Computational Biology

This EMBO workshop brings experimental and computational researchers together around molecular mechanisms of adaptation, evolutionary dynamics, microbial communities, symbiosis, biodiversity, and cell-environment interactions.

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.

The webinar compares prefusion stabilization of vaccine antigens with epitope scaffolding on non-antigen protein backbones. It examines the advantages and limitations of each computational, structure-based vaccine design strategy.

This conference connects Latin American researchers using computation to investigate biological questions. Its programme combines invited lectures, contributed research, tutorials and networking across biomedical omics, microbial communities, comparative and population genomics, molecular sequences and structures, systems biology and networks. It brings together biology, computing, mathematics, statistics and medicine, while introducing scientists new to bioinformatics to tools for analysing biological data. Published keynotes examine AI integration of genomic and phenotypic data for antimicrobial resistance, diagnostics and biomarkers; inclusive genomic studies and biobanks addressing Latin American ancestry and health; network models of non-coding RNA and host-pathogen interactions for drug repurposing and precision medicine; and AI that moves from environmental sensing toward ecological explanation and conservation decisions. Keynote schedule, in Peru Time (PET, UTC−05:00): 11 November, 09:00–10:00 José Arturo Molina Mora (University of Costa Rica) and 16:30–17:30 Andrés Moreno-Estrada (Cinvestav); 12 November, 09:00–10:00 Deisy Morselli Gysi (Federal University of Paraná) and 16:30–17:30 Layla Hirsh Martinez (Pontificia Universidad Católica del Perú); 13 November, 11:00–12:00 Tanya Berger-Wolf (Ohio State University). These are the published keynote sessions; consult the organizer for other sessions. Attend in person at the Universidad de Ingeniería y Tecnología auditorium, Jr. Medrano Silva 165, Barranco, Lima, Peru, or virtually through the conference platform. The auditorium seats 320. Public registration accepts members and nonmembers. Current individual fees are USD 105–255 in person or USD 40–90 virtually, depending on career category and membership. Tutorials cost an additional USD 25 for members or USD 35 for nonmembers; the closing party costs USD 20. In-person fees include breaks and lunch. Both formats include virtual-platform and recorded-session access. Oral presenters are normally expected in person; remote presentation requires an approved waiver for qualifying barriers.

Michelle M. Li examines how computational analyses can preserve the biological context of a proposed treatment, including cell type, disease state, genetic background and patient characteristics. She introduces Medea, an AI system that combines biological software, predictive models and literature retrieval while checking intermediate steps and reconciling evidence. The seminar presents evaluations involving cell-specific target selection, cancer-cell synthetic lethality and immunotherapy response. A separate yeast experiment tests predictions against previously unpublished measurements of gene-pair interactions under DNA-damaging treatments. The research addresses whether an agent can transfer useful evidence between contexts while recognizing when that transfer is unsupported. Reported comparisons cover predictive performance, computational failures and the ability to abstain. This recording retains the original seminar date.

Jiaqi Zhang examines how computational models can learn the effects of genetic interventions from single-cell experiments. Such experiments reveal causal relationships, but their high-dimensional measurements are costly to collect and difficult to interpret. The seminar connects identifiable causal representations with a predictive method for previously unseen perturbations. The approach incorporates prior biological knowledge and changes in data distributions to estimate responses at individual-cell resolution. It also uses predictions to guide subsequent experiments. An application identifies and experimentally validates previously unknown T-cell regulators with potential relevance to cancer immunotherapy. The recording follows the original July seminar; the series lists Zhang at MIT, while the recording biography describes her incoming Columbia appointment.

EMBL-EBI seeks a Bioinformatics Developer for DECIPHER, a platform supporting rare-disease research and clinical interpretation of genetic variation. The developer will evaluate and integrate genomic and phenotype resources, deploy analysis tools, design database structures and interfaces, investigate data problems and work with clinical and research collaborators. The role is based in Hinxton with hybrid working and may be full time or 80% time. The advert gives a closing date of 8 October 2026 at 23:59 CET.

Develop reproducible bioinformatics analyses for adipose-tissue research in the Spalding laboratory. Work with RNA, single-cell and small-RNA datasets to investigate senescence, inflammation and metabolism, and integrate computational findings with laboratory experiments. Responsibilities include analysis workflows and clear communication with experimental researchers. This is a permanent, full-time position, with applications due 13 October 2026.

Develop ARCA, a foundation model that combines crop microbiome, genome and environmental data to predict microbial community behaviour and support crop resilience. The NOAH consortium connects model development with greenhouse and field experiments. This 36–40-hour postdoctoral appointment starts in January 2027, initially for one year with a three-year extension after positive evaluation. Apply with a CV, motivation letter, two referee contacts and evidence of PhD completion or a planned defence.

Fully funded doctoral studentship in the Ali Lab at the Cancer Research UK Cambridge Institute, starting in October 2027. The project combines spatial multiomics with deep learning to identify treatment-response biomarkers in breast cancer. It will analyse large multimodal datasets from observational cohorts and clinical trials, using representation and cross-modal learning to study target expression, tissue architecture and tumour heterogeneity. Training spans quantitative pathology, multiplexed imaging and predictive modelling.

Develop reproducible bioinformatics analyses for adipose-tissue research in the Spalding laboratory. Work with RNA, single-cell and small-RNA datasets to investigate senescence, inflammation and metabolism, and integrate computational findings with laboratory experiments. Responsibilities include analysis workflows and clear communication with experimental researchers. This is a permanent, full-time position, with applications due 13 October 2026.

Join the Hadjab laboratory to investigate chronic pain and headache using single-cell RNA and chromatin-accessibility data, spatial transcriptomics and integration across datasets. The scholarship supports postdoctoral research in Solna, connecting computational methods with molecular and cellular neuroscience. The award is intended for eligible researchers coming from outside Sweden and is tax-exempt; no amount is advertised. Scholarships are normally set for twelve months at a time, up to two years. Apply by 26 October 2026.

MIT Biology Colloquium Series talk by Peter Koo (Cold Spring Harbor Laboratory), hosted by Yunha Hwang, on using AI to learn the gene regulatory code.

Convergence Seminar by Alexis Battle, PhD (Wu and Zhang Professor of Biomedical Engineering and Computer Science, Johns Hopkins University), on computational and machine-learning approaches for analyzing how genetic variation impacts gene regulation and disease, including noncoding sequences and rare variants.