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BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20260522T100000
DTEND;TZID=Europe/Stockholm:20260522T110000
DTSTAMP:20260527T113931
CREATED:20260504T063840Z
LAST-MODIFIED:20260504T070848Z
UID:10001812-1779444000-1779447600@www.scilifelab.se
SUMMARY:Making Sense of AI: Foundations and Practical Realities
DESCRIPTION:Eric Dexter \n\n\n\nNBIS and SciLifeLab Data Centre arrange an open SciLifeLab AI Seminar Series aimed at knowledge-sharing about Artificial Intelligence and applications in the Life Science community. The seminar series is open to everyone. The seminar is run over Zoom on the third Friday of the month during academic terms\, typically between 10 and 11 am\, with approx. 45 min presentation and 15 min discussion. \n\n\n\nWhen: May 22\, 10:00-11:00 \n\n\n\nWhere:  Zoom http://meet.nbis.se/ainw \n\n\n\nSpeaker: Eric Dexter\, Dexter Precision Analytics. \n\n\n\nRead more about the speaker here . \n\n\n\nAbstract \n\n\n\nThe rapid spread of AI models\, especially large language models (LLMs)\, has put many researchers and institutions in an awkward position: making consequential decisions about fast-moving technologies. This talk is about identifying and closing knowledge gaps to support better decision making around AI implementation. It covers the fundamentals of AI literacy needed to participate meaningfully in decisions about these tools\, with the recognition that different roles\, whether user\, decision-maker\, or engineer\, call for different depths of understanding. Working through key vocabulary and the basics of how LLMs actually behave\, including hallucinations\, model bias\, and the rise of agentic systems built on top of them\, the talk lays out a practical framework for getting started with LLMs at the institutional level. We will look at common failure modes that lead to wasted effort or poorly scoped projects\, how to design pilot initiatives that produce useful information rather than just enthusiasm\, and how to build reproducible workflows that hold up to scientific scrutiny. \n\n\n\n \n\n\n\nTo stay updated\, you can join our email list by contacting ai-network@scilifelab.se. \n\n\n\n\nJoin Seminar
URL:https://www.scilifelab.se/event/agentic-ai-in-the-life-sciences-toward-trustworthy-research-environments/
LOCATION:Online event via Zoom
CATEGORIES:Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20260213T100000
DTEND;TZID=Europe/Stockholm:20260213T110000
DTSTAMP:20260527T113931
CREATED:20260120T150524Z
LAST-MODIFIED:20260216T093503Z
UID:10001727-1770976800-1770980400@www.scilifelab.se
SUMMARY:Agentic AI in the life sciences - toward trustworthy research environments
DESCRIPTION:Sebastian Lobentanzer  \n\n\n\nNBIS and SciLifeLab Data Centre arrange an open SciLifeLab AI Seminar Series aimed at knowledge-sharing about Artificial Intelligence and applications in the Life Science community. The seminar series is open to everyone. The seminar is run over Zoom on the third Friday of the month during academic terms\, typically between 10 and 11 am\, with approx. 45 min presentation and 15 min discussion. \n\n\n\nWhen: February 13\, 10:00-11:00  \n\n\n\nWhere:  Zoom http://meet.nbis.se/ainw \n\n\n\nSpeaker: Sebastian Lobentanzer (Computational Biology at Helmholtz Center Munich). The speaker is a Principal Investigator at the Institute of Computational Biology at Helmholtz Center Munich since 2025\, and in affiliation with the Open Targets group at the European Bioinformatics Institute (EMBL-EBI) since 2024. Sebasitian also serves as the head of Computational Biology at the German Center for Diabetes Research.  \n\n\n\nRead more about the speaker here . \n\n\n\nAbstract \n\n\n\nAgentic AI systems promise to improve the accessibility and efficiency of biomedical research\, yet generic large language model (LLM)–based agents often lack the reliability\, transparency\, and reproducibility required for scientific use. We present BioChatter\, a modular\, ontology-grounded agentic AI framework designed as the basis for an Integrated Research Environment (IRE) for biomedicine. BioChatter orchestrates LLMs\, biomedical knowledge representations\, and domain-specific tools within transparent and auditable workflows\, enabling domain-aware reasoning and traceable data flows from raw data to scientific conclusions. \n\n\n\nFollowing a benchmark-first development paradigm\, BioChatter supports systematic evaluation of agent behavior\, reasoning strategies\, and tool use prior to deployment. Using extensible interfaces such as the Model Context Protocol\, the framework enables interoperable\, community-driven extension while maintaining clear separation between reasoning\, knowledge\, and execution layers. By moving beyond chatbot-style interactions toward reproducible research workflows\, BioChatter demonstrates how agentic AI can evolve from opaque assistants into trustworthy research partners for the life sciences. \n\n\n\n \n\n\n\nTo stay updated\, you can join our email list by contacting Olga Dethlefsen (olga.dethlefsen@dbb.su.se) or Bengt Sennblad (bengt.sennblad@scilifelab.se). \n\n\n\nPresentation Slides \n\n\n\nPowered By EmbedPress \n\n\n\n \n\n\n\nJoin the webinar  \n\n\n\n\nJoin event
URL:https://www.scilifelab.se/event/agentic-ai-in-the-life-sciences-towards-trustworthy-research-environments/
LOCATION:Online event via Zoom
CATEGORIES:Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20250926T100000
DTEND;TZID=Europe/Stockholm:20250926T110000
DTSTAMP:20260527T113931
CREATED:20250918T102541Z
LAST-MODIFIED:20250926T144156Z
UID:10001616-1758880800-1758884400@www.scilifelab.se
SUMMARY:Practical tools for facilitating openness in AI research and development: Introducing the Model Openness Framework and the OpenMDW license
DESCRIPTION:Speaker: Cailean Osborne\, PhD.  \n\n\n\nNBIS and SciLifeLab Data Centre arrange an open SciLifeLab AI Seminar Series aimed at knowledge-sharing about Artificial Intelligence and applications in the Life Science community. The seminar series is open to everyone. The seminar is run over Zoom on the third Friday of the month during academic terms\, typically between 10 and 11 am\, with approx. 45 min presentation and 15 min discussion. \n\n\n\nAbstractIn the rapidly evolving field of AI\, openness and transparency are essential for promoting collaboration\, trust\, and reproducibility. In this presentation\, Cailean Osborne will introduce two practical tools designed to support openness in AI research and development: the Model Openness Framework (MOF) and the OpenMDW licence. The MOF offers practical guidance for practitioners to identify which components of machine learning models can be shared\, and recommends suitable licenses for each. Complementing this\, the OpenMDW licence is a novel permissive license tailored specifically for machine learning models\, enabling the use\, study\, modification\, and redistribution of open machine learning models and accompanying artifacts\, including code\, data\, and documentation. Together\, the MOF and OpenMDW license provide practical tools for advancing openness and transparency in AI\, enabling more reproducible\, collaborative\, and responsible AI research and development. \n\n\n\nContactFor questions\, contact bengt.sennblad@scilifelab.se \n\n\n\nPresentation Slides \n\n\n\nPowered By EmbedPress \n\n\n\n\nZoom link
URL:https://www.scilifelab.se/event/practical-tools-for-facilitating-openness-in-ai-research_and_development/
LOCATION:
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20250822T160000
DTEND;TZID=Europe/Stockholm:20250822T170000
DTSTAMP:20260527T113931
CREATED:20250625T063012Z
LAST-MODIFIED:20250811T130403Z
UID:10001571-1755878400-1755882000@www.scilifelab.se
SUMMARY:Mithrl AI Co-Scientist for Accelerating Biological Discovery.
DESCRIPTION:Vivek Adarsh\, Mithrl \n\n\n\nNBIS and SciLifeLab Data Centre arrange an open SciLifeLab AI Seminar Series aimed at knowledge-sharing about Artificial Intelligence and applications in the Life Science community. The seminar series is open to everyone. The seminar is run over Zoom on the third Friday of the month during academic terms\, typically between 10 and 11 am\, with approx. 45 min presentation and 15 min discussion. \n\n\n\nAbstract \n\n\n\n​Despite the explosion of biological data from sequencing\, imaging\, and high-throughput experiments\, extracting meaningful insights remains slow\, manual\, and heavily reliant on limited bioinformatics resources. Scientists often encounter bottlenecks that delay decision-making and limit the scope of discovery. \n\n\n\nIn this talk\, we introduce the concept of an AI Co-Scientist—a set of autonomous agents that collaborates with researchers to analyze data\, generate hypotheses\, and uncover novel insights in minutes rather than months. We’ll explore real-world use cases where AI systems assist with tasks ranging from experimental planning and data preprocessing to functional analysis and scientific interpretation. We’ll also address practical challenges\, including data quality\, trust in AI-generated results\, hallucinations\, and integration into existing research workflows. By the end of the session\, you’ll have a clearer understanding of how AI can partner with scientists to accelerate progress in the life sciences.
URL:https://www.scilifelab.se/event/mithrl-ai-co-scientist-for-accelerating-biological-discovery/
LOCATION:Online event via Zoom
CATEGORIES:Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20250523T100000
DTEND;TZID=Europe/Stockholm:20250523T110000
DTSTAMP:20260527T113931
CREATED:20250510T161536Z
LAST-MODIFIED:20250510T161537Z
UID:10001544-1747994400-1747998000@www.scilifelab.se
SUMMARY:Seqera AI: How we're using LLMs and Agents with Nextflow code.
DESCRIPTION:Phil Ewels\, Seqera \n\n\n\nNBIS and SciLifeLab Data Centre arrange an open SciLifeLab AI Seminar Series aimed at knowledge-sharing about Artificial Intelligence and applications in the Life Science community. The seminar series is open to everyone. The seminar is run over Zoom on the third Friday of the month during academic terms\, typically between 10 and 11 am\, with approx. 45 min presentation and 15 min discussion. \n\n\n\nAbstract \n\n\n\n​LLMs are fast becoming an indispensable tool for anyone writing software. But how well do they cope with Nextflow pipelines? Hear how Seqera is building a suite of AI tools that can kickstart Nextflow developer experience and integrate deeply with bioinformaticians’ tool chains. Learn how we’re going beyond simple chat interfaces\, with agentic tooling that can fast-track edits without sacrificing accuracy and reproducibility.
URL:https://www.scilifelab.se/event/seqera-ai-how-were-using-llms-and-agents-with-nextflow-code/
LOCATION:Online event via Zoom
CATEGORIES:Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20250425T100000
DTEND;TZID=Europe/Stockholm:20250425T110000
DTSTAMP:20260527T113931
CREATED:20250403T100003Z
LAST-MODIFIED:20250403T100224Z
UID:10001522-1745575200-1745578800@www.scilifelab.se
SUMMARY:Towards an interpretable deep learning model of cancer cells.
DESCRIPTION:Avlant Nilsson\, DDLS fellow\, Karolinska Institutet \n\n\n\nNBIS and SciLifeLab Data Centre arrange an open SciLifeLab AI Seminar Series aimed at knowledge-sharing about Artificial Intelligence and applications in the Life Science community. The seminar series is open to everyone. The seminar is run over Zoom on the third Friday of the month during academic terms\, typically between 10 and 11 am\, with approx. 45 min presentation and 15 min discussion. \n\n\n\nAbstract \n\n\n\nCancer emerges from complex molecular interactions that drive pathological cells states. To model these interactions\, we develop deep learning frameworks of cellular signaling\, gene regulation\, and metabolism. Our approach embeds prior knowledge networks into a recurrent architecture\, allowing us to capture cellular dynamics by training on omics data across different perturbations and conditions.At the core of our modeling is a propagator function that predicts the next cell state based on the current state\, enabling the simulation of molecular state transitions over time. To ensure biological plausibility\, we employ a technic based on feature embedding and superposition that encodes molecular identities in a structured feature space while restricting the predictive input for each molecular state to its direct network connections. These structured embeddings facilitate the use of a universal function allowing generalization across different molecules\, cell types\, and experimental settings.By constraining learned representations to known molecular entities\, our framework maintains interpretability while enabling data-driven inference. Ultimately\, we aim to integrate our models into a unified representation of cellular behavior. Bridging mechanistic understanding with predictive modeling\, this work lays the foundation for AI-driven precision medicine\, offering new tools to simulate and control cancer cell states.
URL:https://www.scilifelab.se/event/towards-an-interpretable-deep-learning-model-of-cancer-cells/
LOCATION:Online event via Zoom
CATEGORIES:Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20250214T100000
DTEND;TZID=Europe/Stockholm:20250214T110000
DTSTAMP:20260527T113931
CREATED:20250207T152508Z
LAST-MODIFIED:20250402T084940Z
UID:10001482-1739527200-1739530800@www.scilifelab.se
SUMMARY:Is UMAP accurate? Addressing some fair and unfair criticism.
DESCRIPTION:Nikolay Oskolkov\, NBIS\, Lund University \n\n\n\nNBIS and SciLifeLab Data Centre arrange an open SciLifeLab AI Seminar Series aimed at knowledge-sharing about Artificial Intelligence and applications in the Life Science community. The seminar series is open to everyone. The seminar is run over Zoom on the third Friday of the month during academic terms\, typically between 10 and 11 am\, with approx. 45 min presentation and 15 min discussion. \n\n\n\nAbstract \n\n\n\nUMAP is a golden standard dimensionality reduction method in single cell biology\, yet it has a controversial reputation and is sometimes heavily criticized\, see for example [1 – 5]. In particular\, the recent Nature publication of All of Us program [6] gave rise to an avalanche of discussions in scientific community regarding the controversial UMAP figure of human populations suggesting that UMAP is not accurate for this purpose. Remarkably\, the main criticism of UMAP originates (to the best of my knowledge) from the population genomics community\, wile the single cell community seems to be satisfied with the quality of UMAP analysis. \n\n\n\nIn this talk I will discuss peculiarities of data in single cell and population genomics analyses\, and explain some insights from the UMAP algorithm\, which could potentially attempt to resolve the contradiction between the two communities and very different research questions studied by the communities. I will also cover the foundations of PCA + tSNE + UMAP algorithms and emphasize their pros and cons for different types of data in Life Sciences. \n\n\n\n[1] https://simplystatistics.org/posts/2024-12-23-biologists-stop-including-umap-plots-in-your-papers/[2] https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1011288[3] https://x.com/jkpritch/status/1759769445759893832?lang=en[4] https://www.nature.com/articles/d41586-024-00568-w[5] https://www.science.org/content/article/huge-genome-study-confronted-concerns-over-race-analysis[6] https://www.nature.com/articles/s41586-023-06957-x \n\n\n\nSlides \n\n\n\nDownload slides (PDF)
URL:https://www.scilifelab.se/event/is-umap-accurate-addressing-some-fair-and-unfair-criticism/
LOCATION:Online event via Zoom
CATEGORIES:Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20241115T100000
DTEND;TZID=Europe/Stockholm:20241115T110000
DTSTAMP:20260527T113931
CREATED:20240815T085457Z
LAST-MODIFIED:20241111T152828Z
UID:10001323-1731664800-1731668400@www.scilifelab.se
SUMMARY:Strengths and challenges of diversity: Correlative analysis of multimodal image data
DESCRIPTION:Nataša Sladoje\, Uppsala University \n\n\n\nNBIS arranges an open AI and IO Seminar Series aimed at knowledge-sharing about Artificial Intelligence and Integrative Omics (AI & IO) analysis and applications in the Life Science community. The seminar series is open to everyone. The seminar is run over Zoom on the third Friday of the month during academic terms\, typically between 10 and 11 am\, with approx. 45 min presentation and 15 min discussion.  \n\n\n\nAbstract \n\n\n\nThe MIDA (Methods for Image Data Analysis) group\, at Dept of Information Technology\, Uppsala University\, focuses on development of methods which address challenges of biomedical visual data analysis\, while also being broadly applicable to other types of images. I will give a short overview of our different research projects and collaborative initiatives\, and will then focus on our experiences and results in multimodal (bio)image analysis.  \n\n\n\nMultimodal imaging gives an opportunity to collect diverse and complementary information about a specimen\, enabling a deeper understanding of complex systems and phenomena. This advantage comes at the cost of a typically very demanding and challenging data analysis. Successful correlative analysis of the collected data requires accurate automated alignment of multimodal images and efficient information fusion to maximize the gain from the available heterogeneous and complementary content. I will present our results in this context and will discuss our experiences gained in method development and their application. 
URL:https://www.scilifelab.se/event/methods-for-image-data-analysis-mida/
LOCATION:Online event via Zoom
CATEGORIES:Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20241018T100000
DTEND;TZID=Europe/Stockholm:20241018T110000
DTSTAMP:20260527T113931
CREATED:20240815T085623Z
LAST-MODIFIED:20241014T143808Z
UID:10001324-1729245600-1729249200@www.scilifelab.se
SUMMARY:Conformal prediction enables disease course prediction and allows individualized diagnostic uncertainty in multiple sclerosis
DESCRIPTION:Accurate assessment of progression and disease course in multiple sclerosis (MS) is vital for timely and appropriate clinical intervention. The transition from relapsing-remitting MS (RRMS) to secondary progressive MS (SPMS) is gradual and diagnosed retrospectively with a typical delay of three years. To address this diagnostic delay\, we developed a predictive model that is able to distinguish between RRMS and SPMS with high accuracy\, trained on data from electronic health records collected at routine hospital visits obtained from the Swedish MS Registry containing 22\,748 patients with 197\,227 hospital visits. To be useful within a clinical setting\, we applied conformal prediction to deliver valid measures of uncertainty in predictions at the level of the individual patient. We showed that the model was theoretically and empirically valid\, having the highest efficiency at a 92% confidence level\, and demonstrated on an external test set that it enables effective prediction of the clinical course of a patient with individual confidence measures. We applied the model to a set of patients who transitioned from RRMS to SPMS during the cohort timeframe and showed that we can accurately predict when patients transition from RRMS to SPMS. We also identified new patients who\, with high probability\, are in the transition phase from RRMS to SPMS but have not yet received a clinical diagnosis. We conclude that our methodology can assist in monitoring MS disease progression and proactively identify patients undergoing transition to SPMS. An anonymized\, publically accessible version of the model is available at https://msp-tracker.serve.scilifelab.se/. \n\n\n\n \n\n\n\nA preprint is available here: https://www.medrxiv.org/content/10.1101/2024.03.01.24303566v1  \n\n\n\nKim Kultima\, Uppsala University \n\n\n\nNBIS arranges an open AI and IO Seminar Series aimed at knowledge-sharing about Artificial Intelligence and Integrative Omics (AI & IO) analysis and applications in the Life Science community. The seminar series is open to everyone. The seminar is run over Zoom on the third Friday of the month during academic terms\, typically between 10 and 11 am\, with approx. 45 min long presentation and 15 min discussion. 
URL:https://www.scilifelab.se/event/conformal-predictors-for-multiple-sclerosis/
LOCATION:Online event via Zoom
CATEGORIES:Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20240920T100000
DTEND;TZID=Europe/Stockholm:20240920T110000
DTSTAMP:20260527T113931
CREATED:20240815T085241Z
LAST-MODIFIED:20240909T135631Z
UID:10001322-1726826400-1726830000@www.scilifelab.se
SUMMARY:Variational inference for tumor phylogeny using single cell data
DESCRIPTION:Harald Melin\, KTH Royal institute of Technology \n\n\n\nMCMC has long been the gold standard for Bayesian inference in classical phylogenetics\, instantiated e.g. in popular softwares such as MrBayes and BEAST. This presentation focuses on an alternative Bayesian approach\, Variational Inference (VI)\, which has made recent advances in fields of classical and tumor phylogenetics. I will give an introduction to the method and how it is applied in classical phylogeny\, emphasising its strengths and limitations w.r.t. MCMC\, followed by how it facilitates Bayesian inference of copy number evolution in tumors using low coverage single cell whole-genome sequencing data\, based on our recent project VICTree. \n\n\n\n— \n\n\n\nNBIS arranges an open AI and IO Seminar Series aimed at knowledge-sharing about Artificial Intelligence and Integrative Omics (AI & IO) analysis and applications in the Life Science community. The seminar series is open to everyone. The seminar is run over Zoom on the third Friday of the month during academic terms\, typically between 10 and 11 am\, with approx. 45 min long presentation and 15 min discussion. 
URL:https://www.scilifelab.se/event/variational-inference/
LOCATION:Online event via Zoom
CATEGORIES:Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20240816T100000
DTEND;TZID=Europe/Stockholm:20240816T110000
DTSTAMP:20260527T113931
CREATED:20240815T084917Z
LAST-MODIFIED:20240815T085734Z
UID:10001320-1723802400-1723806000@www.scilifelab.se
SUMMARY:The protein structure prediction problem: from Anfinsen's hypothesis to AlphaFold and beyond
DESCRIPTION:Claudio Mirabello\, NBIS\, Linköping University \n\n\n\nAbstract: Proteins are the tools responsible for most essential functions carried in every organism\, from viruses to mammals. In order to better understand the way a protein works\, it is important to know its three-dimensional structure. In the past few years\, new Machine Learning technologies – neural networks not too dissimilar to those powering ChatGPT – have made it possible to greatly accelerate the process of determination of protein structures by leveraging their evolutionary history. But how do these new technologies work\, how did we get to build tools such as AlphaFold and what comes next? \n\n\n\nNBIS arranges an open AI and IO Seminar Series aimed at knowledge-sharing about Artificial Intelligence and Integrative Omics (AI & IO) analysis and applications in the Life Science community. The seminar series is open to everyone. The seminar is run over Zoom on the third Friday of the month during academic terms\, typically between 10 and 11 am\, with approx. 45 min long presentation and 15 min discussion.
URL:https://www.scilifelab.se/event/the-protein-structure-prediction-problem-from-anfinsens-hypothesis-to-alphafold-and-beyond/
LOCATION:Online event via Zoom
CATEGORIES:Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20240517T100000
DTEND;TZID=Europe/Stockholm:20240517T110000
DTSTAMP:20260527T113931
CREATED:20240311T123125Z
LAST-MODIFIED:20240311T123126Z
UID:10001199-1715940000-1715943600@www.scilifelab.se
SUMMARY:Digital twins and integrative systems biology
DESCRIPTION:NBIS\, Scilifelab’s Bioinformatics platform\, arranges an open AI and IO Seminar Series aimed at knowledge-sharing about Artificial Intelligence and Integrative Omics (AI & IO) analysis and applications in the Life Science community. The seminar series is open to everyone. The seminar is run over Zoom on the third Friday of the month during academic terms\, typically between 10 and 11 am\, with ca. 45 min long presentation and 15 min discussion. \n\n\n\nFor further info\, please see this website. \n\n\n\n \n\n\n\n\n\n\n\nDigital twins and integrative systems biology\n\n\n\nGunnar Cedersund\, Linköping University \n\n\n\nClick here to join zoom conference
URL:https://www.scilifelab.se/event/digital-twins-and-integrative-systems-biology/
LOCATION:Online event via Zoom
CATEGORIES:Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20240419T100000
DTEND;TZID=Europe/Stockholm:20240419T110000
DTSTAMP:20260527T113931
CREATED:20240115T121853Z
LAST-MODIFIED:20240115T121929Z
UID:10001109-1713520800-1713524400@www.scilifelab.se
SUMMARY:Model-guided ML approaches to integrative omics analyses
DESCRIPTION:NBIS\, Scilifelab’s Bioinformatics platform\, arranges an open AI and IO Seminar Series aimed at knowledge-sharing about Artificial Intelligence and Integrative Omics (AI & IO) analysis and applications in the Life Science community. The seminar series is open to everyone. The seminar is run over Zoom on the third Friday of the month during academic terms\, typically between 10 and 11 am\, with ca. 45 min long presentation and 15 min discussion. \n\n\n\nFor further info\, please see this website. \n\n\n\n \n\n\n\n\n\n\n\nModel-guided ML approaches to integrative omics analyses\n\n\n\nCemal Erdem\, DDLS fellow\, Umeå University \n\n\n\nClick here to join zoom conference
URL:https://www.scilifelab.se/event/model-guided-ml-approaches-to-integrative-omics-analyses/
LOCATION:Online event via Zoom
CATEGORIES:Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20240315T100000
DTEND;TZID=Europe/Stockholm:20240315T110000
DTSTAMP:20260527T113931
CREATED:20240222T142943Z
LAST-MODIFIED:20240222T142946Z
UID:10001174-1710496800-1710500400@www.scilifelab.se
SUMMARY:AI and Ethics
DESCRIPTION:Speaker \n\n\n\nPerihan Elif Ekmekci\, Faculty of Medicine\, TOBB ETÜ University of Economics and Technology\, Turkey \n\n\n\nNBIS arranges an open AI and IO Seminar Series aimed at knowledge-sharing about Artificial Intelligence and Integrative Omics (AI & IO) analysis and applications in the Life Science community. The seminar series is open to everyone. The seminar is run over Zoom on the third Friday of the month during academic terms\, typically between 10 and 11 am\, with ca. 45 min long presentation and 15 min discussion.  \n\n\n\njoin meeting
URL:https://www.scilifelab.se/event/ai-and-ethics/
LOCATION:Online event via Zoom
CATEGORIES:Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20240216T100000
DTEND;TZID=Europe/Stockholm:20240216T110000
DTSTAMP:20260527T113931
CREATED:20240115T121541Z
LAST-MODIFIED:20240213T154055Z
UID:10001108-1708077600-1708081200@www.scilifelab.se
SUMMARY:Clusters\, gene flow and artificial genotypes - looking at population structure from a deep learning angle
DESCRIPTION:NBIS\, Scilifelab’s Bioinformatics platform\, arranges an open AI and IO Seminar Series aimed at knowledge-sharing about Artificial Intelligence and Integrative Omics (AI & IO) analysis and applications in the Life Science community. The seminar series is open to everyone. The seminar is run over Zoom on the third Friday of the month during academic terms\, typically between 10 and 11 am\, with ca. 45 min long presentation and 15 min discussion. \n\n\n\nFor further info\, please see this website. \n\n\n\n \n\n\n\n\n\n\n\nClusters\, gene flow and artificial genotypes: looking at population structure from a deep learning angle\n\n\n\nMarcin Kierzcak\, NBIS\, Uppsala University \n\n\n\nWe will look at different ways of modelling and visualising population structure based on genomic kinship. Starting from more traditional approaches like PCA or MDS as benchmark\, we will see how one can build more complex deep learning-based models (autoencoders) and we will discuss when such approach can be beneficial. Finally\, we are going to see how generative deep learning (VAEs) can be used to augment original input data with some artificially-generated individuals with desired pre-defined kinship relationships. \n\n\n\nsee further on the session page https://scilifelab.atlassian.net/l/cp/oR289EJK for updates. \n\n\n\nHope to see you all on this exciting talk on Friday\, \n\n\n\nClick here to join zoom conference
URL:https://www.scilifelab.se/event/clusters-gene-flow-and-artificial-genotypes/
LOCATION:Online event via Zoom
CATEGORIES:Event
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BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20240119T100000
DTEND;TZID=Europe/Stockholm:20240119T110000
DTSTAMP:20260527T113931
CREATED:20240115T114456Z
LAST-MODIFIED:20240116T094413Z
UID:10001107-1705658400-1705662000@www.scilifelab.se
SUMMARY:AICell Lab -- Building AI Systems for Human Cell Modeling and Simulation
DESCRIPTION:NBIS\, Scilifelab’s Bioinformatics platform\, arranges an open AI and IO Seminar Series aimed at knowledge-sharing about Artificial Intelligence and Integrative Omics (AI & IO) analysis and applications in the Life Science community. The seminar series is open to everyone. The seminar is run over Zoom on the third Friday of the month during academic terms\, typically between 10 and 11 am\, with ca. 45 min long presentation and 15 min discussion. \n\n\n\nFor further info\, please see this website. \n\n\n\n \n\n\n\n\n\n\n\nAICell Lab — Building AI Systems for Human Cell Modeling and Simulation\n\n\n\nWei Ouyang\, DDLS fellow\, Royal Institute of Technology\, KTH \n\n\n\nThe AICell Lab is a newly founded group by the Data-Driven Life Science fellows program at the department of applied physics at KTH. The lab is dedicated to building artificial intelligence (AI) systems for cell and molecular biology\, with the ultimate goal of modeling the human cell and building human cell simulators using powerful AI models. The lab’s approach to this grand challenge involves not only innovations in data analysis and modeling\, but also in data generation\, specifically the creation of an automated imaging farm equipped with multiple microscopes\, robotic arms\, liquid handling robots\, and automatic incubators. The lab’s AI software infrastructure enables real-time augmentation of microscopy views\, generating artificial labels and annotations\, and optimizing experimental conditions to capture rare events in live cells. The long-term goal of the AICell Lab is to create large-scale whole human cell models trained on existing multi-omics datasets and new data generated by the imaging farm\, which have the potential to revolutionize in-silico cell experimentation and drug discovery while contributing to a holistic and systematic understanding of the human cell. \n\n\n\nClick here to join zoom conference
URL:https://www.scilifelab.se/event/ai-approach-to-cell-and-molecular-biology/
LOCATION:Online event via Zoom
CATEGORIES:Event
END:VEVENT
END:VCALENDAR