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22 materials found

Target audience: beginner bioinformaticians  or Biomedical Researchers 


FAIR principles in practice for health data

FAIR principles in practice for health data was developed in the context of the Swiss Personalized Health Network (SPHN) initiative and is part of a series of trainings centered around the [SPHN Interoperability...

Scientific topics: Computer science, Data management, FAIR data, Medical informatics

Operations: Standardisation and normalisation, Design

Keywords: Clinical data, RDF, Knowledge graph, Semantic framework, FAIR, Findability, Accessibility, Interoperability, Reusability

Resource type: Video, E-learning

Expanding the SPHN RDF Schema

Expanding the SPHN RDF Schema is a training that was developed in the context of the Swiss Personalized Health Network (SPHN) initiative and is part of a series of trainings centered around the [SPHN Interoperability...

Scientific topics: Ontology and terminology, Medical informatics, FAIR data, Data management, Computer science

Operations: Editing, Ontology visualisation, Visualisation, Data handling

Keywords: Clinical data, Data semantics, FAIR, Ontology editing, Protegé, RDF, OWL

Resource type: Video, Training materials, E-learning

Training Primer (RDF and SPARQL)

The RDF and SPARQL training primer was developed in the context of the Swiss Personalized Health Network (SPHN) initiative and is part of a series of trainings centered around the [SPHN Interoperability...

Scientific topics: Computer science, Data management, FAIR data, Medical informatics, Ontology and terminology

Operations: Query and retrieval, Database search, Data handling, Data retrieval

Keywords: Clinical data, SPARQL, Query data, RDF, Knowledge graph, Triplestore, Ontology

Resource type: Video, Training materials, E-learning

Semantic Standards

This video was developed in the context of the Swiss Personalized Health Network (SPHN) initiative and serves as an introduction to the main standards used within the [SPHN Interoperability...

Scientific topics: Computer science, Data management, FAIR data, Medical informatics, Ontology and terminology

Operations: Data handling, Standardisation and normalisation

Keywords: Clinical data, Data semantics, FAIR, Standards, Ontology, SNOMED CT, LOINC, ATC, CHOP, ICD, Interoperability

Resource type: Video, Training materials, E-learning

RDF Schema and Data Visualization

RDF Schema and Data Visualization is a training that was developed in the context of the Swiss Personalized Health Network (SPHN) initiative and is part of a series of trainings centered around the [SPHN Interoperability...

Scientific topics: Data visualisation, Medical informatics, FAIR data, Data management, Computer science

Operations: Ontology visualisation, Visualisation, Data retrieval, Data handling, Query and retrieval

Keywords: Clinical data, SPARQL, Data visualization, RDF, Knowledge graph, GraphDB, Mock data

Resource type: Video, Training materials, Mock data, E-learning

Validate Graph Data with SHACL

Validate Graph Data with SHACL is a training that was developed in the context of the Swiss Personalized Health Network (SPHN) initiative and is part of a series of trainings centered around the [SPHN Interoperability...

Scientific topics: Medical informatics, FAIR data, Data management, Computer science

Operations: Validation, Data handling

Keywords: Clinical data, SHACL, Data validation, RDF, Knowledge graph, GraphDB, RDF, RDF graph validation

Resource type: Video, Training materials, E-learning

How to use Python and R with RDF Data

How to use Python and R with RDF Data is a training that was developed in the context of the Swiss Personalized Health Network (SPHN) initiative and is part of a series of trainings centred around the [SPHN Interoperability...

Scientific topics: Computer science, Data management, FAIR data, Medical informatics

Operations: Query and retrieval, Data handling, Data retrieval

Keywords: Clinical data, SPARQL, Query data, RDF, Knowledge graph, Python, R, GraphDB

Resource type: Video, Training materials, Mock data, E-learning

Querying Data with SPARQL

Querying Data with SPARQL is a training that was developed in the context of the Swiss Personalized Health Network (SPHN) initiative and is part of a series of trainings centered around the [SPHN Interoperability...

Scientific topics: Computer science, Data management, FAIR data, Medical informatics, Data mining

Operations: Query and retrieval, Database search, Data handling, Data retrieval

Keywords: Clinical data, SPARQL, Query data, RDF, Knowledge graph, SNOMED CT, LOINC, Interoperability

Resource type: Video, Training materials with mock data, E-learning

ELIXIR TtR course: Basic genomics using advanced analysis tools

Materials from the ELIXIR workshop “ELIXIR TtR course: Basic genomics using advanced analysis tools”, Nov 5-6 2018 at the University of Ljubljana, Faculty of Medicine, Ljubljana, Slovenia

Scientific topics: Genomics

Keywords: Galaxy, training, Genomics, eLearning, EeLP

Resource type: course materials, Training materials, Slides

UNIX Fundamentals

This self-learning tutorial aims to present the UNIX environment and to provide the most basic commands to users with no or very little UNIX knowledge.
The examples are taken from various Biological fields but have been chosen carefully to be easily accessible to a wide audience.
At the end of...

Keywords: Problem based learning, Programming, Unix

Resource type: e-learning

High-throughput sequencing training materials repository

This repository includes training materials on the analysis of high-throughput sequencing (HTS) data, on the following topics: Introduction to HTS, RNA-seq, ChIP-seq and variant calling analysis.
Materials have been annotated following the standards and guidelines proposed at the “Best practices...

Scientific topics: Bioinformatics, Data architecture, analysis and design

Keywords: High throughput sequencing analysis, Rna seq chip seq anayses, Variant calling

Plant and Pathogen Bioinformatics

This package contains presentations and other training material given at the AllBio Plant and Pathogen Bioinformatics training course, held at the European Bioinformatics Institute, Hinxton, United Kingdom, Tuesday, July 8, 2014 - Friday, July 11, 2014. The course was aimed at giving an...

Keywords: Allbio, Bioinformatics, Biological databases, Genome sequence analysis, Pathogenesis, Phytopathogens, Plants

Training Bioinformatics in the Cloud

I present the points of view, the challenges and advantages of developing training materials through the cloud.

Keywords: Advanced bioinformatics training, Cloud computing, Training

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

Bioinformatics: Gene-protein-structure-function

This presentation examines the available in silico tools for protein structure and function prediction. It examines the major protein family databases (PROSITE, PRINTS, Pfam, etc.), and explores why tools like PSI-BLAST, while convenient and easy to use, may not always give optimal results. The...

Keywords: Expert systems, Genequiz, Protein family characterisation, Protein family databases, Protein sequence analysis, Psi blast

InterPro: An introduction

This presentation introduces the background to the InterPro database: what it is, where it came from, and what was the vision behind its creation. It examines in particular whether the database has evolved in line with its original vision, and asks whether the resource is still fit for purpose. 

Keywords: Integrated diagnostic tools, Protein family characterisation, Protein sequence analysis

PRINTS: A protein family database with a difference

A presentation designed to introduce the concept of protein family analysis and characterisation using motif-based methods, with a particular focus on protein fingerprinting. Following a general introduction to sequence analysis, and the fingerprint approach, specific examples are given to...

Keywords: Functional diagnosis, Protein family characterisation, Protein sequence analysis

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