This is the third and last part of a webinar series on InterPro which is held between May 6th 2020 and May 20th 2020.

InterPro is a database that helps users to understand the possible functions of proteins sequence by identifying what family it belongs to or what domains and motifs it contains. To deal with the growing volume of protein sequence data and an increasing demand to retrieve subsets of the data, often via programmatic access, the InterPro website has been entirely redesigned. It provides additional features and more flexibility in querying, presenting and retrieving data. The website relies on an Application Programming Interface (API) which can also be utilised by users for direct access to the data.

This webinar describes how the InterPro data is structured in the API, and how it could be accessed programmatically for further bioinformatics analyses.

You can access the slides via GitHub.

Who is this course for?
This webinar is aimed at scientists and bioinformaticians, with basic programming knowledge, who are interested in accessing the InterPro database programmatically.

The Ensembl project offers integrated genome, variation, gene regulation and comparative genomics data of mainly vertebrate genomes on an open access web browser platform.

This webinar will introduce you to the analysis of Linkage Disequilibrium (LD) between variants with Ensembl. We will look at different ways to explore and visualise LD in the Ensembl genome browser website. We will discuss the new LD Calculator tool which has been released with Ensembl 91 and show how to use it.

Who is this course for?
This webinar is aimed at individuals who wish to learn more about analysing LD with Ensembl. No prior knowledge of bioinformatics is required, but an understanding of undergraduate level genetics would be useful.

Outcomes
By the end of the webinar you will be able to:

Analyse linkage disequilibrium between variants in Ensembl
Visualise linkage disequilibrium using the Ensembl Genome Browser

UniProt is a high quality, comprehensive protein resource. Next to expert curation, one of the core activities at UniProt is to develop computational methods for the functional annotation of protein sequences. In this webinar, we will be introducing our functional annotation system UniFire that can be used by the community to share and run rule-based automatic annotation systems to add functional information to proteins.

Who is this course for?
No prior knowledge of bioinformatics is required, but an undergraduate level knowledge of biology would be useful.

Outcomes
By the end of the webinar you will be able to:

Outline the types of data available in UniProt
Describe the automatic annotation systems used in UniProt
Describe the UniFire platform for sharing and utilising UniProt’s automatic annotation systems

The Ensembl VEP is a powerful tool that allows you to input a list of genetic variants and determines which genes are affected and how. In this webinar, you’ll learn how to use the online VEP tool, which is suitable for analysing short lists of genetic variants, and the offline tool, which allows you to annotate whole genome variant calls.

Who is this course for?
This webinar is suitable to any clinical or research scientists who are interested in exploring genetic variants and their effect. In this webinar we will use examples from human clinical data but the VEP tool is available for other species too.

Outcomes
By the end of the webinar you will be able to:

Describe the application of VEP
Analyse short lists of genetic variants using VEP
Annotate variation data

This course explores a range of contemporary scholarship oriented to the study of ‘cybercultures,’ with a focus on research inspired by ethnographic and more broadly anthropological perspectives. Taking anthropology as a resource for cultural critique, the course will be organized through a set of readings chosen to illustrate central topics concerning the cultural and material practices that comprise digital technologies. We’ll examine social histories of automata and automation; the trope of the ‘cyber’ and its origins in the emergence of cybernetics during the last century; cybergeographies and politics; robots, agents and humanlike machines; bioinformatics and artificial life; online sociality and the cyborg imaginary; ubiquitous and mobile computing; ethnographies of research and development; and geeks, gamers and hacktivists. We’ll close by considering the implications for all of these topics of emerging reconceptualizations of sociomaterial relations, informed by feminist science and technology studies.

The primary learning objective of this textbook is to introduce the reader to the fundamental statistical methods and basic analytical procedures associated with processing data in regard to healthcare research. It is intended that by working through the applications and practice problems, readers should be able to understand and apply some of the methods for developing, implementing, and applying healthcare statistic principles in research.

UniProt is a high quality, comprehensive protein resource in which the core activity is the expert review and annotation of proteins where the function has been experimentally investigated. At the same time the UniProt database contains large numbers of proteins which are predicted to exist from gene models, but which do not have associated experimental evidence indicating their function. UniProt commits significant resources to developing computational methods for functional annotation of these predicted proteins based on the data in entries that have gone through the expert review process.

We will describe the two main automated annotation systems currently in use. First, UniRule, which is an established UniProt system in which curators manually develop rules for annotation. Second ARBA (Association-Rule-Based Annotator), which has recently been introduced as a significant improvement in fully automated functional annotation. ARBA is a multiclass learning system which uses rule mining techniques to generate concise annotation models. ARBA employs a data exclusion set that censors data not suitable for computational annotation, and generates human-readable rules for each UniProt release.

We will also briefly touch on the mechanism UniProt has set up to enable researchers to run these automated annotation systems on their own protein datasets.

Who is this course for?
This webinar is for scientists and bioinformaticians with an interest in functional annotation of protein sequences.

Outcomes
By the end of the webinar you will be able to:

Recall the role of UniProt's two main automated annotation systems
Describe how UniRule and ARBA work
Get started using these automated annotation systems

This quick tour provides a brief introduction to EMBL-EBI’s resource of mathematical models of biological/biomedical systems.

By the end of the course you will be able to:
Identify how mathematical models are used in investigating the mechanism underlying biological systems and why do we need them.
Explore the content, features, functionality and use of BioModels
Determine where to find out more about BioModels Database

This quick tour provides a brief introduction to BioSamples data resource, the EMBL-EBI resource that stores and supplies descriptions and metadata about biological samples.

By the end of the course you will be able to:
Describe the role of BioSamples
Navigate the BioSamples website
Describe where to find out more about BioSamples

BioSamples is the EMBL-EBI archive which records and supplies metadata about biological samples and connects sample records across EBI databases to the corresponding experimental data. BioSamples aims to improve metadata quality through ontology annotation, metadata curation, data validation and certification.

In this webinar, we will briefly introduce BioSamples and highlight specific use cases from current collaborations and features deployed to increase FAIRness (Findability, Accessibility, Interoperability, Reusability) of the data.

Ongoing collaboration with major consortia rely on and drive addition of new features to BioSamples:

Ability to walk an ontology hierarchy such as disease for the Global Alliance for Genomics and Health (GA4GH)
Synthetic dataset and linking to human controlled access data for the Common Infrastructure for National Cohorts in Europe, Canada, and Africa (CINECA)
Metrics and automated processes for FAIRplus
Who is this course for?
Biologists and bioinformaticians who are interested in sample metadata and FAIR practices.

Outcomes
By the end of the webinar you will be able to:

Describe the role of BioSamples
Recall use cases that increase FAIRness of data

The goal of the BioStudies database is to facilitate transparency and reproducibility of research by aggregating all the outputs of a study (a ‘data package’) in a single place. A data package consists of the overall biological study description (metadata), links to data generated in this study in key community databases at EMBL-EBI and elsewhere, as well as “orphan data” such as supplemental data. The database can accept a wide range of types of studies described via a simple format and does not impose minimum requirements outside those agreed by the respective community.

In this webinar we will introduce the basic principles of BioStudies, explore data access and data deposition interfaces, as well as briefly consider some more advanced topics such as use of BioStudies for data sharing in an ongoing project.

Who is this course for?
No prior knowledge of bioinformatics is required, but an undergraduate level knowledge of biology would be useful.

This exercise contains two interrelated modules that introduce students to modern biological techniques in the area of Bioinformatics, which is the application of computer technology to the management of biological information. The need for Bioinformatics has arisen from the recent explosion of publicly available genomic information, such as that resulting from the Human Genome Project.

On its own, a huge DNA sequence is a meaningless pile of data — so, how do biologists figure out what it means? They turn to the power of bioinformatics! In this episode, we’ll learn what bioinformatics is, how it works, and how scientists have used it to better understand everything from evolution to a viral epidemic.
Chapters:
Introduction: Pizza Data
Bioinformatics
Algorithms
The Human Genetic Code
The BRCA1 Gene
Transcriptomes
The Zika Virus
Bioinformatics & Programming
Review & Credits
Credits

This course is a continuation of Bioinformatics I. Topics include gene expression, microarrays, next- generation sequencing methods, RNA-seq, large genomic projects, protein structure and stability, protein folding, and computational structure prediction of proteins; proteomics; and protein-nucleic acid interactions. The lab component includes R-based statistical data analysis on large datasets, introduction to big data analysis tools, protein visualization software, internet-based tools and high-level programming languages.

This interdisciplinary course provides a hands-on approach to students in the topics of bioinformatics and proteomics. Lectures and labs cover sequence analysis, microarray expression analysis, Bayesian methods, control theory, scale-free networks, and biotechnology applications. Designed for those with a computational and/or engineering background, it will include current real-world examples, actual implementations, and engineering design issues. Where applicable, engineering issues from signal processing, network theory, machine learning, robotics and other domains will be expounded upon.

What is bioinformatics and where does it fit with bench-based life science research? Find out more about bioinformatics tools and resources that are available and how you can start to apply them in your research.

By the end of the course you will be able to:
Assess the role of bioinformatics in molecular science.
Describe the key features of primary and secondary databases.
List strategies for describing data consistently.
Identify some of the different types of data analysis that can be applied to solving biological problems.

The EMBL-EBI Job Dispatcher framework (https://www.ebi.ac.uk/services) provides free access to several core Bioinformatics tools and related data, via the web or programmatically via Web Services APIs. In this webinar, we will give an overview of the Web Interface and RESTful API. We will then explore how to use our Sample Clients to perform various bioinformatics analysis, and how we can leverage CWL to run analysis workflows.

Who is this course for?
This webinar is aimed at individuals at all levels of expertise, particularly those interested in learning how to use our Web Services programmatically.

This course provides an introduction to structural biology and related resources at EMBL-EBI.

By the end of the course you will be able to:
Describe what biomacromolecular structures are
List common methods for obtaining biomacromolecular structure data
Identify the protein structure resources which are available at the EBI

Analyzes computational needs of clinical medicine reviews systems and approaches that have been used to support those needs, and the relationship between clinical data and gene and protein measurements. Topics: the nature of clinical data; architecture and design of healthcare information systems; privacy and security issues; medical expertsystems; introduction to bioinformatics. Case studies and guest lectures describe contemporary systems and research projects. Term project using large clinical and genomic data sets integrates classroom topics.