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DTSTART;TZID=Europe/Stockholm:20240827T120000
DTEND;TZID=Europe/Stockholm:20241001T120000
DTSTAMP:20260407T093256
CREATED:20240615T115304Z
LAST-MODIFIED:20240615T115305Z
UID:10001278-1724760000-1727784000@www.scilifelab.se
SUMMARY:Data-Driven Life Sciences Course 2024 (Online)
DESCRIPTION:Welcome to the Data-driven Life Sciences 2024 course\, where you will explore the intersection of data science\, artificial intelligence\, and life sciences to drive innovation and discovery. This fully online course culminates in an in-person hackathon\, fostering a vibrant community that gathers the DDLS and SciLifeLab members. \n\n\n\nThe 6 modules aim to introduce learners to computer-driven life sciences\, covering application areas in data-driven life sciences. Guest lecturers (DDLS Fellows\, SciLifeLab fellows\, and SciLifeLab facility training providers) will teach topics including technologies and analysis of data sets from proteomics\, transcriptomics\, biomolecular structure\, molecular dynamics simulations\, and various imaging techniques. These modules present\, analyze\, and discuss models of biological phenomena and related scientific breakthroughs based on such data analysis. \n\n\n\nRegistration\n\n\n\nAs prerequisites for the course\, we recommend that you have a look at the following resources: \n\n\n\n\nPlease have a look at the SciLifeLab Data-Driven Life Science (DDLS) initiative website to understand what data-driven life sciences are\, and how Sweden is investing in this area. Focus in particular on the concept of the data life cycle\, which is central in this class.\n\n\n\nWe will use Python as the main programming language in the computer lab\, so please make sure you know the basics of Python. \n\n\n\n\nFor the computer lab\, you will need a computer with internet access\, and make sure you have the following set up: \n\n\n\n\nInstall the latest browser\, e.g. Chrome\n\n\n\nRegister a Google account for the Google Colab access and use the Google Drive\n\n\n\nRegister a ChatGPT account (Note: No need to subscribe to the paid version of ChatGPT\, using the free version is sufficient for this course)\n\n\n\nRegister a Github account for versioning of the code\n\n\n\n\nLearning objectives:  \n\n\n\n\nDescribe the field of data-driven life sciences\n\n\n\nPresent an overview of various application areas\n\n\n\nProvide examples of applications and their associated analysis methods\n\n\n\nApply statistical and machine learning analysis to biological data sets\n\n\n\nFormulate models of biological phenomena\n\n\n\nPresent and review scientific literature in computer-driven life sciences\n\n\n\nReflect on the ethical consequences of data-driven life sciences\n\n\n\nPractice good data management\, including collection\, handling\, sharing\, and analysis\n\n\n\n\nFor questions\, contact the course leader Wei Ouyang at weio@kth.se
URL:https://www.scilifelab.se/event/data-driven-life-sciences-course-2024-online/
LOCATION:Online event via Zoom
CATEGORIES:Course
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20241001T080000
DTEND;TZID=Europe/Stockholm:20241003T170000
DTSTAMP:20260407T093256
CREATED:20240529T151443Z
LAST-MODIFIED:20240529T151527Z
UID:10001270-1727769600-1727974800@www.scilifelab.se
SUMMARY:Basic Course in Scanning and Transmission Electron Microscopy (SEM/TEM) for Life Sciences
DESCRIPTION:This course covers lectures and practical demonstrations in SEM and TEM techniques. The contents include principles of electron microscopy\, specimen preparation\, cryo-electron microscopy and correlative light-electron microscopy. The main focus will be on imaging biological samples\, but the course may also be suitable for material scientists interested in high-resolution electron microscopy. \n\n\n\nRead more\n\n\n\nApplication deadline:10 September 2024 \n\n\n\nLocation:Lectures at the KBC Building and laboratory demonstrations at UCEM. \n\n\n\nParticipants:18 persons \n\n\n\nInstructors:UCEM staff \n\n\n\nDuration:3 days \n\n\n\nBreaks/Refreshments:Coffee\, cookies and fruit. \n\n\n\nCosts:No course fee\, but full attendance is required! \n\n\n\nExamination/Credits:Oral and practical examinations are conducted during laboratory demonstrations. A course certificate will be given after participants attend all lectures and laboratory demonstrations for this 3-day course. UCEM recommends PhD program examiners to give 1 ECTS after successful participation.
URL:https://www.scilifelab.se/event/basic-course-in-scanning-and-transmission-electron-microscopy-sem-tem-for-life-sciences/
LOCATION:KBC Building Umeå\, Linneaus Väg 6\, Umeå
CATEGORIES:Course
ATTACH;FMTTYPE=image/jpeg:https://www.scilifelab.se/wp-content/uploads/2024/05/241001_241003_Basic-TEM-SEM-Life-Sciences-2024.jpg
ORGANIZER;CN="SciLifeLab Ume%C3%A5":MAILTO:umea@scilifelab.se
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20241014T080000
DTEND;TZID=Europe/Stockholm:20241025T170000
DTSTAMP:20260407T093256
CREATED:20240617T081347Z
LAST-MODIFIED:20240617T081528Z
UID:10001279-1728892800-1729875600@www.scilifelab.se
SUMMARY:New Super-Resolution\, Light-Sheet\, and FCS-Methods at Scilifelab
DESCRIPTION:The Advanced Light Microscopy Facility\, ALM\, at Scilifelab gives a two-week PhD-level course on four new imaging and fluorescence spectroscopy techniques: \n\n\n\nDepletion-based Super-Resolution Imaging \n\n\n\n\nSTED-imaging\, 2D and 3D\, 30-50 nm resolution\n\n\n\nIn Living Cells – MoNaLISA\, 1-2 Hz\, 100 x 100 mm field of view\n\n\n\n\nMINFLUX \n\n\n\n\nImaging with 3 nm resolution\n\n\n\nTracking single molecules at 10 kHz\n\n\n\n\nLight-Sheet Imaging \n\n\n\n\nLong time-lapse imaging of live model organisms with low phototoxicity\n\n\n\nUltrafast volumetric imaging of cells with lattice light-sheet microscopy\n\n\n\n\nFCS-Methods \n\n\n\n\nMeasurements of concentrations\, diffusion coefficients\, molecular dynamics and interactions\, in solution or living cells\n\n\n\nCross-correlation\, FRET-\, STED-\, and line-scan-FCS are covered\n\n\n\n\nLecturers: \n\n\n\nSteven Edwards \n\n\n\nErdinc Sezgin \n\n\n\nAna Agostinho \n\n\n\nFrancesca Pennacchietti \n\n\n\nHans Blom \n\n\n\nStefan Wennmalm \n\n\n\nDates: Monday October 14th – Friday October 25th 2024 \n\n\n\nCredits: 3 hp for PhD students \n\n\n\nLocation: Gamma 3\, Scilifelab\, Solna \n\n\n\nRegistration: stewen@kth.se latest September 30th
URL:https://www.scilifelab.se/event/new-super-resolution-light-sheet-and-fcs-methods-at-scilifelab/
LOCATION:Gamma 3\, Tomtebodavägen 23 A\, Solna\, Sweden
CATEGORIES:Course
ORGANIZER;CN="Advanced Light Microscopy Unit":MAILTO:stewen@kth.se
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BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20241014T090000
DTEND;TZID=Europe/Stockholm:20241018T170000
DTSTAMP:20260407T093256
CREATED:20240326T120939Z
LAST-MODIFIED:20240403T083011Z
UID:10001215-1728896400-1729270800@www.scilifelab.se
SUMMARY:Omics Integration and Systems Biology
DESCRIPTION:National course open for PhD students\, postdocs\, researchers\, and other employees in all Swedish universities\, in need of a general description of different approaches for working with multiple types of biological data. We also welcome applications from outside of Sweden and from the non-academic sector\, for more info contact us! \n\n\n\n\n\n\n\nImportant dates and information\n\n\n\nApplication opens: 2024-08-05 \n\n\n\nApplication closes: 2024-09-16 \n\n\n\nConfirmation to accepted students: 2024-09-23 \n\n\n\nCourse Leader and teachers: \n\n\n\nNikolay Oskolkov (Lund University\, course leader) \n\n\n\nRasool Saghaleyni (Chalmers University of Technology\, course leader) \n\n\n\nSergiu Netotea (Chalmers University of Technology\, course lecturer) \n\n\n\nJennifer Fransson (Uppsala University\, course lecturer) \n\n\n\nYuan Li (Lund University\, TA) \n\n\n\nNima Rafati (Uppsala University\, TA) \n\n\n\nIn case you miss information on any of the above dates\, please contact: \n\n\n\nNikolay Oskolkov\, nikolay.oskolkov@scilifelab.se \n\n\n\nRasool Saghaleyni\, rasools@chalmers.se \n\n\n\n\n\n\n\n\n\nApplication\n\n\n\n\n\nCourse website\n\n\n\n\n\nCourse fee\n\n\n\nA course fee* of 3000 SEK for academic participants and 15 000 SEK for non-academic participants will be invoiced to accepted participants. The fee includes all coffee breaks\, all lunches and 1 course dinner. \n\n\n\n*Please note that NBIS cannot invoice individuals \n\n\n\n\n\n\n\nCourse content\n\n\n\nThe aim of this workshop is to provide an integrated view of data-driven analysis of biological data through machine learning\, graph and network analysis as well as constraint-based modeling integration methods. A general description of different approaches for working with multiple layers of biological information\, i.e. Omics data (e.g. transcriptomics and genomics) will be presented with some of the lectures discussing their advantages and pitfalls. The techniques will be discussed in terms of their rationale and applicability. \n\n\n\nTopics covered will include: \n\n\n\n\nData pre-processing\, cleaning and feature selection prior to integration;\n\n\n\nApplication of key machine learning methods for multi-omics analysis including deep learning;\n\n\n\nMulti-omics factor analysis\, dimension reduction and clustering;\n\n\n\nSingle Cell and Spatial transcriptomics integration;\n\n\n\nBiological network inference\, community and topology analysis and visualization;\n\n\n\nCondition-specific and personalized modeling through Genome-scale Metabolic models for integration of transcriptomic\, proteomic\, metabolomic and fluxomic data;\n\n\n\nIdentification of key biological functions and pathways;\n\n\n\nIdentification of potential biomarkers and targetable genes through modeling and biological network analysis;\n\n\n\nApplication of network approaches in meta-analyses;\n\n\n\nSimilarity network fusion and matrix factorization techniques;\n\n\n\nIntegrated data visualization techniques\n\n\n\n\n\n\n\n\nLearning outcomes\n\n\n\nUpon completion of this course\, you will be able to: \n\n\n\n\nIdentify key methods for analysis and integration of omics data based on a given dataset;\n\n\n\nPerform  feature selection and dimension reduction techniques; \n\n\n\nUnderstand strengths and pitfalls of key machine learning techniques in multi-omic analysis;\n\n\n\nApply unsupervised and supervised machine learning data integration techniques;\n\n\n\nBuild biological networks based on different omics data including integrated multi-omics networks;\n\n\n\nPerform centrality and community analyses in graphs;\n\n\n\nApply network approaches in meta-analyses;\n\n\n\nApply similarity network fusion of patient data;\n\n\n\nCompare different cell-types or conditions through the application of different biological network analysis techniques;\n\n\n\nSimulate biological functions using constraint-based models and flux balance analysis;\n\n\n\nIdentify potential confounding factors and sources of bias.\n\n\n\n\n\n\n\n\nEntry requirements\n\n\n\nThe following is a list of skills required for being able to follow the course and complete the exercises: \n\n\n\n\nBasic knowledge in R or Python;\n\n\n\nBasic understanding of frequentist statistics;\n\n\n\n\nDesirable\, but not essential\, skills increasing the output of the course\, include: \n\n\n\n\nExperience with NGS and omics analysis\n\n\n\nCompleting “Introduction to bioinformatics using NGS data” and “Introduction to biostatistics and machine learning” NBIS courses\n\n\n\n\n\n\n\n\nDue to limited space the course can accommodate a maximum of 35 participants. If we receive more applications\, participants will be selected based on selection criteria\, including (but not limited to) correct entry requirements\, motivation to attend the course\, as well as gender and geographical balance.
URL:https://www.scilifelab.se/event/omics-integration-and-systems-biology/
LOCATION:Lund University\, Lund\, Sweden
CATEGORIES:Course
ORGANIZER;CN="NBIS - National Bioinformatics Infrastructure Sweden":MAILTO:education@nbis.se
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20241028T090000
DTEND;TZID=Europe/Stockholm:20241101T170000
DTSTAMP:20260407T093256
CREATED:20240808T121308Z
LAST-MODIFIED:20240809T075123Z
UID:10001316-1730106000-1730480400@www.scilifelab.se
SUMMARY:R Programming Foundations for Data Analysis
DESCRIPTION:The course is addressed to individuals with little or no experience in programming but who are enthusiastic about learning how to use R for data analysis and streamline their work. It is a national course open for PhD students\, postdocs\, researchers and other employees in all Swedish. We also welcome applications from outside of Sweden (EU-zone) and from the non-academic sector\, for more info contact us. NOTE: In October 2024\, the course will be a 5-day-course on-site both in Uppsala and Lund. \n\n\n\n\n\n\n\nVenue – onsite\n\n\n\n\nUppsala University: Experimental room\, Campus Blåsenhus\, von Kraemers allé 1A\, 2nd floor\n\n\n\nLund University: Retina D227\, Biologihuset\n\n\n\n\n\n\n\n\nImportant dates\n\n\n\n\nApplication open: August 08\, 2024\n\n\n\nApplication deadline: September 30\, 2024\n\n\n\nConfirmation to accepted students: October 4\, 2024\n\n\n\n\nResponsible teachers: Nima Rafati\, Guilherme Dias\, Miguel Angel Redondo\, Marcin Kierczak\, Lokeshwaran Manoharan\, Louella Vasquez \n\n\n\nContact for questions: edu.r@nbis.se \n\n\n\n\n\n\n\nCourse fee\n\n\n\nA course fee* of 3000 SEK for non-profit organizations or 15000 SEK for private companies will be invoiced to accepted participants. This includes lunches\, coffee\, snacks\, and one course dinner. \n\n\n\n*Please note that NBIS cannot invoice individuals \n\n\n\n\n\n\n\n\n\nApplication\n\n\n\n\n\nCourse website\n\n\n\n\n\n\n\n\n\nCourse content\n\n\n\nThe course covers fundamental concepts of programming and software design focusing on programming in R. We will go through various aspects of R scripting. After introductory lectures on good programming practices\, basic software design theory and a brief overview of R\, we will delve into programming. We start by learning how to use R as a basic calculator\, what are variable types\, how to use data structures\, how to implement repeating actions with and without loops\, and how to take actions based on certain conditions. We gradually proceed to loading data\, importing data from common file formats\, some basic matrix algebra and learning how to perform basic statistical tests and visualize results. You will learn how to document your work and how to generate automatic reports using real-life datasets. During the course you will also be working on a small dataset to apply knowledge you learnt in the course and will present that in a report format towards the end of the workshop. \n\n\n\nTopics covered will include: \n\n\n\n\nVariables and Operators\n\n\n\nMatrices\, lists\, and dataframes\n\n\n\nData manipulation\n\n\n\nVisualization\n\n\n\nR packages\n\n\n\nBioconductor\n\n\n\n\nUpon completion of this course\, you will be able to: \n\n\n\n\nDescribe different data structures commonly used in R.\n\n\n\nWork with different data types.\n\n\n\nImport and export data from and to R environment. \n\n\n\nManipulate data.\n\n\n\nWork with dataframes and lists.\n\n\n\nVisualize the data.\n\n\n\nUse R Markdown to create reports containing text\, code\, tables and/or figures.\n\n\n\n\n\n\n\n\nEntry requirements\n\n\n\nGood general computer literacy is expected\, but no previous experience in programming or R is required. You are expected to know basic concepts in mathematics and statistics\, but the emphasis of the course is to learn how to use R. \n\n\n\nParticipants are expected to use their own computers with pre-installed R and R Studio (detailed instructions will be given upon acceptance). \n\n\n\nDue to our best practice to have a high teacher to student ratio\, there are a maximum number of allowed participants. If we receive more applications\, participants will be selected based on several criteria. Selection criteria include correct entry requirements\, motivation to attend the course as well as gender and geographical balance.
URL:https://www.scilifelab.se/event/r-programming-foundations-for-data-analysis/
LOCATION:Uppsala University\, Lund University
CATEGORIES:Course
ORGANIZER;CN="NBIS - National Bioinformatics Infrastructure Sweden":MAILTO:education@nbis.se
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