Register training material
14 materials found

Authors: allegra.via Via  or Jonathan Karr 


runBioSimulations tutorial and help

runBioSimulations is a web application for executing a broad range of modeling studies and visualizing their results. runBioSimulations uses BioSimulators to supports a broad range of modeling frameworks (e.g., logical, constraint-based, kinetic), simulation algorithms (e.g., CVODE, FBA, SSA),...

Scientific topics: Simulation experiment, Computational biology, Systems biology

Operations: Modelling and simulation

Keywords: biosimulators, COMBINE, OMEX, SED-ML, Modeling, dynamic simulations, SBML, BNGL

Resource type: Tutorial, Documentation

BioSimulators tutorial and help

BioSimulators is a registry of containerized biosimulation tools that provide consistent command-line interfaces. The BioSimulations web application helps investigators browse this registry to find simulation tools that have the capabilities (supported modeling frameworks, simulation algorithms,...

Scientific topics: Simulation experiment, Computational biology, Systems biology

Operations: Modelling and simulation

Keywords: Modeling, biomodel, dynamic simulations, COMBINE, OMEX, SED-ML, SBML, BNGL

Resource type: Tutorial, Documentation

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, Scipy,...

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

BioSimulations tutorial and help

BioSimulations is a web application for sharing and re-using biomodels, simulations, and visualizations of simulations results. BioSimulations supports a wide range of modeling frameworks (e.g., kinetic, constraint-based, and logical modeling), model formats (e.g., BNGL, CellML, SBML), and...

Scientific topics: Simulation experiment, Systems biology, Computational biology

Operations: Modelling and simulation, Visualisation

Keywords: SystemsBiology, ComputationalBiology, Computational modelling, Modeling, Biomodelling, Model, Kinetic modeling, SED-ML, COMBINE

Resource type: Documentation

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

Introduction to Biopython

This is a module from the "Python for Biologists" course. The module presents an introduction to Biopython. It shows how to deal with sequences and sequence records, how to download records from NCBI databases, how to run Blast and how to parse XML Blast outputs.

Keywords: Bioinformatics, Biopython, Programming, Python, Python biologists

Using R with Python

This is a module from the "Python for Biologists" course. It describes the Python module interfacing the R package for statistics. The module shows how to calculate mean, standard deviation, z-score and p-value of a set of numbers, and how to generate plots. Input files for the scripts presented...

Keywords: Programming, Python, Python biologists

Searching data using Python

This is a module from the "Python for Biologists" course. It describes how to use Python dictionary and set data structures to search your data. In particular, how to use a dictionary to represent the genetic code table and use it to translate a nucleotide sequence into a protein sequence, and...

Keywords: Programming, Python, Python biologists

Pattern Matching

This is a module from the "Python for Biologists" course. It teaches how to do pattern matching in Python, i.e. how to find a substring (or a set of substrings) in a string. To this aim, it introduces the regular expression syntax, and the tools needed to search regular expressions in biological...

Keywords: Pattern matching, Programming, Python, Python biologists

Writing functions in Python programming

This is a module from the "Python for Biologists" course. It deals with functions and how to write and use them. It also introduces namespaces and the tuple data structure. The module contains several exercises and suggested solutions. The text of exercises is also provided in a separate file. 

Scientific topics: Bioinformatics

Keywords: Programming, Python, Python biologists

Python Programs

This is a module from the "Python for Biologists" course. It deals with Python programs, how to write and run them, and how to provide input and generate output. The module also contains exercises and suggested solutions. 

Keywords: Programming, Python, Python biologists

Linear Motifs and Phosphorylation Sites

This is a lecture on linear motifs and phophorylation sites (P-sites). Some materials from other lectures are reused.
The lecture is basically about computational approaches to encode, predict, analyse, and use functional motifs and P-sites.
Here you can find:

    A definition of linear motifs and...

Keywords: Bioinformatics

Parsing data records using Python programming

This is a module from the "Python for Biologists" course. One typical problem in bioinformatics is parsing data files. This module explains how to parse FASTA files and GenBank records. It also introduces the if/elif/else construct to make choice in programming and the list  data structure. The...

Keywords: Bioinformatics, Programming, Python, Python biologists, Record parsing

Introduction to Unix

Introductory lecture to the Unix/Linux command-line

    Description of the computer shell and the command-line interface

    Differences between graphical and command-line interfaces

    The most commond Unix/Linux commands are provided

 
 

Keywords: Bioinformatics, Programming, Unixlinux