Computational Biology seminars

This webinar uses research on Chagas disease to explain how predicted protein structures can support drug discovery when experimental structures are unavailable. In the example study, AlphaFold models of Trypanosoma cruzi proteins supported a virtual screen of roughly 30,000 compounds; subsequent experiments identified antiparasitic activity in two approved drugs. The session introduces AlphaFold confidence measures and ways to obtain models, then follows a screening workflow through binding-pocket prediction, chemical-library selection, docking, and interpretation of results. It discusses difficulties encountered when docking against predicted structures and considerations for adapting the workflow to other targets. The material is intended for doctoral students, early-career researchers, and other drug-discovery professionals.

Jan Kosinski explains how AlphaFold-style methods predict protein complexes and why their reliance on evolutionary information makes interactions between host and pathogen proteins especially difficult. The talk reviews large-scale studies, interpreting both successful predictions and failures rather than treating reported success rates as universal performance. It then examines ways to improve predictions through broader sampling, altered sequence alignments and experimental restraints, including crosslinking mass spectrometry, with influenza A virus as a worked research example. The session is suitable for students and researchers interested in host-pathogen interactions and structural bioinformatics; basic knowledge of protein structures and sequence alignments is useful, but prior AlphaFold experience is unnecessary.

This webinar examines reconstruction and use of marine metagenome-assembled genomes. The first part introduces the Ocean Microbiomics Database as a standardized resource for prokaryotic genome-resolved analysis, including co-abundance-based reconstruction, contextual metadata, and relationships between ecological patterns and microbial genomes. The second part considers why eukaryotic genomes are harder to recover: their complexity, low abundance, and limited markers and reference sequences complicate assembly and classification. Participants will compare reconstruction approaches, explore the database, and consider tools and steps for recovering eukaryotic genomes. The session serves academic and industrial researchers developing marine-microbiome applications and infrastructure teams managing samples, data, and discovery resources.

Scientific computing has environmental impacts that extend beyond the growing use of artificial intelligence. This seminar examines how research computing affects the environment, how researchers can measure and reduce those effects, and how funders are responding. It also asks whether efficiency alone provides an adequate strategy. The speakers introduce Green DiSC, a certification scheme for sustainable computing, and the Environmentally Sustainable Computational Science community forum. The discussion connects practical choices in computational research with community approaches to sustainability and concludes with questions. It is suitable for researchers and software developers without prior knowledge of sustainable computing.

Tim Ebbels presents interpretable machine-learning models for metabolomics and multi-omics using pathway and chemical-class scores. Sparse coverage of the metabolome and uncertain annotations make conventional results difficult to interpret; pathway-based features aim to connect model output directly to biological function. The webinar examines applications from multi-assay mass spectrometry and multi-omics integration to single-cell and mass-spectrometry imaging, discusses methodological challenges and attempts to resolve them, and demonstrates how these approaches can clarify complex biological signals. Online via Zoom. Free for interested life scientists and bioinformaticians, with advance registration required through the Australian BioCommons event page. Tuesday 13 October, 16:00–17:00 AEDT (Australia/Melbourne), equivalent to 05:00–06:00 UTC. The event is subject to the BioCommons Code of Conduct and may be recorded.

This webinar explains how researchers can retrieve and analyse protein information using UniProt. It demonstrates advanced queries, BLAST searches, peptide searches, and multiple-sequence alignments, including how to navigate outputs and use functional annotations to interpret them. It also discusses how identifiers, ontologies, and controlled vocabularies organize biological knowledge, and how identifier mapping connects resources. The session is suitable for scientists at any career stage who want to use UniProt or extend their existing skills; undergraduate-level biology knowledge is helpful.

José Molina Mora presents an integrative study of the core stress-response mechanisms, or perturbome, of Escherichia coli, Pseudomonas aeruginosa and Staphylococcus aureus. Transcriptomic data are analysed using machine learning, systems biology, functional enrichment and ortholog comparisons to prioritise stress-associated genes. Experimentally determined protein structures are combined with AlphaFold predictions where structural data are missing. Molecular docking and further computational analyses then identify preliminary compounds and conditions that might inhibit selected targets. These results are a proof of concept awaiting experimental validation. The talk connects gene-expression analysis with structural modelling for antimicrobial research and is aimed at researchers, graduate students and professionals in microbiology, bioinformatics and related biomedical fields.

This webinar explores computational and structure-based vaccine design, comparing prefusion stabilisation of vaccine antigens with epitope scaffolding onto non-antigen protein backbones. It discusses the advantages and limitations of both strategies. No background in computational protein design is required; familiarity with vaccine antigens and viral glycoproteins is helpful. Free online webinar; advance registration and details: https://www.ebi.ac.uk/training/events/strategies-computational-vaccine-design-prefusion-stabilisation-epitope-focussing/

Interpreting human missense variants requires connecting genomic coordinates with protein sequences, structures and functional evidence. ProtVar integrates annotations and predictions from UniProt, Ensembl, PDBe, Open Targets and AlphaFoldDB, extending variant lookup to discovery across more than 500 million potential missense variants. This seminar demonstrates natural-language searches using diseases, pathways and drug responses, multi-criteria filtering, structural visualisation and data export. Participants will learn to prioritise variants, interpret their structural and functional effects, and retrieve data through web downloads or the REST API. The session serves geneticists, drug-discovery researchers and computational biologists; undergraduate molecular biology and genetics are recommended.