Investigations
We develop macrophage logical models to represent the activation/polarization of this immune cell. Interactions are manually curated with available macrophage literature. The models are mainly built and analyzed in GINsim. But other resources are used to integrate specific pathways or small modules (CasQ software) and to analyze the logical models (CoLoMoTo Notebooks).
Submitter: Viviam Solangeli Bermúdez Paiva
Studies: C19DM - Macrophage logical model
Assays: No Assays
The COVIDminer text mining project (https://rupertoverall.net/covidminer/) reads the published literature concerning SARS-CoV-2 and COVID-19 to extract statements about (primarily molecular) interactions. Using the API associated with this project, putative interactors can be automatically retrieved for the existing COVID-19 Disease Maps. New interactions are prioritised based on their frequency in the literature and the topological importance of the interaction targets to provide a focussed set ...
Frequency doubling in the cyanobacterial circadian clock
Submitter: Jacky Snoep
Studies: Figure 4B: A minimal mathematical model, containing an incoherent feedfo..., Figure 6C and D: The clock-sigC circuit represents a general mechanism t...
Assays: Frequency doubling in the cyanobacterial circadian clock, Frequency doubling in the cyanobacterial circadian clock
Collection of models submitted to PLaSMo by Jonathan Massheder and automatically transferred to FAIRDOM Hub.
Submitter: BioData SynthSys
Studies: LINTUL_V2 - PLM_42, SUCROS1 - PLM_24
Assays: LINTUL_V2 - PLM_42, version 1, SUCROS1 - PLM_24, version 1
Sucrose translocation between plant tissues is crucial for growth, development and reproduction of plants. Systemic analysis of this metabolic process and underlying regulatory processes can help to achieve better understanding of carbon distribution within the plant and the formation of phenotypic traits. Sucrose translocation from ‘source’ tissues (e.g. mesophyll) to ‘sink’ tissues (e.g. root) is tightly bound to the proton gradient across the membranes. The plant sucrose transporters are grouped ...
Submitter: Jurgen Haanstra
Studies: Inhibition with Sulfasalazine (SSZ), Measurements of metabolism of HepG2 cells at 0 mM, 6 mM or 22 mM externa..., protein per cell for HepG2 cells
Assays: Cell counts and BCA Protein, Cell counts and metabolite levels, Inhibition experiment for the effect of SSZ on HepG2 metabolism
Antibiotics are made during the second phase of growth when there is a transition in metabolism from primary to secondary metabolism. Primary metabolism is growth related and involves all the normal cellular activities associated with cell growth and division. Whereas secondary metabolism is non-growth linked and is non-essential but many important activities occur during this phase which help the bacterium survive.
One of these activities is antibiotic production and is widespread in streptomycetes ...
Submitter: Jay Moore
Studies: ScoCyc metabolic pathway curation, Timeseries 1
Assays: Metabolic pathway curation, Online/offline measurements, metabolomics, proteomics, transcriptomics
The aims of this investigation is to quantify metabolites associated with pathways involved in stress responses for parameterising models of oxidative stress metabolism; the measurement of metabolic fluxes of metabolites of interest with intracellular concentrations
Submitter: Dong-Hyun Kim
Studies: Metabolic flux measurement, Targeted metabolite analysis, Untargeted metabolite analysis
Assays: Generation of uniformly 13C-labelled E. coli extract, Intracellular metabolite concentrations in T. brucei exposed to oxidativ..., Intracellular metabolite concentrations in T. brucei under pH stress, LC-MS based absolute quantification of extracellular metabolites, LC-MS based absolute quantification of intracellular metabolites, Metabolite profiling on T. brucei exposed to oxidative stress
Collection of models submitted to PLaSMo by Andrew Millar and automatically transferred to FAIRDOM Hub.
Submitter: BioData SynthSys
Studies: Arabidopsis clock model P2011, graphical diagram - PLM_1045, Arabidopsis clock model P2011.3.1 - PLM_1041, Arabidopsis clock model P2011.4.1 - PLM_1042, Arabidopsis clock model P2011.5.1 - PLM_1043, Arabidopsis clock model P2011.6.1 - PLM_1044, Arabidopsis clock models P2011.1.2 and P2011.2.1 - PLM_71, Arabidopsis_clock_P2011 - PLM_64, Arabidopsis_clock_P2012 - PLM_70, At_Pokh2011_LD_degr_Op1Ap3.xml - PLM_67, At_Pokh2011v6_plasmo_ltdParams.xml - PLM_68, AuxSim - PLM_27, AuxSim full - PLM_30, DomijanTS_AtClock2011 - PLM_50, Locke2005_CircadianClock_tanh - PLM_8, Locke2006_CircadianClock_tanh - PLM_10, OK MEP pathway 2013 - PLM_72, P2012_AJMv2_NoABA - PLM_69, Salazar2009_FloweringPhotoperiod - PLM_9, Sorokina2011_Ostreo_starch - PLM_44, Wilczek photothermal Science - PLM_48
Assays: Arabidopsis clock model P2011, graphical diagram - PLM_1045, version 1, Arabidopsis clock model P2011.1.2 - PLM_71, version 1, Arabidopsis clock model P2011.2.1 - PLM_71, version 2, Arabidopsis clock model P2011.3.1 - PLM_1041, version 1, Arabidopsis clock model P2011.4.1 - PLM_1042, version 1, Arabidopsis clock model P2011.5.1 - PLM_1043, version 1, Arabidopsis clock model P2011.6.1 - PLM_1044, version 1, Arabidopsis_clock_P2011 - PLM_64, version 1, Arabidopsis_clock_P2011 - PLM_64, version 2, Arabidopsis_clock_P2011 - PLM_64, version 3, Arabidopsis_clock_P2011 - PLM_64, version 4, Arabidopsis_clock_P2012 - PLM_70, version 1, Arabidopsis_clock_P2012 - PLM_70, version 2, At_Pokh2011_LD_degr_Op1Ap3.xml - PLM_67, version 1, At_Pokh2011_LD_degr_Op1Ap3.xml - PLM_67, version 2, At_Pokh2011_LD_degr_Op1Ap3.xml - PLM_67, version 3, At_Pokh2011_LD_degr_Op1Ap3.xml - PLM_67, version 4, At_Pokh2011_LD_degr_Op1Ap3.xml - PLM_67, version 5, At_Pokh2011_LD_degr_Op1Ap3.xml - PLM_67, version 6, At_Pokh2011v6_plasmo_ltdParams.xml - PLM_68, version 1, AuxSim - PLM_27, version 1, AuxSim full - PLM_30, version 1, DomijanTS_AtClock2011 - PLM_50, version 1, DomijanTS_AtClock2011 - PLM_50, version 2, Locke2005_CircadianClock_tanh - PLM_8, version 1, Locke2006_CircadianClock_tanh - PLM_10, version 1, OK MEP pathway 2013 - PLM_72, version 1, P2012_AJMv2_NoABA - PLM_69, version 1, P2012_AJMv2_NoABA - PLM_69, version 2, Salazar2009_FloweringPhotoperiod - PLM_9, version 1, Salazar2009_FloweringPhotoperiod - PLM_9, version 2, Sorokina2011_Ostreo_starch - PLM_44, version 1, Wilczek photothermal Science - PLM_48, version 1, Wilczek photothermal Science - PLM_48, version 2
Submitter: Dikshant Pradhan
Studies: Excision of mutagenic replication-blocking lesions suppresses cancer but...
Assays: GPT Assay – Data Attached, Mass Spectrometry Processing – Data Linked, Mass Spectrometry – Data Linked, Mouse Necropsy – Metadata, RaDR Image Machine Learning Analysis – Data Attached, Tissue Imaging – Metadata, Tissue Lysis – Metadata
Understanding how liver function arises from the complex interaction of morphology, perfusion, and metabolism from single cells up to the entire organ requires systems-levels computational approaches.
Submitter: Matthias König
Studies: A Multiscale Computational Model of Human Galactose Metabolism, PKDB Caffeine Study
Assays: Digitized pharmacokinetics data (Akinyinka2000), Digitized pharmacokinetics data (Amchin1999), Digitized pharmacokinetics data (Blanchard1983a), Digitized pharmacokinetics data (Haller2002), Digitized pharmacokinetics data (Healy1991), Digitized pharmacokinetics data (Hetzler1990), Digitized pharmacokinetics data (Jeppesen1996), Digitized pharmacokinetics data (Kakuda2014), Digitized pharmacokinetics data (Kaplan1997), Digitized pharmacokinetics data (Magnusson2008), Digitized pharmacokinetics data (Oh2012), Digitized pharmacokinetics data (Perera2011), Digitized pharmacokinetics data (Spigset1999a), Digitized pharmacokinetics data (Tanaka2014), Galactose Modelling
Time series response of potato cv. Désirée, which is tolerant to PVY infection, was analysed in both inoculated as well as upper non-inoculated leaves. Additionally, transgenic plants deficient in accumulation of salicylic acid (NahG- Désirée) were studied in the same setting.
All the files available are published under the CC BY 4.0 license.
A further investigation of the variation of FNR number in E.coli Cyo/Cyd mutants is carrying out at different oxygen supply levels. The agent-based FNR and ArcBA model is going to be used for this prediction. The number of Cyo or Cyd and other unrelated agents would be set as ‘0’ at the initial XML file with which the model starts. According to the restrictions of supercomputer ‘Iceberg’ (serviced provided by the University of Sheffield), certain parameters, such as memory per node, would be ...
A key insight, emerging from discussions and data between the projects PIs, was the importance of switching rates in bistable systems. While the existence of multiple steady states in bistable systems can be described by universal models (that do not differ between different systems), switching rates from one stable state to another depend on the molecular details of the system under consideration.
- 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
Automated model building using Taverna workflows from KEGG-Database
Collection of models submitted to PLaSMo by Robert Muetzelfeldt and automatically transferred to FAIRDOM Hub.
Submitter: BioData SynthSys
Studies: 3PG - PLM_12, CENTURY_Rowe_daily - PLM_22, DALEC - PLM_23, LINTUL - PLM_4, McMurtrie vegetation model - PLM_11, TRIFFID - PLM_5
Assays: 3PG - PLM_12, version 1, CENTURY_Rowe_daily - PLM_22, version 1, DALEC - PLM_23, version 1, LINTUL - PLM_4, version 1, McMurtrie vegetation model - PLM_11, version 1, McMurtrie vegetation model - PLM_11, version 2, TRIFFID - PLM_5, version 1
Experimental data and all related material for the publication "Multi -omics reveal lifestyle of acidophile, mineral-oxidizing model species Leptospirillum ferriphilumT".
Submitter: Malte Herold
Studies: Omics_data_analysis
Assays: Experimental methods, Genomics, Proteomics, RNAseq
High salinity chemostat cultivation, multiomics sampling (proteome, transcriptome, metabolome, fluxome) and modelling of carbon core metabolism of Bacillus subtilis 168.
Submitter: Sandra Maass
Studies: B. subtilis_SysMo2_Chemostat_growthrate-salt, Fluxome analysis of Bacillus subtilis 168 under osmotic stress
Assays: 13C Metabolic Flux Analysis of Bacillus subtilis 168 in continuous high-..., Absolute quantification of proteins by the AQUA-technology, Absolute quantification of proteins using QconCAT technology, Relative quantification of proteins by metabolic labeling, Transcriptome data for chemostat cultivated samples, extracellular metabolites, intracellular metabolites