Webinars

Explore nanopore sequencing approaches for identifying and characterising fungal pathogens. The webinar compares isolate whole-genome sequencing for strain typing and outbreak investigation with targeted ITS sequencing directly from samples. Speakers discuss workflow validation, implementation and BugSeq analysis, followed by live questions and answers.

Two sessions are available on October 28: 07:00 GMT (15:00 SGT / 18:00 AEDT) and 16:00 GMT (09:00 PDT / 12:00 EDT). Select your preferred session on the registration form.

The work presented is research-focused; Oxford Nanopore notes that the products discussed are not intended for diagnostic procedures.

Explore nanopore sequencing approaches for identifying and characterising fungal pathogens. The webinar compares isolate whole-genome sequencing for strain typing and outbreak investigation with targeted ITS sequencing directly from samples. Speakers discuss workflow validation, implementation and BugSeq analysis, followed by live questions and answers.

Two sessions are available on October 28: 07:00 GMT (15:00 SGT / 18:00 AEDT) and 16:00 GMT (09:00 PDT / 12:00 EDT). Select your preferred session on the registration form.

The work presented is research-focused; Oxford Nanopore notes that the products discussed are not intended for diagnostic procedures.

In this webinar we will talk about:

• Functional metagenomics and directed evolution in microfluidic droplets
• Microfluidic droplet screening – Engineering solutions for ultra–high–throughout analysis: This part of the webinar will cover the practicalities of adapting droplet screening for enzyme discovery and describe case studies for applications.

This event is part of the broader "Exploring and harnessing marine microbiomes for a sustainable blue bioeconomy" webinar series. You can follow the link for more information about the series and its webinars. The organisation of this series has been funded by UKRI, Horizon Europe, and Swiss Confederation.

Who is this course for?

This webinar is suitable for:

• Anyone from academia and industry who conduct research, utilise discovery platforms and develop applications in aquaculture, agriculture and pharmaceuticals
• Anyone from research infrastructures who manage marine sampling and scientific data, and who develop discovery platforms

Outcomes

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

• Identify the different droplet formats, used for high-throughput screening
• Explain how microfluidics can be used to screen for enzyme activity at ultra–high–throughput (>1,000/ sec)

MGnify is the microbiome analysis resource of EMBL-EBI. It provides standardised, versioned analysis pipelines for the taxonomic and functional characterisation of microbiome samples, and easy access to already analysed datasets. By bringing together public and user-submitted datasets, it allows users to browse studies, samples, sequencing runs, analyses and results, with data download options available as well as programmatic access to support further data exploration. In this webinar, we will provide a general introduction to MGnify and the data types it hosts. The session will also act as an introduction to following webinars in the series, where we will dive deeper into different kinds of data and resources available at MGnify.

This event is part of the webinar series “Making sense of metagenomics data with MGnify”. You can follow the link for more information about the series and its webinars.

Who is this course for?

This webinar is suitable for life science students, researchers and other learners interested in microbial communities and sequence data. Basic familiarity with DNA sequencing is helpful, but no specialist bioinformatics or coding experience is required to follow the programme.

Outcomes

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

• Explain what MGnify offers as a resource for microbiome data analysis, discovery and exploration.
• Describe the main data types in the series programme: amplicons, raw reads, assemblies, genomes and proteins.
• Describe how MGnify links studies and samples to analyses, visualisations, and downloads.

Metagenomic raw reads are the direct, raw product of shotgun sequencing a community or environmental sample. They are the starting point for several kinds of analysis: reads can be assembled into longer contigs, compared or mapped against references, or taken into other downstream workflows. This session focuses on what information MGnify can help extract from sequencing reads directly, without first assembling them.

We will look at how MGnify presents taxonomic and functional profiles, and how to find results through the website, API and MGnipy, its Python client. This session will lay the basis for the upcoming sessions about assembly and MAGs generation, and underline the pros and cons of using read-level evidence versus more complex approaches.

This event is part of the webinar series “Making sense of metagenomics data with MGnify”. You can follow the link for more information about the series and its webinars.

Who is this course for?

This webinar is suitable for learners with a basic understanding of DNA sequencing who want to explore whole-community metagenomic data. No coding experience is needed for the website and search demonstration. The API and MGnipy examples will also suit learners interested in programmatic access.

Outcomes

By the end of this webinar, you will be able to:

• Explain what metagenomic raw reads are and how they differ from assemblies.
• Describe the taxonomic and functional profiles available from MGnify raw-read analyses.
• Find analysis results through the MGnify website and identify programmatic routes through the API and MGnipy.
• Use a genome search against public metagenomes to investigate where related sequence occurs, and interpret matches alongside sample metadata

Assembly combines overlapping sequencing reads into longer sequences called contigs. It offers a different view of a community from read-level profiling: contigs can preserve longer stretches of genomic context, and the quality of their assembly is evaluated on the basis of different criteria, as it may depend on sequencing depth, community complexity, and the sequencing technology used. We will introduce the foundations of short-read and long-read assembly and discuss the trade-offs that shape the resulting contigs.

We will then tour through the MGnify’s assembly pipeline and methods for the quality assessment of the results. In addition, we will explore how sequence features are annotated, including taxonomic and functional information, and use the contig viewer visualisation on the MGnify website to inspect annotations in their genomic neighbourhood. A worked example will show how a biological question can guide exploration of an assembly, while keeping in mind that individual contigs may be incomplete and do not necessarily represent a whole genome.

This event is part of the webinar series “Making sense of metagenomics data with MGnify”. You can follow the link for more information about the series and its webinars.

Who is this course for?

This webinar is suitable for life science students and researchers who work with, or want to understand, metagenomic assemblies. A basic understanding of sequencing, and having attended the raw reads session would be helpful. No prior experience with assembly software or bioinformatics is required.

Outcomes

By the end of this webinar, you will be able to:

• Explain how sequencing reads are assembled into contigs and describe the main differences between short-read and long-read approaches.
• Interpret basic indicators of assembly quality and recognise how assembly limitations affect biological conclusions.
• Describe the kinds of taxonomic and functional annotations available for MGnify assembly analyses.
• Navigate the MGnify Contig Viewer to inspect contigs, predicted features and their annotations.

Metagenome-assembled genomes (MAGs) are reconstructed from sequence fragments recovered from a microbial community. They can provide genomic insight into organisms that are difficult to culture, but their completeness, contamination and ability to represent a single population all need careful consideration. This session introduces the benefits and challenges of using MAGs to study microbiomes.

We will explore how MGnify generates MAGs and organises both MAGs and isolate genomes into publicly available biome-specific catalogues. Examples will show how to browse genome taxonomy and annotations, compare a user-provided genome with catalogue genomes, and how to use read-level evidence to guide follow-up checks and improvements for a genome. The session closes with the route for contributing reads, assemblies, bins or MAGs to ENA using nf-core/seqsubmit, and how to update genome catalogues with new members.

This event is part of the webinar series “Making sense of metagenomics data with MGnify”. You can follow the link for more information about the series and its webinars.

Who is this course for?

This webinar is suitable for learners with an interest in microbial ecology, comparative genomics or genome-resolved metagenomics. Concepts covered in the previous two sessions are useful, but the session is designed to introduce MAGs and catalogue exploration without requiring specialist bioinformatics experience.

Outcomes

By the end of this webinar, you will be able to:

• Define a MAG and explain key benefits and limitations of using MAGs in microbiome research.
• Describe how MGnify genome catalogues are built, quality-filtered and updated, and identify the main types of genome information they provide.
• Use MGnify catalogue pages and genome search tools to place a genome in taxonomic and functional context.
• Explain how Branchwater can connect genome sequences to public metagenomes, and how those results can motivate follow-up analysis.
• Identify the role of nf-core/seqsubmit in submitting reads, assemblies, bins and MAGs to ENA for potential inclusion in future catalogue updates.

overview

Artificial intelligence is transforming the way we understand and engineer biology. Recent advances in genome-scale foundation models are enabling researchers to predict gene regulation, interpret genetic variants, and design functional DNA sequences with unprecedented accuracy. In this webinar, Ben Fishman from Genomic Intelligence will introduce DNA language models and demonstrate how they are addressing some of the most important challenges in modern genomics. The session will explore real-world applications in biomedicine and biotechnology, discuss current limitations of these models, and examine how AI is reshaping biological research. Participants will also receive a live introduction to the Genomic Intelligence Platform, including access through the web application, API, and MCP server. The webinar will conclude with a discussion on integrating genome-scale AI models into modern agentic research environments such as Codex, Claude for Science, and Phylo to accelerate biological discovery and programmable biology workflows.

Learning Outcomes

Fundamentals of DNA language models and genome-scale AI Predicting gene regulation using foundation models Interpreting genetic variants with AI Designing functional DNA sequences Applications in biomedicine and biotechnology Current capabilities and limitations of genome-scale AI Using the Genomic Intelligence Platform via the web interface, API, and MCP server Integrating genomic AI with agentic systems, including Codex, Claude for Science, and Phylo

The MGnify Proteins database aggregates 5.7 billion non-redundant protein sequences from the outputs of the MGnify Assembly Analysis Pipeline. The database connects these sequences to the metadata of the assemblies they originate from. These connections create a resource that can be exploited not only for its massive sequence space, but also for the insight it offers into how sequences relate to their biomes of origin, among other things.

In this session, you will learn how to access the data for the latest MGnify Proteins release in three different ways. First, for a sequence of interest, we will show how to use the HMMER Web sequence search tool to retrieve sequences with similar sequence profiles. The resulting list of sequences will then be explored in detail using their respective Protein Landing Pages. Finally, for larger and programmatic access of MGnify Proteins, you will see three examples of how the Parquet files that make up the release can be queried using modern tools like DuckDB.

This event is part of the webinar series “Making sense of metagenomics data with MGnify”. You can follow the link for more information about the series and its webinars.

Who is this course for?

This webinar is suitable for learners interested in using MGnify Proteins. Those with programmatic access needs could benefit from basic SQL knowledge for the final learning outcome.

Outcomes

By the end of this webinar, you will be able to:

• How MGnify Proteins is generated from MGnify analyses
• How to use HMMER Web to search for sequences with similar sequence profiles in MGnify Proteins
• How to explore the Protein Landing Pages to gather information about different MGnify Protein sequences
• How to perform basic querying of the MGnify Proteins release Parquet files for larger-scale data retrieval

In the previous webinars of the series, we have explored how to identify species and retrieve genomes at a very detailed level, and delved into functional annotation and the protein space. Here, we will take a step back and ask ourselves how to have a more general overview of the organisms at play in a microbial community. What does the population look like? Is a microbe of interest present or absent under certain conditions?

The MGnify amplicon analysis pipeline creates taxonomic profiles of metabarcoding datasets against the most popular rRNA databases like SILVA. This session will provide an overview of how 16S, 18S. LSU and ITS markers help profile different microbial groups,and how MGnify processes amplicon data and presents taxonomic results. Finally, a guided exploration of a public MGnify study will show how to use bacterial profiles together with sample metadata to infer population changes.

This event is part of the webinar series “Making sense of metagenomics data with MGnify”. You can follow the link for more information about the series and its webinars.

Who is this course for?

This webinar is suitable for life science students, researchers, and other learners who know basic DNA sequencing concepts, interested in learning more about how to explore microbial communities as a whole.

Outcomes

By the end, learners should be able to:

• Explain how metabarcoding uses marker-gene amplicons to profile microbial communities
• Understand which ribosomal regions are targeted for metabarcoding (16S vs 18S, LSU, ITS), and which kingdoms are usually targeted (bacteria, archaea, fungi)
• Describe the main steps in MGnify’s amplicon analysis and name a few limitations of the resulting profiles
• Explore a public MGnify analysis and use its taxonomic results to investigate a biological question

Bacteriophages, viruses that only infect bacteria, are Earth’s most abundant and diverse biological entities. Their genomes represent the largest untapped source of novel enzymes that function under extreme conditions. Among these, endolysins (phage-encoded peptidoglycan hydrolases) are of huge interest as eco-friendly antimicrobial agents. Endolysins can be utilised in the food, agricultural and sanitation industries as alternatives to harsh chemicals and detergents, owing to their antimicrobial activities over a range of conditions. New cold-adapted endolysins offer the potential of energy-saving low-temperature cleaning, whilst thermophilic variants have potential use in fermentation, food processing and as low-resistance alternatives to antibiotics.

In this webinar I will discuss research from my PhD project, in which I combined AlphaFold and other predictive methods with biophysical and experimental techniques to investigate putative cold-adapted and thermophilic endolysins. Sequences of interest were obtained from metagenomic sources of Icelandic hot springs and Arctic seawater. I will highlight how these investigations revealed unexpected and novel structural features within the enzyme class, the evolutionary implications of this, and the potential for biotechnological applications and rational design.

Who is this course for?

This webinar is intended for researchers, graduate students, and professionals in microbiology, metagenomics, bioinformatics, structural biology, and biotechnology interested in the discovery and characterisation of novel antimicrobial enzymes and the use of AlphaFold to investigate their structure and function.

Outcomes

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

• Describe how metagenomic mining, sequence analysis, and structural prediction can be combined to identify candidate antimicrobial enzymes from extreme environments.
• Explain how AlphaFold predictions can be integrated with experimental approaches, including X-ray crystallography and biochemical characterisation, to investigate novel enzyme structures.
• Interpret how structural features can provide insights into the function and environmental adaptation of extremophilic endolysins.