Plant Phenotyping Data managment (MIAPPE)
This material is first targetting plant biologist willing to describe and annotate their phenotyping experiments before publication. Database managers and software developpers will also receive an introduction of the current plant phenotyping standards (MIAPPE, BrAPI, Crop ontology). Learners...
Scientific topics: Data management, Plant biology, Phenomics
Operations: Formatting, Annotation
Keywords: Plant Phenotyping, Data-format, data sharing
Resource type: Training materials
Plant Phenotyping Data managment (MIAPPE)
https://github.com/MIAPPE/training/tree/master/Paris-Feb-2020
https://tess.elixir-europe.org/materials/plant-phenotyping-data-managment-miappe
This material is first targetting plant biologist willing to describe and annotate their phenotyping experiments before publication. Database managers and software developpers will also receive an introduction of the current plant phenotyping standards (MIAPPE, BrAPI, Crop ontology). Learners will know how to use standards and ontologies, how to describe their measurment protocole and practices how to fill a template with their data and how to apply the standards concept in some data managment tools.
Cyril Pommier
Daniel Faria
Evangelia Papoutsoglou
Célia Michotey
Elizabeth Arnaud
Anne-Françoise Adam-Blondon
Data management
Plant biology
Phenomics
Plant Phenotyping, Data-format, data sharing
Biologists
geneticists
plant researchers
software engineers
database managers
DE-Sim examples, tutorials, and documentation
*DE-Sim* is an open-source, Python-based object-oriented discrete-event simulation (DES) tool that makes it easy to use large, heterogeneous datasets and high-level data science tools such as [NumPy](https://numpy.org/), [Scipy](https://scipy.org/scipylib/index.html),...
Scientific topics: Computational biology, Mathematics, Computer science, Simulation experiment
Operations: Visualisation, Modelling and simulation
Keywords: data-driven modeling, Computational modelling, discrete-event simulation, DES, object-oriented programming, Python, data visualization, Data Science
Resource type: examples, Tutorial, Jupyter notebook, API reference
DE-Sim examples, tutorials, and documentation
https://github.com/KarrLab/de_sim
https://tess.elixir-europe.org/materials/de-sim-examples-tutorials-and-documentation
*DE-Sim* is an open-source, Python-based object-oriented discrete-event simulation (DES) tool that makes it easy to use large, heterogeneous datasets and high-level data science tools such as [NumPy](https://numpy.org/), [Scipy](https://scipy.org/scipylib/index.html), [pandas](https://pandas.pydata.org/), and [SQLAlchemy](https://www.sqlalchemy.org/) to build and simulate complex computational models. Similar to [Simula](http://www.simula67.info/), *DE-Sim* models are implemented by defining logical process objects which read the values of a set of shared variables and schedule events to modify their values at discrete instants in time.
This website provides examples, tutorials, and documentation for *DE-Sim*.
Jonathan Karr
Arthur Goldberg
Computational biology
Mathematics
Computer science
Simulation experiment
data-driven modeling, Computational modelling, discrete-event simulation, DES, object-oriented programming, Python, data visualization, Data Science
computational scientists
Computational biologists
bioinformaticians
software engineers
programmers
InterMine operator manual
Documentation on how to install, configure and operate an InterMine instance.
Keywords: Data integration, Data analysis, Data publishing, FAIR
Resource type: Documentation
InterMine operator manual
http://intermine.org/im-docs
https://tess.elixir-europe.org/materials/intermine-operator-manual
Documentation on how to install, configure and operate an InterMine instance.
Julie Sullivan
Gos Micklem
Yo Yehudi
Sergio Contrino
Rachel Lyne
Daniela Butano
Justin Clark-Casey
Kevin Herald Reierskog
Data integration, Data analysis, Data publishing, FAIR
Bioinformaticians
software engineers
