Short Name: T21_SXPsysbio Title: Use a systems biology approach to identify regulatory bottlenecks in SxPv1 Description: Samples from SXPv1.0 plants as well as sister nulls (progeny from the original transgenic event in which the transgene has segregated) and wild type will be grown and leaf samples taken for RNA extraction and profiling of primary metabolites and volatiles (target pheromones as well as potential derivatives) (P1, P5). Phenotypic and GC-MS data will be obtained and analysed from ...
Submitter: Marko Petek
Studies: Investigation files, _S_P1_SPv10T0andT1, _S_P1_SPv10T2andT3, _S_P1_SPv1TransientExp, _S_P1_SxPAltAcTransferases, _S_P1_SxPv10vsSxP12, _S_P1_SxPv12T2, _S_P4_CoExpNetViz, _S_P4_DiNAR, _S_P4_GAtreat, _S_P4_SxP10-newG-DE, _S_P4_SxP10-oldG-DE, _S_P4_SxP1012-finalG, _S_P4_SxP12-newG-DE
Assays: _A_00_SxP_photos-phenotyping, _A_01_RNA1-RNAisol, _A_01_SxP_Data_Only-CoExp, _A_01_SxPv12_fastq-QC, _A_01_mapping-CLC, _A_01_toNewGenome-CLC-mapping, _A_02_FastQC-bioinfo, _A_02_Nb_datasets-CoExp, _A_02_SxPv12_mapping-CLC, _A_02_limmavoomDE-R, _A_02a_limmavoom-multim-R, _A_02a_limmavoomDEbylines-R, _A_02b_limmavoom-uniquem-R, _A_03_MapMan-visualisation, _A_03_NewGenome-MapMan, _A_03_SxPv12_limmavoom_DE-R, _A_03_mapping-CLC, _A_03a_mapping2-STAR, _A_04_GSEA-Stat, _A_04_MapManBINenrich-GSEA, _A_04_Mercator-bioinfo, _A_04_SxPv12_GeneSetEnrichment-RNAseg-GSEA, _A_05_DEstat-R, _A_05_Phenotype_analysis-Stat, _A_05_VOCcomp-Bioinfo, _A_05a_DEstat2-R, _A_05b_DElow-wt-R, _A_06_MapMan-bioinfo, _A_06_SxPv1-0_Illumina-Centrifuge, _A_07_NbAUSv1-0-InterPro, _A_07_transgenes-CLC, _A_CKN-DiNAR, _A_CKN_NbL35-DiNAR, _A_LeavesSxPv10vsv12-GCMS, _A_P4_v10v12-phenotyping, _A_PIS-DiNAR, _A_PIS-SxPv12-DiNAR, _A_PIS_NbL35-DiNAR, _A_RootsSxPv10vsv12-GCMS, _A_SP10T0Analysis-GCMS, _A_SP10T1Analysis-GCMS, _A_SPv10EaDActAnalysis-GCMS, _A_SPv10T2Analysis-GCMS, _A_SPv10T3Analysis-GCMS, _A_SPv10_phenotyping-Images, _A_SxPAlternativeAcetyltransferases-GCMS, _A_SxPv10vsv12-phenotyping, _A_SxPv12ScreeningT2-GCMS, _A_TransientSPv11andSPv12-GCMS, _I_T21_SXPsysbio-files, _S_P1_SPv10T0andT1-files, _S_P1_SPv10T2andT3-files, _S_P1_SPv1TransientExp-files, _S_P1_SxPAltAcTransferases-files, _S_P1_SxPv10vsSxP12-files, _S_P1_SxPv12T2-files, _S_P4_CoExpNetViz-files, _S_P4_DiNAR-files, _S_P4_GAtreat-files, _S_P4_SxP10-newG-DE-files, _S_P4_SxP10-oldG-DE-files, _S_P4_SxP1012-finalG-files, _S_P4_SxP12-newG-DE-files
We performed topological analysis on pathways from a harmonised dataset containing pathways from the COVID-19 Disease Map, WikiPathways, and Reactome. The analysis was done using Vanted, SBGN-ED, and LMME which support the import and export of several standard formats (such as SBML, and SBGN-ML).
Submitter: Felicia Burtscher
Assays: No Assays
Data, FMv2 model and simulations for the Chew et al. 2017 paper (bioRxiv https://doi.org/10.1101/105437 ), updated 2022 as bioRxiv https://doi.org/10.1101/105437v2, mostly on the prr7 prr9 double mutant, with controls in lsf1 and prr7 single mutants. This is one of the outputs from the EU TiMet project, https://fairdomhub.org/projects/92.
This data archive was updated during submisson to the journal _in Silico _Plants in 2022, and a Snapshot was published. NB ...
Submitter: Andrew Millar
Studies: Analysis of Framework Model version 2 (FMv2), Construction of Framework Model version 2 (FMv2), Test of FMv2, follow-on: mechanisms of malate/fumarate accumulation, Test of FMv2, photoperiodic flowering and hypocotyl elongation, Test of FMv2, study Gibberellins 1, Test of FMv2, study Laurel & Hardy 1, Test of FMv2, study Laurel & Hardy 2, Test of FMv2, study Laurel & Hardy 3, Tests of FMv2, compilations and figures
Assays: Assimilation and partitioning of 14CO2 at night, Biomass and metabolites, Biomass and metabolites, Biomass and metabolites, Biomass, leaf area and gas exchange data, Biomass, leaf number and metabolites, Circadian period analysis, Composition of FMv2, FMv2 simulation, FMv2 simulation, FMv2 simulation, Mizuno lab, Flowering time in clock mutants, Mizuno lab, Hypocotyl length in clock mutants, Relationship among FMv2 outputs, Sensitivity analysis of FMv2, Simulating clock gene expression with model P2011.1.2, Thiamine vitamers, TiMet WP1.1, Clock gene expression in clock mutants, TiMet WP1.1a Metabolite analysis of clock mutants
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: No Studies
Assays: No Assays
Data integration is an essential part of Systems Biology. Scientists need to combine different sources of information in order to model biological systems, and relate those models to available experimental data for validation. Currently, only a small fraction of the data and models produced during Systems Biology investigations are deposited for reuse by the community, and only a smaller fraction of that data is standards compliant, semantic content. By embedding semantic technologies into familiar ...
Submitter: Olga Krebs
Assays: Affy Transcriptomics Templates, Chip-chip Excel Template, General Transcriptomics Templates, Metabolomics Master Template, NimbleGen Transcriptomics Templates, Proteomics Template (gel electrophoresis), Proteomics Templates (Mass spectrometry), RT-PCR Excel Template, Standard-based Excel template for metabolomics data
Short Name: 03_Omics Title: Omics analysis of RNAi response in CPB Description: Transcriptomics and metagenome changes upon feeding CPB larvae with dsRNA Phenodata: ./phenodata_20210115.txt pISA Investigation creation date: 2021-01-15 pISA Investigation creator: Marko Petek Principal investigator: Marko Petek License: CC BY 4.0 Sharing permission: Private Upload to FAIRDOMHub: Yes
Submitter: Marko Petek
Assays: _A_01-DNAisol, _A_01_RNA-Seq_dsEGFP-NGS, _A_02-DNASeq, _A_02_CLC-RNASeq, _A_03-Centrifuge, _A_04_DE_divers-R, _A_05_extr_reads-rcf, _A_06_extr_bact-assembly, _A_07_allReads_meta-assembly, _I_03_Omics-files, _S_01_ns-dsRNA_trans-files, _S_02_metagenome_resp-files
Short Name: 02_FieldTrials Title: Field trials Description: Field trials - spraying CPB larvae on potato field with the insecticidal dsRNA validated for effectiveness in the laboratory trials Phenodata: ./phenodata_20210115.txt pISA Investigation creation date: 2021-01-15 pISA Investigation creator: Marko Petek Principal investigator: Marko Petek License: CC BY 4.0 Sharing permission: Private Upload to FAIRDOMHub: Yes
Short Name: 01_LabTrials Title: Laboratory trials Description: Selection of targets and their validation in trials performed in the laboratories and greenhouse at NIB Phenodata: ./phenodata_20210113.txt pISA Investigation creation date: 2021-01-13 pISA Investigation creator: Marko Petek Principal investigator: Marko Petek License: CC BY 4.0 Sharing permission: Private Upload to FAIRDOMHub: Yes
Submitter: Marko Petek
Studies: Investigation files, _S_01_TargetSelect, _S_02_dsRNAorder, _S_03_dsRNAprod, _S_04_Stages, _S_05_jun2016, _S_06_oct2016, _S_07_dec2016, _S_08_jan2017, _S_09_jun2017, _S_10_apr2018, _S_11_may2018
Assays: _A_00_Ecoli-dry, _A_00_jun2017_dsRNA_stabil-wet, _A_01_AgroRNA-wet, _A_01_LitData-dry, _A_01_dec2016-phenotyping, _A_01_jan2017-phenotyping, _A_01_jun2016-phenotyping, _A_01_jun2017-phenotyping, _A_01_jun2017-phenotyping, _A_01_may2018-phenotyping, _A_01_oct2016-phenotyping, _A_01_pIsol-wet, _A_02_UlrichTop100-BLAST, _A_02_dec2016-RNAisol, _A_02_jun2016-RNAisol, _A_02_jun2017-RNAisol, _A_02_plasmid-SangerSeq, _A_02_qPCR_ampl_test-wet, _A_03_RNaseItreat-wet, _A_03_dec2016-qPCR, _A_03_jun2016-qPCR, _A_03_jun2017-qPCR, _A_03_patentDB-BLAST, _A_03_stages-RNAisol, _A_04_ortho-BLAST, _A_04_prod-qPCR, _A_04_stages-qPCR, _A_05_CPB_gene-annot, _A_06_splitter_BLAST-dry, _A_07_MergeEvi-dry, _A_08_SelTargetsA-dry, _I_01_LabTrials-files, _S_01_TargetSelect-files, _S_02_dsRNAorder-files, _S_03_dsRNAprod-files, _S_04_Stages-files, _S_05_jun2016-files, _S_06_oct2016-files, _S_07_dec2016-files, _S_08_jan2017-files, _S_09_jun2017-files, _S_10_apr2018-files, _S_11_may2018-files
Because enzyme activity depends very much on the reaction conditions, it is crucial to report all these metadata (see for example the STRENDA Guidelines:https://www.beilstein-strenda-db.org/strenda/public/guidelines.xhtml).
Another challenge in experiments to determine enzyme reaction parameters is the choice of suitable substrate concentrations to enable optimal kinetic fits and the informed choice of a kinetic model.
A Jupyter notebook is given to assist in the choice of substrate concentrations ...
Submitter: Gudrun Gygli
Assays: Use a Jupyter Notebook to design an initital rate experiment, Use a Jupyter Notebook to model Michaelis-Menten Kinetics on experimenta..., Use a Jupyter Notebook to understand how a progress curve experiment can..., Use a Jupyter Notebook to understand how the Selwyn test works
The dataset presents mathematical models of the gene regulatory network of the circadian clock, in the plant Arabidopsis thaliana. The work is published in Urquiza-Garcia and Millar, Testing the inferred transcription rates of a dynamic, gene network model in absolute units, In Silico Plants, 2021.
Starting from the P2011 model, this project corrects theoretical issues (EC steady state binding assumption) to form an intermediate model (first version U2017.1; published as U2019.1) model, rescales ...
Multiscale and multicellular simulation of SARS-CoV-2 infection uncover points of intervention to evade apoptosis.
Our framework enables the simulation of the dynamics of signaling pathways that include the relevant players in SARS-CoV-2 infection, at the level of the individual cell and of the cell population. These different players encompass the virus, epithelial and immune cells. The model focuses on apoptosis and suggests two knock out alterations that force apoptosis of the ...
Research in Systems Biology involves integrating data and knowledge about the dynamic processes in biological systems in order to understand and model them. By connecting fields such as genomics, proteomics, bioinformatics, mathematics, cell biology, genetics, mathematics, engineering and computer sciences, Systems Biology enables discovery of yet unknown principles underlying the functioning of living cells. At the same time, testable and predictive models of complex cellular pathways and ...
An experimental workflow to provide detailed information of the molecular mechanisms of enzymes is described. This workflow will help in the application of enzymes in technical processes by providing crucial parameters needed to plan, model and implement biocatalytic processes more efficiently. These parameters are homogeneity of the enzyme sample (HES), kinetic and thermodynamic parameters of enzyme kinetics and binding of reactants to enzymes. The techniques used to measure these properties are ...
Submitter: Gudrun Gygli
Assays: Analysis of data from ITC experiments (binding), Analysis of data from ITC experiments (kinetics), Binding of HK to Gre2p (ITC-BIND), Binding of NADP+ to Gre2p in HEPES Buffer (ITC-BIND), Binding of NADP+ to Gre2p in KPi Buffer (ITC-BIND), Binding of NADP+ to Gre2p in PBS Buffer (ITC-BIND), Binding of NADPH to Gre2p in HEPES Buffer (ITC-BIND), Binding of NADPH to Gre2p in KPi Buffer (ITC-BIND), Binding of NADPH to Gre2p in PBS Buffer (ITC-BIND), Binding of NADPH to Gre2p in Tween-KPi Buffer (ITC-BIND), Binding of NDK to Gre2p (ITC-BIND), DLS measurements in 2 buffers, DLS measurements in KPi Buffer and in KPi buffer with Tween added, DLS measurements in KPi buffer with BSA added, Kinetic parameters of Gre2p, Kinetics of the reaction of NDK and NADPH with Gre2p (ITC-MIM) in HEPES ..., Kinetics of the reaction of NDK and NADPH with Gre2p (ITC-MIM) in KPi bu..., Kinetics of the reaction of NDK and NADPH with Gre2p (ITC-MIM) in PBS bu..., Kinetics of the reaction of NDK and NADPH with Gre2p (ITC-MIM) in Tween-..., Kinetics of the reaction of NDK and NADPH with Gre2p (ITC-rSIM) in 3 buf..., Selwyn test of Gre2p, Specific activity of Gre2p
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 ...
Submitter: Rupert Overall
Studies: No Studies
Assays: No Assays
We further used the transcriptome dataset from the GEO database with accession number GSE147507 (Blanco-Melo et al., 2020) to extract the series number 5 from the dataset, consisting of 2 conditions in triplicate, A549 cells treated with a mock and A549 infected with SARS-CoV-2, measured 24 hours after treatment. Phosphoproteomic data of mock-treated and SARS-CoV2 infected cells were extracted from (Stukalov et al., 2020). We then applied our pipeline described in M&M X. This work notably ...
Submitter: Aurélien Dugourd
Assays: No Assays
In this investigation, we aim to develop automatic workflows to pinpoint drug targets carrying genomic variants at high frequency in the population
Submitter: Janet Piñero
Assays: No Assays
In this investigation we aim to develop automatic workflows to analyze COVID19 Omics data to understand and predict the molecular pathways depicting host-virus interaction.
Submitter: Dikshant Pradhan
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
Submitter: Pasquale Linciano
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).
The hallmarks of cancer provide a highly cited and well-used conceptual framework for describing the processes involved in cancer cell development. However, methods for translating these high-level concepts into data-level associations between hallmarks and genes (for high throughput analysis), vary widely between studies. In this investigation we compare cancer hallmark mapping strategies from different studies, based on Gene Ontology and biological pathway annotation. By analysing the semantic ...
Submitter: Katy Wolstencroft
Assays: Analysing Changes to GO Biological Process, Annotation Consensus and GO Consensus, Hub genes of modules and enriched GO terms, Jaccard Index Prognostic Hallmark Genes, WGCNA Prognostic Hallmark Genes
NFDI4Health task area 2 targets core deficits in medical sciences, i.e. the lack of harmonised standards for data and data quality management in clinical trials, public health surveys, and epidemiological cohorts, as well as the lack of information on and access to relevant standards. By making standards available, TA2 will improve the findability, accessibility and interoperability of existing and novel data bodies. For this purpose, guidelines, standards and policies on data management and ...
Submitter: Martin Golebiewski
Studies: NFDI4Health T2.1: Data management and publication policies, NFDI4Health T2.2: Data and metadata standards and integration, NFDI4Health T2.3: Data quality and data provenance, NFDI4Health T2.4: Standardisation of health data access and interoperabi...
Assays: No Assays
The aim of this investigation is to understand molecular mechanisms of PUFA biosynthesis and regulation in order to enable the sustainable use of vegetable oils in aquafeeds as current sources of fish oils are unable to meet increasing demands for omega-3 PUFAs. By generating gene knockouts, we would like to study the genes that are crucial for multi-tissue synthesis of PUFA synthesis in vivo.
Multidisciplinary development of selective anti-parasitic multi-target inhibitors of PTR1/DHFR based on a pteridine scaffold.
Submitter: Ina Poehner
Assays: Compound library preparation, Correlation analysis between PTR1 and DHFR activities and anti-parasitic..., Correlation analysis between predicted ADMET properties and anti-parasit..., Docking receptor preparation, In silico ADMET data prediction, Induced-fit docking studies, PAINS filtering, Rigid-body docking studies
Present in many industrial effluents and as intermediate of lignin degradation, phenol is a widespread pollutant causing serious environmental problems, due to its toxicity to animals and humans. Removal of phenol from the environment by bacteria has been studied extensively over the past decades, but only little is known about phenol biodegradation in hostile environments. We combined metabolomics and transcriptomics together with metabolic modelling to elucidate the organism’s response to growth ...
Consortium website: https://covidclinical.net/
i2b2 tranSMART Foundation Call to Action: https://transmartfoundation.org/covid-19-call-to-action/
Objectives: Empowering smooth implementation and fruitful completion of all WPs and tasks. Implementation of a data management plan for efficient dissemination under F.A.I.R. principles.
Description of Work: The PI of the project with the heads of the collaborating groups will closely monitor the progress of the technical and administrative tasks and it will implement actions to correct any deviation from the established work-plan. The whole group will meet regularly every six months or more ...
Objectives: Establishment of the chemoenzymatic process with the best GO-ATA hybrid catalysts. Highlighting of the potential of the process in semi-preparative scale.
Description of Work: The best hybrid catalysts identified in WP3 will be investigated in coupled one-pot reactions selected in WP1, in batch and continuous flow reactors. The productivity of the system will be optimized with response surface methodology (RSM), for parameters such as temperature, duration, substrate concentration ...