbations External metabolite concentrations for time series data (not pulse experiments) and for mutant OE, KO mutants and perturbations Mutant (OE, KO, perturbation) metabolite measurements
Submitter: Niels Zondervan
Investigation: Modelling of M. pneumoniae metabolism
Assays: 40 samples data analysis - metabolite correlation, All samples data, Metabolomics external metabolites measurements, Metabolomics internal metabolites, time series measurements
Snapshots: No snapshots
Training of the core model, parameter estimation using Evolutionary Programming using metabolomics, proteomics and some flux data. The core model contains reactions in glycolysis, pyruvate metabolism and ATPase
Submitter: Niels Zondervan
Investigation: Modelling of M. pneumoniae metabolism
Assays: Comparison of Kcat values from the model and values from literature, Construction and training of the core model
Snapshots: No snapshots
Validation of the core model of glycolysis, pyruvate metabolism and ATPase reaction using OE, KO mutant samples and perturbation samples
Submitter: Niels Zondervan
Investigation: Modelling of M. pneumoniae metabolism
Assays: Dynamic model simmulation pipeline, Metabolic control analysis (local and global), Validation by simulating independent mutant and perturbation samples
Snapshots: No snapshots
This section contains all the raw data and files required for each figures.
Submitter: Dorothee Houry
Investigation: 1 hidden item
Assays: FIGURE 2: Crystal structures of human NAMPT in complex with NA and PRPP,..., FIGURE 3: ATP is essential for NAMN formation by NAMPT, FIGURE 4: ATP indirectly stabilizes PRPP via pHis247., FIGURE 5: The deletion of the β1-β2 loop does not alter the geometry of ..., FIGURE 6: SAXS analysis of WT and Δ42-51 NAMPT.
Snapshots: Snapshot 1
Construction of a Genome scale constrained-based metabolic modeling of M. hyopneumonia
Submitter: Niels Zondervan
Investigation: Modelling of M. pneumoniae metabolism
Assays: Construction of a Genome Scale Metabolitic model of M. hyopneumoniae
Snapshots: No snapshots
Proteomics Average and SD data for time series data, 6h, 12h, 24h, 48h,72, 96h per protein
Submitter: Niels Zondervan
Investigation: Modelling of M. pneumoniae metabolism
Assays: Proteomics assay
Snapshots: No snapshots
Contains copy number per locus tag at different times of Growth between 0.25h and 96 hours. M. pneumoniae was grown in Batch, cells attached to the bottom of the flask (single cell layer), non stirred, non aerated.
Submitter: Niels Zondervan
Investigation: Modelling of M. pneumoniae metabolism
Assays: Transcriptomics assay of M. pneumoniae at diferent times of growth
Snapshots: No snapshots
Submitter: Natalie Stanford
Investigation: Designing a new way to predict engineering stra...
Assays: OptKnock applied to e.coli for butanol production., RobOKoD applied to e.coli for butanol production., RobustKnock applied to e.coli for butanol production.
Snapshots: No snapshots
RobOKoD algorithm was, designed then implemented as part of a study in RobOKoD: microbial strain design for (over)production of target compounds. (http://fairdomhub.org/publications/236). It was used to generate a strain of e.coli for producing butanol, that was then compared to an experimental strain. It was shown to perform better than similar methods (OptKnock, and RobustKnock).
Submitter: Natalie Stanford
Biological problem addressed: Model Analysis Type
Investigation: Designing a new way to predict engineering stra...
Organisms: No organisms
Models: iNS142 RobOKoD Redesigned Butanol Producing.
SOPs: RobOKoD SOP for Redesigning Butanol Producing S...
Data files: FBA result of RobOKoD designed e.coli strain.
Snapshots: No snapshots
OptKnock algorithm was used as part of a study in RobOKoD: microbial strain design for (over)production of target compounds. (http://fairdomhub.org/publications/236). It was used to generate a strain of e.coli for producing butanol, that was then compared to an experimental strain.
Submitter: Natalie Stanford
Biological problem addressed: Model Analysis Type
Investigation: Designing a new way to predict engineering stra...
Organisms: No organisms
Models: No Models
SOPs: OptKnock SOP for Redesigning Butanol Producing ...
Data files: No Data files
Snapshots: No snapshots
RobustKnock algorithm was used as part of a study in RobOKoD: microbial strain design for (over)production of target compounds. (http://fairdomhub.org/publications/236). It was used to generate a strain of e.coli for producing butanol, that was then compared to an experimental strain.
Submitter: Natalie Stanford
Biological problem addressed: Model Analysis Type
Investigation: Designing a new way to predict engineering stra...
Organisms: No organisms
Models: No Models
SOPs: RobustKnock SOP for Redesigning Butanol Produci...
Data files: No Data files
Snapshots: No snapshots
Training of the model, parameter estimation using Evolutionary Programming using metabolomics, proteomics and some flux data.
Submitter: Niels Zondervan
Biological problem addressed: Model Analysis Type
Investigation: Modelling of M. pneumoniae metabolism
Study: Core Model training
Organisms: No organisms
Models: Core model of glycolysis, pyruvate metabolism A..., Dynamic model of glycolysis, pyruvate metabolis...
SOPs: No SOPs
Data files: Master file, metabolite concentration, protein ..., Model training, parameter estimation, Parameter estmimation for model with addition o..., Parameter scan for the model with addition of o...
Snapshots: No snapshots
Validation by simulating independent OE, KO mutant and perturbation samples, using sampling of the gausian distribution based on the mean and SD of measurements per sample. A 1000 samples of the gausian distribution of the mean and SD was performed per sample to show error in the measurements and how it propegates in predicted metabolite concentration in SS
Submitter: Niels Zondervan
Biological problem addressed: Model Analysis Type
Investigation: Modelling of M. pneumoniae metabolism
Study: Core Model predictions
Organisms: No organisms
Models: Dynamic model of glycolysis, pyruvate metabolis...
SOPs: No SOPs
Data files: 40 samples internal metabolite concentrations F..., Comparison of model SS metabolite concentration..., Dynamic modelling pipeline, Internal metabolite concentraitons for mutants,..., Symmetric mean absolute percentage error per sa...
Snapshots: No snapshots
Comparison of Kcat values from the model and values from literature.
Submitter: Niels Zondervan
Assay type: Enzymatic Assay
Technology type: Technology Type
Investigation: Modelling of M. pneumoniae metabolism
Study: Core Model training
Organisms: No organisms
SOPs: No SOPs
Data files: Comparison of Kcat values model and values from...
Snapshots: No snapshots
Protein copy number at 6h, 12h, 24h, 48h, 72h, 96h, average values and SD for the measurements
Submitter: Niels Zondervan
Assay type: Proteomics
Technology type: Technology Type
Investigation: Modelling of M. pneumoniae metabolism
Study: Proteomics analysis
Organisms: No organisms
SOPs: No SOPs
Data files: Master file, metabolite concentration, protein ..., Proteomics, protein copy number measured over time
Snapshots: No snapshots
Metabolomics time series measurements for internal metabolites for 6h, 24h and 48h for multiple experiments. Largely based on MAss spectrometry, bioluminescence kits to measure NAD, NADH at 24h, other time points are infered from relative measurements times the absolute measurements at 24h.
Submitter: Niels Zondervan
Assay type: Experimental Assay Type
Technology type: Mass Spectrometry
Investigation: Modelling of M. pneumoniae metabolism
Study: Metabolomics measurements
Organisms: No organisms
SOPs: Metabolomics perturbation samples preparation
Data files: 40 samples internal metabolite concentrations F..., All_samples_mean_meatbolite_concentration&enzym..., Internal metabolite concentraitons for mutants,..., Internal metabolite concentrations time series, Master file, metabolite concentration, protein ..., Metabolites all experiments, relative measurements
Snapshots: No snapshots
Simulation of OE mutants targetting enzymes in the model, combined with metabolite concentrations and enzyme fold change of from the 40 samples. For each second mutant the enzyme concentrations in case of OE and KO mutants in updated and the metabolite concentrations of the second sample are loaded in the model. Using this approach the model approximately predicts combinatorial effects of OE mutations with other mutations, perturbations and time series concentrations.
Submitter: Niels Zondervan
Biological problem addressed: Model Analysis Type
Investigation: Modelling of M. pneumoniae metabolism
Organisms: No organisms
Models: Dynamic model of glycolysis, pyruvate metabolis...
SOPs: No SOPs
Data files: Double mutants and perturbations, Dynamic modelling pipeline
Snapshots: No snapshots
Measurements of external metabolites based on growth curve data. Flux estimates for uptake of external metabolites such as glucose and production rates for external metabolites lactate and acetate
Submitter: Niels Zondervan
Assay type: Experimental Assay Type
Technology type: Technology Type
Investigation: Modelling of M. pneumoniae metabolism
Study: Metabolomics measurements
Organisms: No organisms
SOPs: No SOPs
Data files: External metabolite concentration times series, Master file, metabolite concentration, protein ...
Snapshots: No snapshots
Construction and manual curated Genome Scale Metabolitic model of M. hyopneumoniae. Dynamic flux balance analysis was performed for glucose uptake
Submitter: Niels Zondervan
Biological problem addressed: Model Analysis Type
Investigation: Modelling of M. pneumoniae metabolism
Organisms: No organisms
Models: Genome Scale Metabolic model of M. hyopneumoniae
SOPs: SOP for generating a Genome Scale Metabolic mod...
Data files: No Data files
Snapshots: No snapshots
Submitter: Niels Zondervan
Assay type: Transcriptional Profiling
Technology type: Technology Type
Investigation: Modelling of M. pneumoniae metabolism
Organisms: No organisms
SOPs: No SOPs
Data files: Absolute copy number per locus tag, M. pneumoni...
Snapshots: No snapshots
Contains the analysis of the internal metabolite concentrations of the 40 independend samples Pearson correlation was used to generate heatmaps Pearson correlation with p-value cutof of 0.001 was used and as input for a correlation network (grouping using H-clust) Principal component analysis was performed on samples, F-ion and H-ion data combined and seperately Zip files contains the data (FC.txt), PCA and heatmap plots and the script to re-generate these plots
Submitter: Niels Zondervan
Biological problem addressed: Model Analysis Type
Investigation: Modelling of M. pneumoniae metabolism
Study: Metabolomics measurements
Organisms: No organisms
Models: No Models
SOPs: No SOPs
Data files: 40 samples internal metabolite concentrations F..., 40 samples metabolite correlation analysis - he...
Snapshots: No snapshots
Metabolic control analysis: Local control coefficients for 40 independent samples based on 100x sampling from the measurement distribution Global control analysis based on 100.000 Latin Hypercube sampling from the parameter search range (0.01-100 for Km values and 0.001-1000 for Vmax values)
Submitter: Niels Zondervan
Biological problem addressed: Model Analysis Type
Investigation: Modelling of M. pneumoniae metabolism
Study: Core Model predictions
Organisms: No organisms
Models: Dynamic model of glycolysis, pyruvate metabolis...
SOPs: No SOPs
Data files: Dynamic modelling pipeline, Global sensitivity analysis, Global sensitivity analysis - correlation betwe..., Global sensitivity analysis - tab seperated file, Local sensitivity analysis based on 40 samples, Local sensitivity analysis based on 40 samples ... and 1 hidden item
Snapshots: No snapshots
The associated zip files contains all input files and a Jupyter notebook to rerun sampled simmulations, combined simmulations, parameter scan for the model with addition of an oxygin inhibiton of LDH, local- and global-sensitivity analysis and plot simmulation output in various formats. In addition the zip file contains the py36.yaml file that can be used to recreate the model simmulation environment using Anaconda making all simmulations completely reproducable. All information on how to use ...
Submitter: Niels Zondervan
Biological problem addressed: Model Analysis Type
Investigation: Modelling of M. pneumoniae metabolism
Study: Core Model predictions
Organisms: No organisms
Models: Dynamic model of glycolysis, pyruvate metabolis...
SOPs: No SOPs
Data files: Dynamic modelling pipeline
Snapshots: No snapshots
Submitter: Dorothee Houry
Assay type: Experimental Assay Type
Technology type: Technology Type
Investigation: 1 hidden item
Organisms: No organisms
SOPs: No SOPs
Data files: No Data files
Snapshots: No snapshots
Submitter: Dorothee Houry
Assay type: Experimental Assay Type
Technology type: Technology Type
Investigation: 1 hidden item
Organisms: No organisms
SOPs: No SOPs
Data files: Fig3: NAMN formation w/ and w/o ATP in WT NAMPT
Snapshots: No snapshots
Submitter: Dorothee Houry
Assay type: Experimental Assay Type
Technology type: Technology Type
Investigation: 1 hidden item
Organisms: No organisms
SOPs: No SOPs
Data files: NMN and NAMN formation w/ and w/o ATP in Δ42-51...
Snapshots: No snapshots
Submitter: Dorothee Houry
Assay type: Experimental Assay Type
Technology type: Technology Type
Investigation: 1 hidden item
Organisms: No organisms
SOPs: No SOPs
Data files: SAXS raw data of WT and Δ42-51 NAMPT w/ Nam, NA...
Snapshots: No snapshots
Submitter: Dorothee Houry
Assay type: Experimental Assay Type
Technology type: Technology Type
Investigation: 1 hidden item
Organisms: No organisms
SOPs: No SOPs
Data files: No Data files
Snapshots: No snapshots
Content:
- Compiled 15 columns annotation of P. cordatum (Dougan et al. 2022)
- Summary of predicted unknown proteins of P. cordatum
- Calculations of predicted unknown proteins of P. cordatum
Tab color: annotation, purple; unknowns, green
Creators: None
Submitter: Jana Kalvelage
Investigations: 1 hidden item
- Calculations of predictions of all identified proteins of P. cordatum
- Calculations of fold-changes of all identified proteins (cell vs. nuclei fraction) of P. cordatum
- Calculations of predictions of proteins of unknown function of_ P. cordatum_
- Calculations of fold-changes of unknowns (cell vs. nuclei fraction) of P. cordatum
Tab color: all identified proteins, purple; unkowns, green
Creators: None
Submitter: Jana Kalvelage
Investigations: 1 hidden item
Content:
- Nuclear protein fractions: NSP, NMP and NTP R1-R3 (Peptide counts)
- Summary nuclear proteins geLC
- Cellular protein fractions: CSP, CMP R1-R3 (Peptide counts)
- Summary cellular proteins geLC
- Summary nuclear protein fractions NSP R1-R3 (iBAQs)
- Summary cellular protein fractions CSP R1-R3 (iBAQs)
- 15 columns annotation
- Final summary of protein data
- Prediction results
- Annotation (biological processes and categories)
Tab color: raw data, green; summarized data, orange; final ...
Creators: None
Submitter: Jana Kalvelage
Investigations: 1 hidden item
- Summary of functional categorization of all identified proteins of P. cordatum
- Calculations of general functions (Fig. 5, left panel)
- Calculations of nuclear functions (Fig. 5, right panel)
- Categories in separate sheets
Tab color: Summarized data, purple; calculations, organge; functional categories, green
Creators: None
Submitter: Jana Kalvelage
Investigations: 1 hidden item
- Summary of nuclear proteins
- Separate sheets of nuclear processes (MBNP_Histones, DNA replication, DNA repair, RNA processing (rRNA and mRNA processing), transcription, import and export, ubiquitylation, proteasome, biogenesis ribosomes)
- Ribosomes (category translation)
Tab color: Summary, purple; nuclear processes, green; ribosomes, orange
Creators: None
Submitter: Jana Kalvelage
Investigations: 1 hidden item
Creators: None
Submitter: Lars Wöhlbrand
Investigations: 1 hidden item
Prepared (sub-)cellular fractions were separated by gradient SDS-PAGE and entire sample lanes cut into pieces prior to in-gel digest and nanoLC separation coulpled to iontrap MS/MS detection.
Creators: None
Submitter: Lars Wöhlbrand
Investigations: 1 hidden item
Supplementary movie of the distribution of nuclear pores in the nuclear envelope of P. cordatum
Creators: None
Submitter: Jana Kalvelage
Investigations: 1 hidden item
Movie of the chromosomal packing in the nucleus of P. cordatum MPEG format (mp4)
Creators: None
Submitter: Jana Kalvelage
Investigations: 1 hidden item
- Amira raw data of nuclear structures of P. cordatum
- Volume calculations of nuclear structures of_ P. cordatum _
Creators: None
Submitter: Jana Kalvelage
Investigations: 1 hidden item
- raw data tif-file, stacked image for 3D reconstruction of the nucleus of P. cordatum
Creators: None
Submitter: Jana Kalvelage
Investigations: 1 hidden item
This file provides a full list of the PubMed IDs used as input to our survey of SARS-CoV2 enrichment analysis results
Creators: None
Submitter: Yi Chen
Investigations: FAIR Functional Enrichment: Assessing and Model...
Studies: FAIR Functional Enrichment
Assays: FAIR Functional Enrichment
A list of the search terms used for identifying SARS-CoV2 studies involving enrichment analysis. A random sample of 100 papers were used as input to the experiment.
Creators: None
Submitter: Yi Chen
Investigations: FAIR Functional Enrichment: Assessing and Model...
Studies: FAIR Functional Enrichment
Assays: FAIR Functional Enrichment
Creator: Lorenzo Tagliazucchi
Submitter: Lorenzo Tagliazucchi
Investigations: No Investigations
Studies: No Studies
Assays: No Assays
Creator: Lorenzo Tagliazucchi
Submitter: Lorenzo Tagliazucchi
Investigations: No Investigations
Studies: No Studies
Assays: No Assays
Creator: Lorenzo Tagliazucchi
Submitter: Lorenzo Tagliazucchi
Investigations: No Investigations
Studies: No Studies
Assays: No Assays
Summary of identified ribosomal proteins of P. cordatum.
Creators: None
Submitter: Jana Kalvelage
Investigations: 1 hidden item
Summary table of identified pigment binding proteins with relative shares in % and calculations of total amount of pigment binding proteins in the different data sets.
Creators: None
Submitter: Jana Kalvelage
Investigations: 1 hidden item
Creators: None
Submitter: Lorenzo Tagliazucchi
Investigations: No Investigations
Studies: No Studies
Assays: No Assays
Creators: None
Submitter: Lorenzo Tagliazucchi
Investigations: No Investigations
Studies: No Studies
Assays: No Assays
Underlying R script for the investigation of immune cells. Script contains basic data processing, as well as a DE and monocle analysis.
Creator: Markus Wolfien
Submitter: Markus Wolfien
Model type: Not specified
Model format: Not specified
Environment: Not specified
Organism: Mus musculus
Investigations: Disparate immune responses lead to varied outco...
Studies: Single nuclei data analysis
Stoichiometric model in SBML format using the acetate-aerobic standard scenario.
Please note that SBML was exported using the sbmlwriter class of Metano. This file was not used for the actual analyses.
Creator: Julia Koblitz
Submitter: Julia Koblitz
Model type: Stoichiometric model
Model format: SBML
Environment: Not specified
Organism: Aromatoleum aromaticum
Investigations: Systems biology investigation of aromatic compo...
Studies: Metabolic Modelling
Assays: Metabolic modeling of EbN1
This stoichiometric model of Aromatoleum aromaticum EbN1 is a genome-scale model and comprises 655 enzyme-catalyzed reactions and 731 distinct metabolites.
The model is in the plain-text reaction format of Metano that is human-readable and can be opened with every text editor. To run this version of the model, please use the Metano Modeling Toolbox (mmtb.brenda-enzymes.org) and the associated scenario files.
Creators: Julia Koblitz, Dietmar Schomburg, Meina Neumann-Schaal
Submitter: Julia Koblitz
Model type: Stoichiometric model
Model format: Not specified
Environment: Not specified
Organism: Aromatoleum aromaticum
Investigations: Systems biology investigation of aromatic compo...
Studies: Metabolic Modelling
Assays: Metabolic modeling of EbN1, Scenario files for Metano metabolic modeling
A population of turtles have between 1 and 3 genes contributing to the strength of selective destruction, which can either cause ageing or allow for negligible senescence.
Creator: James Wordsworth
Submitter: James Wordsworth
Model type: Agent based modelling
Model format: Not specified
Environment: Not specified
Organism: Not specified
Investigations: No Investigations
Studies: No Studies
Assays: No Assays
Model of selective destruction in a single population of cells with differing sensitivities for growth. Fast growing cells can be epigenetically converted to slower cells rather than simple cell death as in previous models.
Creator: James Wordsworth
Submitter: James Wordsworth
Model type: Agent based modelling
Model format: Not specified
Environment: Not specified
Organism: Not specified
Investigations: No Investigations
Studies: No Studies
Assays: No Assays
Model of unselective destruction in a single population of cells with differing sensitivities for growth
Creator: James Wordsworth
Submitter: James Wordsworth
Model type: Agent based modelling
Model format: Not specified
Environment: Not specified
Organism: Not specified
Investigations: No Investigations
Studies: No Studies
Assays: No Assays
Model of selective destruction in a single population of cells with differing sensitivities for growth
Creators: James Wordsworth, Daryl Shanley, Hannah O'Keefe
Submitter: James Wordsworth
Model type: Agent based modelling
Model format: Not specified
Environment: Not specified
Organism: Not specified
Investigations: No Investigations
Studies: No Studies
Assays: No Assays
Here, we describe the index file generation of the mm10 genome, the genome alignment with kallisto, and quantification with bustools to obtain the used spliced / unspliced transcript input.
Creator: Markus Wolfien
Submitter: Markus Wolfien
Model type: Not specified
Model format: Not specified
Environment: Not specified
Here is the detailed R script to generate the input needed by scSynO for synthetic cell generation and classification model training.
The code that can be embedded into any other Seurat data processing workflow is:
cell_expression_target_cluster <- as.matrix(GetAssayData(seuratobject, slot = "data")[, WhichCells(seuratobject, ident = "target_cluster_number")]) cell_expression_all_other_clusters <- as.matrix(GetAssayData(seuratobject, slot = "data")[, WhichCells(seuratobject, ident = ...
Creator: Markus Wolfien
Submitter: Markus Wolfien
Model type: Not specified
Model format: Not specified
Environment: Not specified
Single nuclei transcriptomics data as .csv files from the Allen Brain atlas data set of mus musculus (https://celltypes.brain-map.org/) have been utilized as an input for scSynO. The underlying analysis is part of the manuscript entitled "Automated annotation of rare-cell types from single-cell RNA-sequencing data through synthetic oversampling". Data anaylsis and visalizations were mainly generated with the Seurat R package (https://satijalab.org/seurat/archive/v3.2/spatial_vignette.html)
Creator: Markus Wolfien
Submitter: Markus Wolfien
Model type: Not specified
Model format: Not specified
Environment: Not specified
Creator: Saptarshi Bej
Submitter: Markus Wolfien
Model type: Not specified
Model format: Not specified
Environment: Not specified
Creator: Saptarshi Bej
Submitter: Saptarshi Bej
Model type: Not specified
Model format: Not specified
Environment: Not specified
Organism: Not specified
Investigations: 1 hidden item
Studies: 1 hidden item
Dynamic model of glycolysis, pyruvate metabolism and NoxE. The model is parameterized by selecting the best out of 100 parameter set using Copasi's Genetic algorithm with 1000 itterations and 500 simmulatanious models.
Creator: Niels Zondervan
Submitter: Niels Zondervan
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: Not specified
Organism: Mycoplasma pneumoniae
Investigations: Modelling of M. pneumoniae metabolism
Studies: Core Model predictions, Core Model training, Core model predicting combined mutations and pe...
Assays: 40 samples, OE mutants of glycolysis and pyruva..., Construction and training of the core model, Dynamic model simmulation pipeline, Metabolic control analysis (local and global), Validation by simulating independent mutant and...
The new GEM of S. coelicolor developed by Tjasa Kumelj, Snorre Sulheim, Alexander Wentzel and Eivind Almaas in 2017/2018
Creators: Snorre Sulheim, Tjasa Kumelj
Submitter: Snorre Sulheim
Model type: Stoichiometric model
Model format: SBML
Environment: Not specified
Organism: Streptomyces coelicolor
Investigations: No Investigations
Studies: No Studies
Assays: No Assays
Creator: Niels Zondervan
Submitter: Niels Zondervan
Model type: Metabolic network
Model format: SBML
Environment: JWS Online
Organism: Not specified
Investigations: Modelling of M. pneumoniae metabolism
Core model with the addition of a NoxE reaction to regenerate NAD using O2. COPASI’s build in Evolutionary programming algorithm was used to estimate parameters using a maximum of 2000 generations with a population size of 100 models with value scaling as weights to train the 5 parameters of the NoxE reaction.
Creator: Niels Zondervan
Submitter: Niels Zondervan
Model type: Not specified
Model format: Copasi
Environment: Copasi
Organism: Mycoplasma pneumoniae
Investigations: Modelling of M. pneumoniae metabolism
Studies: Core Model training
Butanol producing iNS142, redesigned using RobOKoD.
Creator: Natalie Stanford
Submitter: Natalie Stanford
Model type: Metabolic network
Model format: SBML
Environment: Matlab
Organism: Not specified
Investigations: Designing a new way to predict engineering stra...
Creator: Robert Muetzelfeldt
Submitter: Robert Muetzelfeldt
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: Not specified
Organism: Not specified
Investigations: No Investigations
Studies: No Studies
Assays: No Assays
E.coli Core model, with additional reactions added to generate the beta-oxadation cycle. This is the basic model used in RobOKoD: microbial strain design for (over)production of target compounds (http://fairdomhub.org/publications/236).
Creator: Natalie Stanford
Submitter: Natalie Stanford
Model type: Metabolic network
Model format: SBML
Environment: Matlab
Organism: Not specified
Investigations: No Investigations
Studies: No Studies
Assays: No Assays
Creators: Sarah Kirstein, Katrin Ripken
Submitter: Sarah Kirstein
Investigations: Systems biology investigation of aromatic compo...
Studies: Experimental multi-OMICS
Assays: non-volatile metabolites GC/MS
Creator: Lars Wöhlbrand
Submitter: Lars Wöhlbrand
Investigations: Systems biology investigation of aromatic compo...
Studies: Experimental multi-OMICS
Assays: Proteomic data
Creators: Sarah Kirstein, Katrin Ripken, Esther Wenzel
Submitter: Sarah Kirstein
Investigations: Systems biology investigation of aromatic compo...
Studies: Experimental multi-OMICS
Assays: CoA LC/MS Data
Creators: Katrin Ripken, Esther Wenzel, Sarah Kirstein
Submitter: Sarah Kirstein
Investigations: Systems biology investigation of aromatic compo...
Studies: Experimental multi-OMICS
Assays: CoA LC/MS Data
Creators: Katrin Ripken, Sarah Kirstein
Submitter: Sarah Kirstein
Investigations: Systems biology investigation of aromatic compo...
Studies: Experimental multi-OMICS
Assays: CoA LC/MS Data
Creators: Katrin Ripken, Esther Wenzel, Sarah Kirstein
Submitter: Sarah Kirstein
Investigations: Systems biology investigation of aromatic compo...
Studies: Experimental multi-OMICS
Assays: non-volatile metabolites GC/MS
Creators: Katrin Ripken, Sarah Kirstein
Submitter: Sarah Kirstein
Investigations: Systems biology investigation of aromatic compo...
Studies: Experimental multi-OMICS
Assays: non-volatile metabolites GC/MS
Creators: Daniel Wünsch, Patrick Becker
Submitter: Daniel Wünsch
Investigations: Systems biology investigation of aromatic compo...
Studies: Experimental multi-OMICS
Assays: Cultivation for multi-OMICS
This file contains the script for the downstream scRNA-Seq analysis including quality control using the barcode ranking method together with the tool DropletUtils to exclude empty droplets and undetected genes as well as standard data processing (normalisation, variable feature identification, scaling, and dimensionality reduction) using tools of Seurat (v.3.2.2). After cluster annotation the %mtDNA was plotted for both datasets.
Creator: Anne-Marie Galow
Submitter: Anne-Marie Galow
Investigations: 1 hidden item
This file contains the detailed experimental protocol for the cultivation of "induced sinoatrial bodies (iSABs), the scRNA-Seq procedure as well as the general computational workflow for data processing. The R-script is provided separately.
Creators: Anne-Marie Galow, Sophie Kussauer, Markus Wolfien
Submitter: Anne-Marie Galow
Investigations: 1 hidden item
This file contains the R-script to analyse single nuclei and single cell data of Bl6 and Fzt:DU mice previously processed with cellranger. The analyses utilizes the Seurat and harmony package to integrate three datasets before subsequent downstream analysis characterizing proliferative cardiomyocytes.
Creator: Anne-Marie Galow
Submitter: Anne-Marie Galow
Investigations: 1 hidden item
Creator: Markus Wolfien
Submitter: Markus Wolfien
Investigations: 1 hidden item
Studies: Single nuclei comparison
This file contains the detailed experimental protocol to isolate nuclei from murine hearts.
Creators: Markus Wolfien, Anne-Marie Galow
Submitter: Markus Wolfien
Investigations: 1 hidden item
Studies: Single nuclei characterisation of adult mammali..., integrative cluster analysis - proliferative ca...
Assays: Single nuclei RNA-Seq analysis of Fzt:DU mice, integrative cluster analysis of single cell and...
This R-script contains the single nuclei analysis for our Fzt:DU and BL6 data, namely bustools file integration, preprocessing, scaling, clustering, marker indentification and annotation of markers and RNAvelocity computation.
Creator: Markus Wolfien
Submitter: Markus Wolfien
Investigations: 1 hidden item
Studies: Single nuclei comparison
Detection of small RNAs by blot hybridization.
Creator: Vânia Pobre
Submitter: Vânia Pobre
Investigations: No Investigations
Studies: No Studies
Assays: No Assays
Describes the steps required in order to detect and quantify alcohols and other volatile compounds in microbial culture supernatants by gas chromatography with a flame-ionization detector (GC-FID).
Creator: Maximilian Bahls
Submitter: Maximilian Bahls
Investigations: No Investigations
Studies: No Studies
Assays: No Assays
Creator: Susana Domingues
Submitter: Susana Domingues
Investigations: 1 hidden item
Studies: 1 hidden item
Assays: 1 hidden item
This protocol describes the analysis of RNA-Seq data to identify differential expressed genes between two samples. The protocol is simply the analysis of the data and do not include the sequencing protocol.
Creator: Vânia Pobre
Submitter: Vânia Pobre
Investigations: No Investigations
Studies: No Studies
Assays: No Assays
Metabolomics perturbation sample preparation and description of how the exact details of the perturbations. Perturbations: -Glucose starvation -Amino acid starvation -Fe2+ depletion -Oxidative stress via H2O2 -Glycerol addition to the medium
Creators: Niels Zondervan, Luis Serrano, Maria Lluch, Eva Yus
Submitter: Niels Zondervan
Investigations: Modelling of M. pneumoniae metabolism
Studies: Metabolomics measurements
Standard Operating Procedure describing the process and software used in generating a Genome Scale Metabolic model of M. hyopneumoniae. Used software: Pathway tools PathLogic Cobrapy the Cobra Toolbox libSBML
Creator: Niels Zondervan
Submitter: Niels Zondervan
Investigations: Modelling of M. pneumoniae metabolism
Abstract (Expand)
Authors: Robert Leaman, Rezarta Islamaj, Virginia Adams, Mohammed A Alliheedi, João Rafael Almeida, Rui Antunes, Robert Bevan, Yung-Chun Chang, Arslan Erdengasileng, Matthew Hodgskiss, Ryuki Ida, Hyunjae Kim, Keqiao Li, Robert E Mercer, Lukrécia Mertová, Ghadeer Mobasher, Hoo-Chang Shin, Mujeen Sung, Tomoki Tsujimura, Wen-Chao Yeh, Zhiyong Lu
Date Published: 2023
Publication Type: Journal
Citation: Database 2023,baad005
Abstract (Expand)
Authors: Ghadeer Mobasher, Lukrécia Mertová, Sucheta Ghosh, Olga Krebs, Bettina Heinlein, Wolfgang Müller
Date Published: 11th Nov 2021
Publication Type: Proceedings
DOI: 10.1101/2021.11.09.467905
Citation: biorxiv;2021.11.09.467905v1,[Preprint]
Abstract (Expand)
Authors: A. M. Galow, S. Kussauer, M. Wolfien, R. M. Brunner, T. Goldammer, R. David, A. Hoeflich
Date Published: 24th Aug 2021
Publication Type: Manual
PubMed ID: 34427691
Citation: Cell Mol Life Sci. 2021 Aug 24. pii: 10.1007/s00018-021-03916-5. doi: 10.1007/s00018-021-03916-5.
Abstract (Expand)
Authors: M. Ziegler, M. Monne, A. Nikiforov, G. Agrimi, I. Heiland, F. Palmieri
Date Published: 14th Jun 2021
Publication Type: Journal
PubMed ID: 34198503
Citation: Biomolecules. 2021 Jun 14;11(6). pii: biom11060880. doi: 10.3390/biom11060880.
Abstract
Authors: Mathias Bockwoldt, Dorothée Houry, Marc Niere, Toni I. Gossmann, Ines Reinartz, Alexander Schug, Mathias Ziegler, Ines Heiland
Date Published: 6th Aug 2019
Publication Type: Journal
Citation: Proc Natl Acad Sci USA 116(32):15957-15966
Abstract
Authors: Tjaša Kumelj, Snorre Sulheim, Alexander Wentzel, Eivind Almaas
Date Published: 7th Dec 2018
Publication Type: Not specified
Citation: Biotechnol. J. : 1800180
Abstract (Expand)
Authors: J. J. Koehorst, J. C. van Dam, R. G. van Heck, E. Saccenti, V. A. Dos Santos, M. Suarez-Diez, P. J. Schaap
Date Published: 6th Dec 2016
Publication Type: Journal
PubMed ID: 27922098
Citation: Sci Rep. 2016 Dec 6;6:38699. doi: 10.1038/srep38699.
Abstract (Expand)
Authors: M. R. VanLinden, C. Dolle, I. K. Pettersen, V. A. Kulikova, M. Niere, G. Agrimi, S. E. Dyrstad, F. Palmieri, A. A. Nikiforov, K. J. Tronstad, M. Ziegler
Date Published: 13th Nov 2015
Publication Type: Not specified
PubMed ID: 26432643
Citation: J Biol Chem. 2015 Nov 13;290(46):27644-59. doi: 10.1074/jbc.M115.654129. Epub 2015 Oct 2.
Abstract (Expand)
Authors: N. J. Stanford, P. Millard, N. Swainston
Date Published: 24th Mar 2015
Publication Type: Not specified
PubMed ID: 25853130
Citation: Front Cell Dev Biol. 2015 Mar 24;3:17. doi: 10.3389/fcell.2015.00017. eCollection 2015.
Abstract (Expand)
Authors: T. Maier, J. Marcos, J. A. Wodke, B. Paetzold, M. Liebeke, R. Gutierrez-Gallego, L. Serrano
Date Published: 20th Apr 2013
Publication Type: Not specified
PubMed ID: 23598864
Citation: Mol Biosyst. 2013 Jul;9(7):1743-55. doi: 10.1039/c3mb70113a. Epub 2013 Apr 19.
Abstract (Expand)
Authors: J. A. Wodke, J. Puchalka, M. Lluch-Senar, J. Marcos, E. Yus, M. Godinho, R. Gutierrez-Gallego, V. A. dos Santos, L. Serrano, E. Klipp, T. Maier
Date Published: 4th Apr 2013
Publication Type: Not specified
PubMed ID: 23549481
Citation: Mol Syst Biol. 2013;9:653. doi: 10.1038/msb.2013.6.
Abstract
Authors: Pablo I. Nikel, Víctor de Lorenzo
Date Published: 2013
Publication Type: Not specified
DOI: 10.1016/j.ymben.2012.09.006
Citation: Metabolic Engineering 15 : 98
Abstract (Expand)
Authors: J. Schaber, R. Baltanas, A. Bush, E. Klipp, A. Colman-Lerner
Date Published: 15th Nov 2012
Publication Type: Not specified
PubMed ID: 23149687
Citation: Mol Syst Biol. 2012;8:622. doi: 10.1038/msb.2012.53.
Abstract
Authors: Matthew A. Oberhardt, Jacek Puchałka, Vítor A. P. Martins dos Santos, Jason A. Papin
Date Published: 31st Mar 2011
Publication Type: Not specified
DOI: 10.1371/journal.pcbi.1001116
Citation: PLoS Comput Biol 7(3) : e1001116
Abstract
Authors: Seung Bum Sohn, Tae Yong Kim, Jong Myoung Park, Sang Yup Lee
Date Published: 1st Jul 2010
Publication Type: Not specified
Citation: Biotechnology Journal 5(7) : 739
Abstract (Expand)
Authors: J. Schaber, A. Lapytsko, D. Flockerzi
Date Published: No date defined
Publication Type: Not specified
PubMed ID: 24307567
Citation: J R Soc Interface. 2013 Dec 4;11(91):20130971. doi: 10.1098/rsif.2013.0971. Print 2014 Feb 6.
Abstract (Expand)
Authors: Adriana Buskin, Lili Zhu, Valeria Chichagova, Basudha Basu, Sina Mozaffari-Jovin, David Dolan, Alastair Droop, Joseph Collin, Revital Bronstein, Sudeep Mehrotra, Michael Farkas, Gerrit Hilgen, Kathryn White, Dean Hallam, Katarzyna Bialas, Git Chung, Carla Mellough, Yuchun Ding, Natalio Krasnogor, Stefan Przyborski, Jumana Al-Aama, Sameer Alharthi, Yaobo Xu, Gabrielle Wheway, Katarzyna Szymanska, Martin McKibbin, Chris F Inglehearn, David J Elliott, Susan Lindsay, Robin R Ali, David H Steel, Lyle Armstrong, Evelyne Sernagor, Eric Pierce, Reinhard Luehrmann, Sushma-Nagaraja Grellscheid, Colin A Johnson, Majlinda Lako
Date Published: No date defined
Publication Type: Not specified
DOI: 10.1101/232397
Citation: Human iPSC-derived RPE and retinal organoids reveal impaired alternative splicing of genes involved in pre-mRNA splicing in PRPF31 autosomal dominant retinitis pigmentosa
COVID-19 modelling efforts in advice to Luxembourg government , talk given by Atte Aalto
Creators: Olga Krebs, Stefania Astrologo, Atte Aalto, Jorge Goncalves
Submitter: Olga Krebs
Introductory lecture Biology & Epidemiology
Creators: Hans V. Westerhoff, Stefania Astrologo
Submitter: Hans V. Westerhoff
FAIRDOMHub: Implementing FAIR Data Principles for scientific data management and stewardship. Talk given by Olga Krebs
Creators: Olga Krebs, FAIRDOM team
Submitter: Olga Krebs
Crash course of Mathematical modelling, for any learners who want to use models to better understand and assess COVID-19 policies around the world! This course aims at anyone who seeks to understand and assess the utility of mathematical models to make a prediction which could play a key role in government policymaking, as well as a research strategy for pandemic diseases such as COVID-19. The strategies of ‘learning by example’ and ‘learning by doing’ will be here instantiated as learning how ...
Start Date: 30th Nov 2020
End Date: 2nd Dec 2020
Event Website: https://elixir-luxembourg.org/events/2020_11_30_COVID19_modelling_training
Country: Not specified
City: online course
Figures showing the changes of edges and terms.
Investigations: FAIR Functional Enrichment: Assessing and Model...
Studies: FAIR Functional Enrichment
Assays: FAIR Functional Enrichment
Prov-O Representation for an enrichment analysis experiment on differentially expressed RNA-Seq data, analysed with Enrichr and 2021 version of GO. Rectangle represents Activity, eclipse represents entity and rhombus represents agents
Investigations: FAIR Functional Enrichment: Assessing and Model...
Studies: FAIR Functional Enrichment
Assays: FAIR Functional Enrichment
Supplementary table containing all reactions, genes, and metabolites involved in the metabolic model iAA835 .
Creator: Julia Koblitz
Submitter: Julia Koblitz
Investigations: Systems biology investigation of aromatic compo...
Studies: Metabolic Modelling
Assays: Metabolic modeling of EbN1
This file contains Violin plots for mitochondrial gene transcripts (%mtRNA), cardiac marker (Tnnt2), and pace-maker marker (Hcn4) for identified cell clusters in iSABS and sinoatrial node region (results obtained from a data reanalysis of Goodyer et al.).
Creator: Anne-Marie Galow
Submitter: Anne-Marie Galow
Investigations: 1 hidden item
This file contains several Scatter plots illustrating the correlation of %mtDNA and (a) Tnnt2 (b) Hcn4 (c) total number of gene transcripts per cell In Tnnt2 positive cells and (d) total number of gene transcripts per cell In Hcn4 positive cells.
Creator: Anne-Marie Galow
Submitter: Anne-Marie Galow
Investigations: 1 hidden item
Sehr geehrte Damen und Herren,
wir laden Sie herzlich zum unseren 2. Statusmeeting des Forschungsverbundes iRhythmicsein, welches Live via **Webex **Anbieter am 10.06.2021 übertragen wird. Anbei finden Sie den Flyer mit dem gesamten Programm.
Informationen zum Konsortium erfahren Sie unter: https://irhythmics.med.uni-rostock.de/konsortium/
Bei Interesse wenden Sie sich bitte an die Projektmanegerin via anna.skorska@med.uni-rostock.de Somit werden Ihnen die Zugangsdaten für die Webex ...
Creator: Anna Skorska
Submitter: Anna Skorska
Investigations: No Investigations
Studies: No Studies
Assays: No Assays
Graphical abstract for the manuscript "Quality control in scRNA-Seq can discriminate pacemaker cells – the mtDNA bias" by Anne-Marie Galow#, Sophie Kussauer, Markus Wolfien, Robert David*, and Andreas Hoeflich#*
Creator: Anne-Marie Galow
Submitter: Anne-Marie Galow
Investigations: 1 hidden item
This file contains a UMAP plot generated for the Goodyer dataset illustrating the various cell populations and their proportions as well as the original t-SNE plot of the respective data published by Goodyer et al. in 2019 (doi: 10.1161/CIRCRESAHA.118.314578).
Creator: Anne-Marie Galow
Submitter: Anne-Marie Galow
Investigations: 1 hidden item
This file contains a UMAP plot for the iSABs dataset illustrating the various cell populations and their proportions.
Creator: Anne-Marie Galow
Submitter: Anne-Marie Galow
Investigations: 1 hidden item
Creator: Maximilian Hillemanns
Submitter: Maximilian Hillemanns
Investigations: 1 hidden item
Studies: 1 hidden item
Creator: Maximilian Hillemanns
Submitter: Maximilian Hillemanns
Investigations: 1 hidden item
Studies: 1 hidden item
Creator: Maximilian Hillemanns
Submitter: Maximilian Hillemanns
Investigations: 1 hidden item
Studies: 1 hidden item
Creator: Maximilian Hillemanns
Submitter: Maximilian Hillemanns
Investigations: 1 hidden item
Studies: 1 hidden item
Creator: Maximilian Hillemanns
Submitter: Maximilian Hillemanns
Investigations: 1 hidden item
Studies: 1 hidden item
Creator: Maximilian Hillemanns
Submitter: Maximilian Hillemanns
Investigations: 1 hidden item
Studies: 1 hidden item
Creator: Maximilian Hillemanns
Submitter: Maximilian Hillemanns
Investigations: 1 hidden item
Studies: 1 hidden item
Creator: Maximilian Hillemanns
Submitter: Maximilian Hillemanns
Investigations: 1 hidden item
Studies: 1 hidden item
Creator: Maximilian Hillemanns
Submitter: Maximilian Hillemanns
Investigations: 1 hidden item
Studies: 1 hidden item
Creator: Maximilian Hillemanns
Submitter: Maximilian Hillemanns
Investigations: 1 hidden item
Studies: 1 hidden item
Creator: Maximilian Hillemanns
Submitter: Maximilian Hillemanns
Investigations: 1 hidden item
Studies: 1 hidden item