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DTSTART;TZID=Europe/Stockholm:20221115T123000
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SUMMARY:DDLS Annual Conference
DESCRIPTION:Welcome to a lunch-to-lunch conference focused on Data-driven Life Science. Listen to the DDLS Fellows and take part in social activities onsite.  \n\n\n\nThe Data-Driven Life Science conference on November 15-16\, 2022\, is the first in-person conference of the DDLS program. This meeting brings together the community in biomolecular data science and AI\, introduces newly appointed DDLS fellows\, and provides opportunities for networking across the research community and SciLifeLab infrastructures. We are excited to host two international keynote speakers and welcome the community to join us. We are excited to meet in person at the poster session and other social events. \n\n\n\n \n\n\n\nDDLS Annual Conference Poster session\n\n\n\nLightning talk and Poster session \n\n\n\nThe lightning talk is 1 minute and will be strictly timed. No slides. Please\, indicate in the registration if you like to present a poster with\, or without\, a 1 min lightning talk. \n\n\n\nDDLS Annual Conference Best Poster Award \n\n\n\nThe DDLS Annual Conference Best Poster Award encourages the submission and exhibition of high-quality posters carried out by young scientists\, including Ph.D. students\, post-doctoral researchers\, etc. The poster should be on a topic related to data-driven life science. The Prize\, which is based upon the decision of a Scientific Committee-appointed Jury\, consists of a certificate and a travel grant of up to 5 000 SEK. The travel must be booked and ordered through the DDLS Support team and follow regular University travel policy. The trip should be completed before 2023-12-31. \n\n\n\n\n\n\n\nTarget group: We welcome all researchers interested in the DDLS program and data-driven life science. \n\n\n\nParticipants onsite: Venue Eva & Georg Klein\, Floor 3 (ground floor)\, Biomedicum\, Stockholm \n\n\n\nParticipate online: Online participation info\, e.g\, zoom link will be sent out upon registration \n\n\n\nOrganizer: SciLifeLab\, host of SciLifeLab & Wallenberg National Program for Data-Driven Life Science. \n\n\n\n\n\n\n\nRegister here\n\n\n\nOnsite: Register before November 9 at 12:00\, so we can order coffee and lunch. \n\n\n\n\n\n\n\n\nDownload Flyer\n\n\n\n\n\n\n\n\n\nDownload Program\n\n\n\n\n\n\n\n\nAgenda\n\n\n\nTuesday\, November 1511:45Drop-in Registration with Coffee and WrapsArea: Social area directly to the right of the entrance. You can leave your coat and bag in the Lecture Hall. We ask the participants to be seated at 12:30.12:30WelcomeTuuli Lappalainen\, KTH/SciLifeLabDDLS updatesOlli Kallioniemi\, SciLifeLab13:00Keynote: Samuli Ripatti\, Institute for Molecular Medicine\, University of HelsinkiGenetic variation and risk of common diseases over the life course13:45Coffee break14:15DDLS Fellow Talk: Tom van der Valk\, Museum of Natural HistoryEnvironmental DNA in the genomic decade14:35Infrastructures for data-driven life scienceJohan Rung\, SciLifeLab Data CentreSciLifeLab Data Centre14:45Ola Spjuth\, SciLifeLab Data CentreManaging the life cycle of AI models and apps15:00Matts Karlsson\, Linköping UniversityNAIS\, Berzelius and the road ahead15:15Poster lightning talks (1 minute per poster)Poster session with snacks and beverage17:30End of Day 1Wednesday\, November 1609:00Keynote: Cecilia Clementi\, Freie Universität BerlinDesigning molecular models with machine learning and experimental data09:45DDLS Fellow Talk: Johan Bengtsson-Palme\, Chalmers University of TechnologyUnderstanding the Evolution of Pathogenicity: Predicting and Preventing the Disease Threats of the Future10:05Announcement of DDLS Annual Conference Best Poster Award10:15Coffee break10:45DDLS Fellow Talk: Tobias Andermann\, Uppsala UniversityBig data approaches for assessing biodiversity value and potential11:05DDLS Fellow Talk: Fredrik Edfors\, Royal Institute of Technology\, KTHHarnessing the promise of next-generation plasma profiling for pan-cancer diagnostics11:25DDLS Fellow Talk: Clemens Wittenbecher\, Chalmers University of TechnologyMetabolomics profiling generates candidate biomarkers for precision nutrition approaches11:45Panel discussion: Training in Data Driven Life ScienceChair: Carolina Wählby\, Uppsala UniversityPanelists: Leslie Solorzano Vargas\, postdoc at KINina Norgren\, coordinator for DDLS education and training\, Umeå UniversityKrzysztof Jurdzinski\, PhD student at KTHDaniel Gedon\, PhD student at UU12:30Joint conference lunchProgram updated 2022-11-12\n\n\n\n\n\n\n\nAbstract\n\n\n\nCecilia Clemens\nDesigning molecular models with machine learning and experimental data. Cecilia Clemens. \n\n\n\nThe last years have seen an immense increase in high-throughput and high-resolution technologies for experimental observation as well as high-performance techniques to simulate molecular systems at a microscopic level\, resulting in vast and ever-increasing amounts of high-dimensional data. However\, experiments provide only a partial view of the molecular processes and are limited in their temporal and spatial resolution. On the other hand\, simulations are still not able to completely characterize large and/or complex molecular processes over long timescales\, thus leaving significant gaps in our ability to study these processes at a physically relevant scale. We present our efforts to bridge these gaps\, by combining statistical physics with state-of-the-art machine-learning methods to design optimal coarse models for complex macromolecular systems. We derive simplified molecular models to reproduce the essential information contained both in microscopic simulation and experimental measurements. \n\n\n\n\nSamuli Ripatti\nGenetic variation and risk of common diseases over the life course. Samuli Ripatti. \n\n\n\nPast 15 years have seen tremendous success in identifying genetic loci associated with common diseases and traits. Much of the current activities focus on strategies for inferring causal variants and genes driving these associations and on the potential translational opportunities arising from the genetic discoveries. I will highlight some of the opportunities\, risks and gaps in our knowledge related to both causal inference and genetic prediction and translation.  I will provide examples from FinnGen study (www.finngen.fi) consisting of genome wide profiles and longitudinal health registry data for  half a million Finns and from a network on biobanks and machine learning/AI -methods developers in INTERVENE Consortium (https://www.interveneproject.eu). \n\n\n\n\nJohan Bengtsson-Palme\nPredicting the disease threats of the future. Johan Bengtsson-Palme \n\n\n\nOur inability to restrain covid-19 to remain a local disease outbreak highlighted an important vulnerability in our preparedness for new infectious diseases – our inability to predict what the future disease agents might look like. This inability makes it impossible to preemptively monitor for potential future pathogens and makes it harder to quickly adapt existing disease surveillance to novel outbreaks. There is no guarantee that the next major outbreak will be viral – with increasing antibiotic resistance\, multidrug-resistant bacteria may very well be the next pandemic. In this talk\, I will discuss how we can predict which genes to look for to find future pathogens before they become widespread in clinics or among the general population\, both in terms of genes responsible for pathogenicity and in terms of antibiotic resistance genes. I will also outline how surveillance for antimicrobial resistance could be adapted to also include markers for pathogenicity and thus allow us to prevent or constrain disease outbreaks early. \n\n\n\n\nFredrik Edfors\nHarnessing the promise of next-generation plasma profiling for pan-cancer diagnostics. Fredrik Edfors \n\n\n\nCancer is one of our biggest worldwide health problems\, causing almost 10 million deaths annually. Despite significant advancements in cancer therapy over the past three decades\, diagnosis and treatment still have a great deal of opportunity for improvement.  \n\n\n\nHere\, a total of 12 prevalent cancer types represented by more than 1\,400 cancer patients’ plasma profiles of 1\,463 proteins were evaluated in trace amounts of blood plasma taken at the time of diagnosis and prior to treatment. A group of proteins linked to each of the examined malignancies was found using ML-based disease prediction models. This precision medicine strategy has the potential to benefit from advances in proteomics and precision and personalized medicine. \n\n\n\n\nTobias Andermann\nBig data approaches for assessing biodiversity value and potential. Tobias Andermann \n\n\n\nOur human societies worldwide are having a profound negative impact on the natural world surrounding us\, leading to experts declaring the current biodiversity crisis. However\, to date it is difficult if not impossible to actually quantify the magnitude of our impact on biodiversity. This is largely due to the overwhelming complexity of biodiversity\, which is not easily summarized and reduced into manageable metrics. Yet\, solving this task is necessary and is arguably one of the biggest and most urgent contemporary challenges for the biological research community. In this talk I will discuss the utility of environmental DNA (eDNA) sequencing as a tool for gathering comprehensive biodiversity data in the field. I will touch upon the challenges and possibilities regarding the application of eDNA data for this purpose\, in particular how these data can be applied to train AI models with the ability to model biodiversity and simulate changes thereof. \n\n\n\n\n \n\n\n\n\n\n\n\nScientific Committee\n\n\n\nTuuli Lappalainen\, chair and DDLS Steering group member\, Clemens Wittenbecher\, DDLS Fellow\, Simon Olsson\, WASP and Johan Rung\, Data Centre.  \n\n\n\nOrganizing Committee\n\n\n\nProject leader Erika Erkstam\, Operations office\, and the DDLS support team Heidi T Persson\, Ulrika Wallenquist\, Titti Ekegren.
URL:https://www.scilifelab.se/event/ddls-annual-conference/
LOCATION:Eva & Georg Klein\, Solnavägen 9\, Stockholm\, 17165\, Sweden
CATEGORIES:Event
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DTSTART;TZID=Europe/Stockholm:20221130T090000
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SUMMARY:DDLS Industry PhD Collaboration Dialogue - online
DESCRIPTION:The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS) is a national 12-year research program that involves 11 partner organizations\, collaborators nationally and internationally\, the Swedish life science community\, industry\, healthcare\, and other stakeholders in society at large. \n\n\n\nDuring the program\, more than 250 PhD students and 200 postdocs in academia and industry will be recruited to facilitate collaborations across sectors and disciplines. The DDLS academic and industrial PhD students and postdocs will all be enrolled in the DDLS Research School promoting acquisition of high competence and skills. This is to meet the future needs within data-driven life sciences\, industrial R&D\, health care and society. The DDLS Research School will be launched in 2024.  \n\n\n\nNow\, both well established companies\, small and medium-sized enterprises\, within the data-driven life science sector as well as academia\, are invited to partake in this event and contribute to the future of the program. \n\n\n\n \n\n\n\nAim\n\n\n\nThe aim of this event is to: \n\n\n\n\nInform about the program and KAW donation letter that specifies industrial PhDs and Postdocs.\n\n\n\nInform about the DDLS Research School\, timeline and recruiting models for industrial PhDs.\n\n\n\nEngage industry in the DDLS Program (e.g.\, being part of the DDLS review committees and involved in decisions and other types of evaluations regarding the DDLS research school).\n\n\n\nDiscuss how industry would like to contribute to the the DDLS Research School and the program.\n\n\n\n\n\n\n\n\nPreliminary Agenda\n\n\n\n\nWelcome\n\n\n\nPresentation of the DDLS program\n\n\n\nOverview of the DDLS Research School\n\n\n\nRecruitment Models for DDLS PhD Program – Academia & Industry\n\n\n\nDiscussion/Dialogue\n\n\n\n\n\n\n\n\nRegistration\n\n\n\nRegister as soon as possible but no later than November 28th. \n\n\n\nRegister here\n\n\n\n\n\n\n\nContact\n\n\n\nMojgan Seraji (contact information below) or DDLS support team: ddls@scilifelab.se \n\n\n\n\n\n\n\n \n\n\n\nMojgan SerajiCollaboration ManagerProject leading\, SciLifeLab Code of Conduct\, DDLS PhD & Postdoc Programs\, DDLS Industry CollaborationMojgan.Seraji@scilifelab.uu.se  +46 (0) 73 46 97 306
URL:https://www.scilifelab.se/event/ddls-industry-phd-collaboration-dialogue-online/
LOCATION:Online event via Zoom
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