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18 materials found

Keywords: computer-science  or metadata 

From Swab to Server: Testing, Sequencing, and Sharing During a Pandemic

Discover how sample strategies can affect scientific research and results:
Sampling is a critical part of research in any field. In studying a disease such as Covid-19, it’s imperative that your sample and sampling methods are best-suited to reflect accurate results.

Supported by expert...

Keywords: metadata, Sequencing, genomics, Genomic data, data quality, scientific quality assurance, data sharing, ethics, data ethics, public health, coronavirus, sars-cov-2, covid-19, data linkage

Resource type: FREE online course

FAIR data - Module 3 (Metadata)

Les Métadonnées : les standards du domaine des données omiques en biologie et séances pratiques d’annotations de jeux de données

Scientific topics: Data management, Biology, Bioinformatics

Operations: Data handling

Keywords: metadata, data annotation, life science standards, data sharing

Resource type: Slides

FAIR data - Module 1 (research data)

Research data and their centrality in the research process.
This material is mostly in French.

Keywords: metadata, Data Life Cycle, Reproducibility, Data management plan

Resource type: Slides

Data Management Planning workshop for new Life Science Projects

Slides from Data Management Planning online workshop for Life Science Projects for researchers

Scientific topics: Data management

Operations: Data retrieval, Data handling, Deposition

Keywords: data management plan, NeLS, TSD, metadata, sensitive, data publication, data protection, storage, identifiers, DMP, licensing, Compliance, data life cycle - collect, data life cycle - reuse, data life cycle - analyse, data life cycle - process, data life cycle - preserve, data life cycle - share, data life cycle - plan

Resource type: Slides

FAIRify your data: data documentation and metadata

“Documentation is a love letter that you write to your future self.”
Damian Conway (2005)

Make your data as useful as possible for “your future self” and others
Never forget what you did or how or why you did it
Always find beck your precious data (easily)
Make data understandable,...

Scientific topics: Data management

Keywords: data documentation, metadata

Resource type: Presentation

Giving data context, structure and meaning

Metadata, standards and ontologies are common ways of providing data with context, structure and meaning. In this webinar Sira explores the idea of once data are ontologised (mapped to standard structured vocabulary), they become linkable to build a bigger infrastructure of knowledge network and...

Keywords: metadata, Ontologies

What happens to your data?

This webinar focuses on what happens to your data after you submit it to a public repository and addresses the question of data ownership.

Keeva and Nancy introduce the concepts of FAIR data, metadata and standards. They then show you where you can find an appropriate place to share your data...

Scientific topics: Data management

Keywords: metadata, ArrayExpress

Resource type: Video

FAIRification & Data modelling


Keywords: FAIR, linked data, ontologies, metadata

Resource type: Slides

Essential Steps of the FAIRification Process

Since 2014, a number of FAIR Stakeholders have developed tools and methods around the FAIRifcation of typical datasets. In the last 5 years, these efforts were field tested in a series of "Bring Your Own Data" Workshops" (

This document records the...

Keywords: FAIR, data stewardship, metadata, linked data

Resource type: Training materials

Big Data, Genes, and Medicine

This course distills for you expert knowledge and skills mastered by professionals in Health Big Data Science and Bioinformatics. You will learn exciting facts about the human body biology and chemistry, genetics, and medicine that will be intertwined with the science of Big Data and skills to...

Keywords: life-sciences, computer-science, bioinformatics, algorithms

Bioinformatics Capstone: Big Data in Biology

In this course, you will learn how to use the BaseSpace cloud platform developed by Illumina (our industry partner) to apply several standard bioinformatics software approaches to real biological data.

In particular, in a series of Application Challenges will see how genome assembly can be used...

Keywords: life-sciences, computer-science, health-informatics, algorithms

Finding Hidden Messages in DNA (Bioinformatics I)

Named a top 50 MOOC of all time by Class Central!

This course begins a series of classes illustrating the power of computing in modern biology. Please join us on the frontier of bioinformatics to look for hidden messages in DNA without ever needing to put on a lab coat.

In the first half of the...

Keywords: life-sciences, computer-science, health-informatics, algorithms

Finding Mutations in DNA and Proteins (Bioinformatics VI)

In previous courses in the Specialization, we have discussed how to sequence and compare genomes. This course will cover advanced topics in finding mutations lurking within DNA and proteins.

In the first half of the course, we would like to ask how an individual's genome differs from the...

Keywords: life-sciences, computer-science, health-informatics, algorithms

Genome Sequencing (Bioinformatics II)

You may have heard a lot about genome sequencing and its potential to usher in an era of personalized medicine, but what does it mean to sequence a genome?

Biologists still cannot read the nucleotides of an entire genome as you would read a book from beginning to end. However, they can read...

Keywords: life-sciences, computer-science, health-informatics, algorithms

Biology Meets Programming: Bioinformatics for Beginners

Are you interested in learning how to program (in Python) within a scientific setting?

This course will cover algorithms for solving various biological problems along with a handful of programming challenges helping you implement these algorithms in Python. It offers a gently-paced introduction...

Keywords: life-sciences, computer-science, health-informatics, software-development

Genomic Data Science and Clustering (Bioinformatics V)

How do we infer which genes orchestrate various processes in the cell? How did humans migrate out of Africa and spread around the world? In this class, we will see that these two seemingly different questions can be addressed using similar algorithmic and machine learning techniques arising from...

Keywords: life-sciences, computer-science, health-informatics, algorithms

Comparing Genes, Proteins, and Genomes (Bioinformatics III)

Once we have sequenced genomes in the previous course, we would like to compare them to determine how species have evolved and what makes them different.

In the first half of the course, we will compare two short biological sequences, such as genes (i.e., short sequences of DNA) or proteins. We...

Keywords: life-sciences, computer-science, health-informatics, algorithms

Molecular Evolution (Bioinformatics IV)

In the previous course in the Specialization, we learned how to compare genes, proteins, and genomes. One way we can use these methods is in order to construct a "Tree of Life" showing how a large collection of related organisms have evolved over time.

In the first half of the course, we will...

Keywords: life-sciences, computer-science, health-informatics, algorithms