1. Home
  2. Materials
Register training material
3 materials found

Target audience: bioinformaticians 

and

Licence: MIT License 

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 http://tess.elixir-uk.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*. 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
Datanator tutorial

Datanator is an integrated database of genomic and biochemical data designed to help investigators find data about specific molecules and reactions in specific organisms and specific environments for meta-analyses and mechanistic models. Datanator currently includes metabolite concentrations, RNA...

Scientific topics: Omics, Bioinformatics, Systems biology, Cell biology, Molecular biology

Operations: Filtering, Query and retrieval

Keywords: genomics, Proteomics, transcriptomics, Metabolomics, reaction kinetics, Kinetic modeling, meta analysis

Resource type: Tutorial

Datanator tutorial http://tess.elixir-uk.org/materials/datanator-tutorial Datanator is an integrated database of genomic and biochemical data designed to help investigators find data about specific molecules and reactions in specific organisms and specific environments for meta-analyses and mechanistic models. Datanator currently includes metabolite concentrations, RNA modifications and half-lives, protein abundances and modifications, and reaction kinetics integrated from several databases and numerous publications. The Datanator website and REST API provide tools for extracting clouds of data about specific molecules and reactions in specific organisms and specific environments, as well as data about similar molecules and reactions in taxonomically similar organisms. This tutorial provides a brief introduction to the Datanator database and web application. The tutorial illustrates how to search the Datanator database and obtain and refine clouds of data about specific metabolites, RNA, proteins, and reactions of interest. Omics Bioinformatics Systems biology Cell biology Molecular biology genomics, Proteomics, transcriptomics, Metabolomics, reaction kinetics, Kinetic modeling, meta analysis mololecular cell biologists systems biologists bioinformaticians Computational biologists modelers
Introductory image processing on biological images using python.

A jupyter notebook python practical designed to give students a introduction to opening and processing image files derived from biological samples.

Resource type: Jupyter notebook, PDF

Introductory image processing on biological images using python. http://tess.elixir-uk.org/materials/introductory-image-processing-on-biological-images-using-python A jupyter notebook python practical designed to give students a introduction to opening and processing image files derived from biological samples. Anatole Chessel Volker Baecker Bioimage Analysts Image Analysts Computer Vision scientists bioinformaticians computational scientists Biophysicists Biologists Microscopists Python for Biologists PhD students