Investigations

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143 Investigations visible to you, out of a total of 388

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

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We performed topological analysis on the diagrams of the COVID-19 DM repository using the tool Vanted / SBGN-ED, which supports the import and export of several standard formats (such as SBML, SBGN-ML, and GML).

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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

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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

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In this investigation, we aim to develop automatic workflows to pinpoint drug targets carrying genomic variants at high frequency in the population

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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.

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 parameters to match absolute RNA levels from the TiMet WP1a RNA dataset of Flis et al. 2015 in U2019.2 (first version was U2017.2), then reoptimises globally to match RNA timeseries, period and amplitude constraints to produce the U2019.3 model. [The first version U2017.3 also matched the protein

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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).

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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.

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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

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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

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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.

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

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Consortium website:

https://covidclinical.net/

Slack:

https://c19i2b2.slack.com/

Owner: Nils Gehlenborg (nils@hms.harvard.edu)

i2b2 tranSMART Foundation Call to Action:

https://transmartfoundation.org/covid-19-call-to-action/

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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

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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

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Objectives: Development of efficient ATA immobilization approach. Production of a hybrid catalyst of high catalytic efficiency.

Description of Work: Τhe ATAs selected in WP2 will be expressed, purified and covalently and/or non-covalently immobilized on the GO selected in WP1. The catalytic behavior (in terms of catalytic activity, stability and reusability) and the structural implications of the immobilization will be investigated. For comparison purposes, the non-optimized ATAs (prior to the

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Objectives: Identification of amine transaminases (ATAs) able to catalyze efficiently the amination of a desired set of ketones and aldehydes (expected products of GO oxidation). Optimization of the most potent biocatalysts, in terms of catalytic efficiency, stability, availability of functional groups for covalent immobilization.

Description of Work: ATAs from our construct selection (>30 wild-type and variants of both (R)- and (S)-enantioselectivity) with different substrate selectivity will

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Objectives: Protocol identification and establishment for the synthesis of high-performing catalytic GO in the desired oxidation reactions under mild conditions. Characterization of the most prominent materials synthesized and comparison to commercially available material.

Description of Work: Several established chemical methods will be used for the synthesis of GO. Each batch will be characterized, for instance for its C/O ratio, surface area and conductivity. The catalytic profile of the

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No description specified

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Die Charité – Universitätsmedizin Berlin betreibt gemeinsam mit dem Berlin Institute of Health

Clinical Study Center (BIH-CSC) eine zentrale Registerstudie ("Pa-COVID-19") und Phänotypisierungs-

plattform für alle an der Charité behandelten Patienten mit COVID-19.

Pa-COVID-19 dient der harmonisierten und standardisierten klinischen und molekularen

Phänotypisierung von COVID-19 Patienten. Übergeordnetes Ziel ist die schnelle und umfassende

Charakterisierung von COVID-19 zur Identifikation von

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Governments and policymakers take different measures vis-à-vis the COVID-19 crisis, ranging from advice to reduce social activities, to a complete lock down of society and economy. To support them with tools that enable them to fulfill their tasks we constructed a differential equation model for the COVID-19 epidemics using systems biology methodologies.

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Collection of cross-links to other sites that gather COVID-19 information

No description specified
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