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index.xml
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<?xml version="1.0" encoding="utf-8" standalone="yes"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
<channel>
<title>Home on EnzymeML Project</title>
<link>http://EnzymeML.org/</link>
<description>Recent content in Home on EnzymeML Project</description>
<generator>Hugo -- gohugo.io</generator>
<language>en-us</language>
<lastBuildDate>Thu, 22 Sep 2022 17:01:34 +0700</lastBuildDate><atom:link href="http://EnzymeML.org/index.xml" rel="self" type="application/rss+xml" />
<item>
<title>PyEnzyme</title>
<link>http://EnzymeML.org/tools/pyenzyme/</link>
<pubDate>Thu, 22 Sep 2022 17:01:34 +0700</pubDate>
<guid>http://EnzymeML.org/tools/pyenzyme/</guid>
<description>PyEnzyme is a comprehensive software solution for manipulating EnzymeML files. Furthermore, the library incorporates convenient access to prominent modeling platforms, such as COPASI and PySCeS, enabling a smooth progression from laboratory experiments to kinetic characterization. Additionally, PyEnzyme empowers users to generate aesthetically appealing, publication-quality visualizations, as well as export data to widely utilized formats, such as CSV and JSON.
The API uses the SBML syntax and naming conventions which are familiar to enzymologists to be implemented into EnzymeML.</description>
</item>
<item>
<title>Publications</title>
<link>http://EnzymeML.org/documents/publications/</link>
<pubDate>Mon, 09 Nov 2020 17:01:34 +0700</pubDate>
<guid>http://EnzymeML.org/documents/publications/</guid>
<description>This section lists preprints and published work describing EnzymeML and core EnzymeML-supporting software tools.
Original Peer Review Papers Malzacher S, Range J, Halupczok C, Pleiss J, Rother D (2020). BioCatHub, a graphical user interface for standardized data acquisition in biocatalysis. Chemie Ingenieur Technik 92, 1251-1251. doi: 10.1002/cite.202055297
Pleiss, J. Standardized data, Scalable Documentation, sustainable storage – Enzymeml as a basis for fair data management in biocatalysis. ChemCatChem 13, 3909–3913 (2021). doi: 10.</description>
</item>
<item>
<title>Juergen Pleiss</title>
<link>http://EnzymeML.org/team/juergen-pleiss/</link>
<pubDate>Mon, 19 Nov 2018 10:47:58 +1000</pubDate>
<guid>http://EnzymeML.org/team/juergen-pleiss/</guid>
<description>Bioinformatics Group Leader, Institute of Biochemistry and Technical Biochemistry, University of Stuttgart, Germany.</description>
</item>
<item>
<title>Specific APIs</title>
<link>http://EnzymeML.org/downloads/api/</link>
<pubDate>Thu, 22 Feb 2018 17:01:34 +0700</pubDate>
<guid>http://EnzymeML.org/downloads/api/</guid>
<description>An application programming interface (API) the Python library PyEnzyme, and the Java library JEnzyme, which support reading, writing, editing, merging, and visualization of EnzymeML documents.
Presently, we have three application-specific thin API layers COPASI, STRENDA DB and SABIO-RK. They are available to download in the links below:
TL_COPASI TL_STRENDA TL_BioCatNet </description>
</item>
<item>
<title>Specifications</title>
<link>http://EnzymeML.org/documents/specifications/</link>
<pubDate>Thu, 22 Feb 2018 17:01:34 +0700</pubDate>
<guid>http://EnzymeML.org/documents/specifications/</guid>
<description>The EnzymeML specifications define the syntax and semantics of EnzymeML. These documents are the definitive references for EnzymeML.
STRENDA Guidelines EnzymeML helps you to implement the STRENDA Guidelines. These guidelines aim to support authors in comprehensively reporting kinetic and equilibrium data from their investigations of enzyme activities.
Structure of EnzymeML document An EnzymeML document consists of three file types: a file using SBML to describe the experimental reaction conditions, the kinetic model, and the kinetic parameters, CSV (comma-separated values)-formatted files to store the time courses of substrate and product concentrations, and a manifest file lists the content of the document.</description>
</item>
<item>
<title>Tutorial and Documentation</title>
<link>http://EnzymeML.org/tools/template/tutorial/</link>
<pubDate>Thu, 22 Sep 2022 17:01:34 +0700</pubDate>
<guid>http://EnzymeML.org/tools/template/tutorial/</guid>
<description>This document will further explain the workflow and how to use the spreadsheet by giving best practices. For this, the next paragraph will further elucidate how to acquire the template, how to fill in data and finally how to convert it to EnzymeML.
1. Download the EnzymeML template The EnzymeML template can be downloaded here. Additionally, an example template is provided which demonstrates how a template should be filled.
Once downloaded, you can open the template with any commonly available spreadsheet application such as Microsoft Excel™ or OpenOffice Calc.</description>
</item>
<item>
<title>For Experimentalists</title>
<link>http://EnzymeML.org/services/experimentalists/</link>
<pubDate>Wed, 28 Nov 2018 15:15:26 +1000</pubDate>
<guid>http://EnzymeML.org/services/experimentalists/</guid>
<description>How can EnzymeML help you to manage your experimental data? EnzymeML was developed to support data acquisition, data analysis, and sharing of data by providing a standardized exchange format for enzymatic data. EnzymeML follows the Standards of Reporting Enzymology Data (STRENDA) Guidelines, a comprehensive set of metadata describing reaction conditions and kinetic models. EnzymeML is written in eXtensible Markup Language (XML).
It builds on the well-established Systems Biology Markup Language (SBML) and includes information about the enzyme, the substrate(s) and product(s), the reaction conditions, the selected kinetic model, and estimated kinetic parameters.</description>
</item>
<item>
<title>PyEnzyme</title>
<link>http://EnzymeML.org/downloads/pyenzyme/</link>
<pubDate>Thu, 22 Feb 2018 17:01:34 +0700</pubDate>
<guid>http://EnzymeML.org/downloads/pyenzyme/</guid>
<description>The Python library PyEnzyme is part of the EnzymeML application programming interface (API). It supports reading, writing, editing and visualization of EnzymeML documents.
The library JEnzyme was built based on its respective SBML counterparts libsbml. It can be downloaded here.</description>
</item>
<item>
<title>REST-API</title>
<link>http://EnzymeML.org/tools/rest/</link>
<pubDate>Thu, 22 Sep 2022 17:01:34 +0700</pubDate>
<guid>http://EnzymeML.org/tools/rest/</guid>
<description>We understand the significance of embracing a language-independent methodology for data retrieval and parsing in the present interconnected application ecosystem. In light of this, we have made accessible a publicly available REST-API that incorporates a comprehensive array of endpoints, providing comprehensive EnzymeML handling capabilities. This API allows you to integrate PyEnzyme into your web-based toolkit, regardless of your technology stack, thereby granting you access to all the benefits of PyEnzyme without the need to program in Python.</description>
</item>
<item>
<title>Frank T. Bergmann</title>
<link>http://EnzymeML.org/team/frank-bergmann/</link>
<pubDate>Thu, 20 Dec 2018 13:44:23 +1000</pubDate>
<guid>http://EnzymeML.org/team/frank-bergmann/</guid>
<description>Modeling of Biological Processes Group in Centre for Organismal Studies, Heidelberg University, Germany.</description>
</item>
<item>
<title>For Modelers</title>
<link>http://EnzymeML.org/services/modelers/</link>
<pubDate>Wed, 28 Nov 2018 15:15:34 +1000</pubDate>
<guid>http://EnzymeML.org/services/modelers/</guid>
<description>How can EnzymeML help you develop, implement and analyze models? An EnzymeML document provides the complete experimental information including the enzyme concentration, the initial concentrations of substrates, products, or inhibitors, and the measured concentrations of substrate or product at different time points. It might also provide a preferred kinetic model or alternative kinetic models. The model consists of a kinetic law that determines the temporal changes in the concentration of substrates, products, or enzymes as a function of measured concentrations of substrates, products, and enzymes, and kinetic parameters.</description>
</item>
<item>
<title>Use cases</title>
<link>http://EnzymeML.org/documents/cases/</link>
<pubDate>Thu, 22 Feb 2018 17:01:34 +0700</pubDate>
<guid>http://EnzymeML.org/documents/cases/</guid>
<description>To illustrate the power of EnzymeML, we illustrate selected applications for experimental enzymologists, system biology modelers, and software developers. More applications and use cases are available in our publications on EnzymeML.
Creating EnzymeML documents from spreadsheets In the absence of a standard format, experimentalists typically store their experimental time course data in a spreadsheet following an ad hoc structure. Recently, a CSV-formatted spreadsheet, the BioCatNet template, was proposed to store and report experimental data on enzyme-catalyzed reactions according to the STRENDA Guidelines.</description>
</item>
<item>
<title>Privacy Information, Informationen nach Artikel 13 DS-GVO</title>
<link>http://EnzymeML.org/privacy-info/</link>
<pubDate>Sun, 21 May 2023 17:01:24 +0700</pubDate>
<guid>http://EnzymeML.org/privacy-info/</guid>
<description>Coming soon!!!</description>
</item>
<item>
<title>Impressum/ Anbieterkennzeichnung</title>
<link>http://EnzymeML.org/legal-note/</link>
<pubDate>Fri, 19 May 2023 17:01:34 +0700</pubDate>
<guid>http://EnzymeML.org/legal-note/</guid>
<description>Coming soon!!</description>
</item>
<item>
<title>Santiago Schnell</title>
<link>http://EnzymeML.org/team/santiago-schnell/</link>
<pubDate>Thu, 08 Oct 2020 10:47:58 +1000</pubDate>
<guid>http://EnzymeML.org/team/santiago-schnell/</guid>
<description>William K. Warren Foundation Dean, College of Science, University of Notre Dame, USA</description>
</item>
<item>
<title>For Database Providers</title>
<link>http://EnzymeML.org/services/database/</link>
<pubDate>Wed, 28 Nov 2018 15:14:39 +1000</pubDate>
<guid>http://EnzymeML.org/services/database/</guid>
<description>How can EnzymeML help you to publish results and to exchange data? EnzymeML is a flexible data model for biocatalysis and enzymology capable of completely describing an experiment in a machine-readable format. To handle and integrate EnzymeML in your database, we provide our software solution PyEnzyme, which can be either installed locally or reached via several endpoints of our REST-API.
Validation of minimal requirements and upload to SABIO-RK PyEnzyme as well as our REST-API provide an interface to validate incoming EnzymeML documents to comply with the minimum requirements necessary for a successful upload to your database.</description>
</item>
<item>
<title>For Software Developers</title>
<link>http://EnzymeML.org/services/software/</link>
<pubDate>Wed, 28 Nov 2018 15:14:39 +1000</pubDate>
<guid>http://EnzymeML.org/services/software/</guid>
<description>Want to implement EnzymeML read and write functionalities in your software? Here you have some ideas to inspire your team. EnzymeML follows the Standards of Reporting Enzymology Data (STRENDA) Guidelines, a comprehensive set of metadata describing reaction conditions and kinetic models. EnzymeML is written in eXtensible Markup Language (XML). It builds on the well-established Systems Biology Markup Language (SBML) and includes information about the enzyme, the substrate(s) and product(s), the reaction conditions, the selected kinetic model, and estimated kinetic parameters (find the XML schema definition here).</description>
</item>
<item>
<title>Application Programming Interface</title>
<link>http://EnzymeML.org/documents/api/</link>
<pubDate>Thu, 22 Feb 2018 17:01:34 +0700</pubDate>
<guid>http://EnzymeML.org/documents/api/</guid>
<description>An application programming interface (API) that consists of two libraries, the Python library PyEnzyme, and the REST-API, which support reading, writing, editing, merging, and visualization of EnzymeML documents.
API description The API uses the SBML syntax and naming conventions which are familiar to enzymologists to be implemented into EnzymeML. The basic concept of the two libraries is the usage of multiple dictionaries, in which proteins, reactants, units, and reactions are stored.</description>
</item>
<item>
<title>Software and Databases Guide</title>
<link>http://EnzymeML.org/documents/guide/</link>
<pubDate>Thu, 22 Feb 2018 17:01:34 +0700</pubDate>
<guid>http://EnzymeML.org/documents/guide/</guid>
<description>The EnzymeML Software and Database Guide provides a summary of all EnzymeML-compatible software systems and databases currently available.
COPASI COPASI is a software application for the simulation and analysis of biochemical networks and their dynamics. COPASI is a stand-alone program that supports models in the SBML standard and can simulate their behavior using ODEs or Gillespie&rsquo;s stochastic simulation algorithm; arbitrary discrete events can be included in such simulations. COPASI is versatile with powerful features for representing enzyme models, simulation, data analysis, visualization and output.</description>
</item>
<item>
<title>Validators</title>
<link>http://EnzymeML.org/downloads/validators/</link>
<pubDate>Thu, 22 Feb 2018 17:01:34 +0700</pubDate>
<guid>http://EnzymeML.org/downloads/validators/</guid>
<description>EnzymeML has a specific validation tool that guarantees compatibility with SBML. Further application-specific validation tools have been added, such as a STRENDA DB validator to check for compatibility with the STRENDA Guidelines.
The validators are part of application-specific thin API layers COPASI, STRENDA DB andSABIO-RK. They are available to download in the links below:
TL_COPASI TL_STRENDA TL_BioCatNet </description>
</item>
<item>
<title>Carsten Kettner</title>
<link>http://EnzymeML.org/team/carsten-kettner/</link>
<pubDate>Thu, 20 Dec 2018 13:45:06 +1000</pubDate>
<guid>http://EnzymeML.org/team/carsten-kettner/</guid>
<description>STRENDA Commission Coordinator, Beilstein-Institut, Germany.</description>
</item>
<item>
<title>Jan Range</title>
<link>http://EnzymeML.org/team/jan-range/</link>
<pubDate>Thu, 20 Dec 2018 13:44:55 +1000</pubDate>
<guid>http://EnzymeML.org/team/jan-range/</guid>
<description>Research Software Engineer, Cluster Of Excellence &ldquo;SimTech&rdquo;, University of Stuttgart, Germany</description>
</item>
<item>
<title>Stephan Malzacher</title>
<link>http://EnzymeML.org/team/stephan-malzacher/</link>
<pubDate>Thu, 20 Dec 2018 13:44:55 +1000</pubDate>
<guid>http://EnzymeML.org/team/stephan-malzacher/</guid>
<description>Research Software Engineer, Institute of Bio- and Geosciences, Foschungszentrum Jülich, Germany</description>
</item>
<item>
<title>Contact</title>
<link>http://EnzymeML.org/contact/</link>
<pubDate>Thu, 08 Oct 2020 17:01:34 +0700</pubDate>
<guid>http://EnzymeML.org/contact/</guid>
<description>EnzymeML Project Contacts For questions, suggestions, or participation in the EnzymeML project, please contact the project coordinators:
Jürgen Pleiss, Carsten Kettner, Frank Bergmann or Santiago Schnell.
STRENDA Guidelines If you are interested to learn more about the STRENDA Guidelines, please contact Carsten Kettner.
Website Please contact our webmaster. This website was developed by modifying the Hugo Serif theme by zerostatic.</description>
</item>
</channel>
</rss>