This course explores the ethical, legal and social implications (ELSI) of biomedical data sharing. The material will introduce the reasons why we want to share data, the benefits it can bring, and the challenges of doing so. It will present ideas for best practice and cover resources that provide guidance and advice for sharing data.

By the end of the course you will be able to:
Explain the benefits of sharing data
Explain the challenges of sharing data
Describe some best practices around data sharing

Most researchers know that data management is essential for getting the most out of your data. But what exactly is it and how do you ensure that you’re managing your data well? This course, focused around a series of webinars, introduces key concepts in data management and how to apply them in your research.

By the end of the course you will be able to:
Describe the data management cycle
Discuss benefits and challenges of data sharing
Explain what happens to data after it is shared
Identify appropriate data repositories and their submission requirements
Describe how ontologies and standards are used to annotate biological data
Identify appropriate resources and tools for data management

This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"Microbiomes are more than just prokaryotes and viruses; they also contain important eukaryotes, including fungi and protists. However, eukaryotes are difficult to study using ‘shotgun’ metagenomics, as their signal is often overwhelmed by the prokaryotes. Some methods use eukaryote-specific marker genes, but they can’t detect eukaryotes that aren’t in the reference marker gene set, and such methods are not compatible with web-based tools for downstream analysis. But CORRAL (Clustering Of Related Reference ALignments) is designed to close those gaps. CORRAL identifies eukaryotes in metagenomic data based on alignments to eukaryote-specific marker genes and Markov clustering. It can detect microbial eukaryotes that are not included in the marker gene reference set. The process is even automated and can be carried out at scale. A recent paper demonstrates CORRAL’s sensitivity and accuracy with simulated datasets, mock community standards, and human microbiome datasets..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

The COVID-19 Data Portal was launched in April 2020 to bring together relevant datasets for sharing and analysis in an effort to accelerate coronavirus research. This course provides a short overview of what the COVID-19 Data Portal is, how to access it and how to submit data.

By the end of the course you will be able to:
Explain the purpose of the COVID-19 Data Portal
Describe what data is accessible through the COVID-19 Data Portal
Know where to submit COVID-related data

This quick tour provides a brief introduction to the Cellular Microscopy Phenotype Ontology (CMPO). It covers the scientific principles that led to the creation of this ontology and how it can be used.

By the end of the course you will be able to:
Describe the role of CMPO
Search and browse the ontology and use it to annotate data

This quick tour provides a brief introduction to ChEBI, the EBI's Chemical Entities of Biological Interest database, which focuses on 'small' chemical compounds.

By the end of the course you will be able to:
explain what the ChEBI Database is and how you can use it to access chemical compounds of interest
demonstrate where to find out more about ChEBI

Chemical Entities of Biological Interest (ChEBI) is a user-friendly online chemical dictionary that focuses on the nomenclature, structure, and biological properties of 'small' molecules that may be encountered by anyone working in molecular biology. This course will show you what kind of information is available in ChEBI and how to access and query the database.

By the end of the course you will be able to:
Evaluate what ChEBI is and how it can be useful in your day-to-day research
Know what data are stored and how ChEBI classifies molecules (understanding ChEBI ontology)
Be able to carry out different types of search

This quick tour provides a brief introduction to ChEMBL, the EMBL-EBI's chemogenomics resource.

By the end of the course you will be able to:
Describe what ChEMBL is and how it can help you to understand the interactions between drugs or drug-like molecules and their targets
Recall where to find out more about ChEMBL

This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"The development of long-read sequencing has allowed for the generation of more complete and contiguous genomes in metagenomics studies. However, long-reads are more prone to sequencing errors than short-reads, and these errors can end up incorporated in the draft genomes. Combining short- and long-reads can overcome such errors, but is computationally taxing. To avoid this, researchers developed the ‘Hierarchical Clustering Based Hybrid Assembly (HCBHA) approach.’ This approach first groups the long- and short-reads into candidate bacterial haplotypes and then assembles each group separately, which reduces the computational demand . Researchers tested this framework on a microbiome from activated sludge, an important part of wastewater treatment. The highly complex microbiomes found in activated sludge remove pollutants from wastewater..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"Osteoarthritis is the most common form of joint disease, affecting hundreds of millions of people worldwide. One promising therapeutic target is TGF-β signaling. Studies have shown that blocking this signaling pathway can slow the progression of osteoarthritis. The problem is that TGF-β signaling is also critical for repairing the cartilage cells that are degraded in osteoarthritis. To help separate the bad from the good, researchers recently examined the genetic blueprints that control TGF-β signaling. They discovered a key player in circPhf21a, a type of rare genetic material known as circular RNA. Initially believed to be misshapen RNA, circular RNA is being revealed as an important mediator of disease. In the current study, the team found that overexpression of circPhf21a led to the growth of fewer-than-normal cartilage cells in mice. And in mice with osteoarthritis, levels of circPhf21a were found to be significantly increased..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"High-quality reference genomes are needed to understand the physiology and function of uncultured microbes in complex ecosystems. Metagenomics has been an incredibly useful tool for studying microbial communities, but assigning sequence assemblies accurately to genomes is difficult in microbial species or strains that lack a reference genome. These 'consensus genomes' have lower resolution than those generated from cultured isolates. Combining single-cell genomics with metagenomics may allow us to overcome these methodological weaknesses. Thus, researchers recently developed a framework called SMAGLinker, which integrates single-cell genomes from microfluidic droplets and uses them as guides for metagenome assembly. Compared to metagenomics alone, SMAGLinker showed more precise contig binning and higher recovery rates of rRNA and plasmids in a mock microbial community. In human gut and skin microbiota samples, SMAGLinker returned more genomes than the conventional metagenomics frameworks..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

This quick tour provides a brief introduction to EMBL-EBI's Complex Portal: a manually curated, encyclopedic resource of macromolecular complexes from a number of key model organisms.

By the end of the course you will be able to:
Outline the scope of the available data in Complex Portal
Describe how to search for macromolecular complexes of interest
List manual and computational methods for downloading Complex data
Outline how to submit curation requests for Complexes
Identify sources of more information about Complex Portal

This webinar will present how the research community can contribute both literature references and annotation to the UniProt database of protein sequence and function (www.uniprot.org).

First, we will provide an overview of the resource and then we will focus on describing the functionality to add publications and knowledge to protein entries, including a demo.

In this webinar you will also learn how your domain knowledge contribution improves the resource for the general community, and how it can be used as an alternative metric of your research output given that UniProt uses ORCID, a unique identifier for each researcher, as a mechanism for user validation and credit for these contributions.

Who is this course for?
This webinar is aimed at scientists, clinicians, biocurators and students interested in protein related research. No knowledge of programming is required.

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

explain how the research community can contribute to UniProt
add publications and knowledge to protein entries
describe how UniProt can be used as an alternative metric of research output

This webinar will demonstrate how to create more complex queries by combining the PDBe search API with numerous other calls. By introducing specific case studies, we will highlight the scope of PDBe programmatic access.

This webinar is part of a 6-part PDBe API webinar series, introducing different levels of programmatic access at PDBe.The series will range from basic data retrieval and search using the PDBe API to more advanced features, including access and reuse of PDBe data visualisation components.

Who is this course for?
This webinar is open to anyone who is interested in learning about the programmatic access of PDBe.

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

Create complex queries by combining the PDBe search API with numerous other calls

In this webinar we will go through the basic principles of designing scientific figures to communicate our research findings. We will focus on how we can utilise colour effectively and help our audience make accurate quantitative judgements by taking advantage of fundamental principles of human perception. We will also discuss strategies for visualising complex datasets.

The webinar is based on the articles in data visualisation which were published in the Points of View column in Nature Methods with additional material from publications by Edward Tufte, Tamara Munzner and other leading researchers on data visualisation.

Who is this course for?
This webinar is aimed at scientists who wish to learn more about the principles of data visualisation. No prior knowledge of bioinformatics is required, but an undergraduate level knowledge of biology would be useful.

This webinar will introduce some of the data visualisations available from PDBe, how to add these to your own website and how to customise them for your own requirements. There will also be specific case studies that demonstrate how these visualisations can be used and implemented.

This webinar is part of a 6-part PDBe API webinar series, introducing different levels of programmatic access at PDBe.The series will range from basic data retrieval and search using the PDBe API to more advanced features, including access and reuse of PDBe data visualisation components.

Who is this course for?
This webinar is open to anyone who is interested in learning about the programmatic access of PDBe.

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

Explore the function of data visualisation tools available at PDBe
Customise data visualisation tools according to your own requirements

This material introduces Linux File System structures and demonstrates how to use commands to communicate with the operating system through a Terminal program. Basic program structures and system() function of Perl are discussed. A brief introduction to gene-sequencing terminology and file formats are given.

This material introduces the AWS console interface, describes how to create an instance on AWS with the VMI provided, connect to that machine instance using the SSH protocol. Once connected, it requires the students to write a script to enter the data folder, which includes gene-sequencing input files and print the first five line of each file remotely. The same exercise can be applied if the VMI is installed on a local machine using virtualization software (e.g. Oracle VirtualBox). In this case, the Terminal program of the VMI can be used to do the exercise.

This manual guides the instructor to combine the partial files of the virtual machine image and construct sequencer.ova file. It is accompanied by the partial files of the virtual machine image.

This material briefly reintroduces the DNA double Helix structure, explains SNP and INDEL mutations in genes and describes FASTA, FASTQ, BAM and VCF file formats. It also explains the index creation, alignment, sorting, marking duplicates and variant calling steps of a simple preprocessing workflow and how to write a Perl script to automate the execution of these steps on a Virtual Machine Image.