Welcome to the 21st Swedish Bioinformatics Workshop 2023 in Stockholm!
The Swedish Bioinformatics Workshop (SBW) is an annual event that has been organized by different universities in Sweden since 2000. It is the biggest meeting of bioinformaticians and computational biologists in Sweden. This year, we are happy to announce that the event will take place in Stockholm on November 6-7 at Nya Karolinska Sjukhuset, Solna.
The event is targeted at, and organized by, PhD students and postdocs, but it’s open to everyone working with any kind of bioinformatics or computational biology. Senior scientists and non-academic participants are welcome. In addition, SBW 2023 is part of the Nordic Computational Biology week and is open to participants from other Nordic countries. Register for virtual participation at forms.gle/qvMYdZQTH5oMduhX6 and visit https://bit.ly/ncb-week-2023 for updates on regional programmes.
On this website, we will be updating more information as the arrangements of the workshop proceed.
While on-site registration is no longer available, you can still register for online participation!
|Before August 26th 2023||After August 26th 2023|
|Other academic participants||500 SEK||1000 SEK|
|Non-academic participants||1500 SEK||2000 SEK|
A. Murat Eren
University of Oldenburg
Meren’s research explores microbial life through ‘omics strategies and lab experiments, developing computational approaches and open-source software. They aim to unravel how microbes interact, evolve, disperse, and adapt to environmental changes from complex datasets.
Ida-Maria Sintorn’s main research interests are image processing for 1) automated content driven multi-scale electron microscopy , and 2) improved explainability and incorporating user guidance in machine learning and pattern recognition tools. Besides theoretical development, her research is focused on biomedical applications such as diagnostics, drug development and disease understanding based on microscopy.
Geir Kjetil Ferkingstad Sandve
University of Oslo
With expertise in gene regulation, omics, epidemiology, and immunology, Geir’s research focuses on understanding how B- and T-cells recognize pathogens. They leverage this knowledge for diagnostics and therapeutics while inspiring methodological advancements in machine learning.
Lars Juhl Jensen
Technical University of Denmark
Lars Juhl Jensen conducts cutting-edge research in protein function prediction, omics integration, and network analysis. As a professor at the University of Copenhagen and scientific advisor of ZS | Intomics, his expertise and contributions in these areas have greatly advanced this field of bioinformatics.
Microsoft Research NYC
With a background in computational neuroscience, reinforcement learning, and human fMRI, Ida builds and evaluates AI inspired by human brains and behavior, focusing on prefrontal and hippocampal cognitive functions like memory, executive function, navigation, and planning. In addition to evaluating AI agents in xbox games, her recent work evaluates planning ability in large language models (LLMs) and augments LLMs inspired by hippocampus and prefrontal cortex.
Max obtained his Ph.D. in bioinformatics at KTH Royal Institute of Technology in Stockholm and currently serves as a bioinformatics scientist at Pixelgen Technologies, where he specializes in the analysis and development of methods for Molecular Pixelation data. Molecular Pixelation is an innovative single cell spatial proteomics assay that enables simultaneous measurement of protein abundance, spatial distribution, and colocalization of targeted surface proteins on individual cells. This technique provides a powerful tool for exploring the complex spatial organization of proteins within single cells, opening new avenues for advancements in immune system research
Invited national speakers
Tanja Slotte (Stockholm University)
Marija Cvijovic (University of Gothenburg)
Laura Carroll (Umeå University)
Marta Carroni (Stockholm University)
|Time||Monday, November 6th 2023|
Deciphering how adaptive immune cells recognise pathogens: gathering suited data, defining appropriate assessments and incrementally improving machine learning methodology
Geir Kjetil Ferkingstad Sandve
Machine learning approaches for novel secondary metabolite discovery
Nanometa Live: A User-friendly Interface for Real-time Metagenomic Data Analysis and Pathogen Identification
Alignment-free identification of antibiotic resistance genes
Adapting to reality- tools to incorporate a human-in-the-loop in biomedical image based deep learning
Enzyme engineering to accelerate the Calvin-Benson-Bessham cycle in cyanobacteria
WebSTR: a population-wide database of short tandem repeat variation in humans
Factors influencing the horizontal transfer of antibiotic resistance genes
|13:15-14:45||Lunch Break / Career Lunch|
Lessons from yeast: synergistic effects of damage accumulation, nutrient signalling and metabolism in the context of cellular rejuvenation and healthspan
Molecular Pixelation: Spatial proteomics of single-cells by next generation sequencing
Optimal transport model of cell differentiation infers developmental trajectories in murine hematopoiesis data
ADMExtract: a tool for rapid mining and comparative analysis of proteomic datasets
|18:30-22:00||Social / Dinner|
|Time||Tuesday, November 7th 2023|
Resistant and vulnerable motor neurons show unique temporal gene regulation in SOD1G93A ALS
A generalized benchmark for all types of enrichment analysis methods
Bioinformatics of cryo-EM data analysis: getting the most out of molecules’ images and combining them with prediction methods
Specifying cellular context of regulons for exploring transcriptome-derived gene regulatory networks
Writing code for those who are looking for a kitchen in a world of restaurants
A. Murat Eren
Genomic analyses of the Linum distyly supergene reveal convergent evolution at the molecular level
Neonatal gut Bifidobacterium associates with indole-3-lactic acid levels in blood and risk of ADHD development
Decoding Disease Mechanisms: Representational Learning from Multi-Tissue Healthy Human RNA-seq Data such that Latent Space Arithmetics Extracts Disease Modules
Hendrik de Weerd
Neuroscience-inspired evaluation and architecture for generative AI
Cost-Reduced Genotyping of SNPs in Large Populations from Pooled Experiments
The lectures will be held at Sune Bergström’s Aula at Karolinska Sjukhuset (Solnavägen 30, Stockholm)
The lecture venue can be easily reached with the public transportation with buses 3,6, and 77. Tickets to the bus can be bought via SL app or paying directly with the debit card to the card reader monitor inside the buses. For more information and planning the travels within Stockholm, check sl.se. For more information about parking around Karolinska Sjukhuset, check the website of Karolinska Sjukhuset .
From left to right: María Bueno Álvez, Philipp Rentzsch, Katja Kozjek, Marcel Tarbier, Kristine Bilgrav Saether, Nilay Peker, Lauri Mesilaakso, Alejandro Rodríguez Gijón and Hauke Wernecke. Missing from photo: Vaishnovi Sekar and Emilia Lahtinen
Kristine Bilgrav Saether
PhD Student at Karolinska Institutet (Rare Diseases group, Stockholm).
Genomics of rare diseases
Maria Bueno Álvez
PhD Student at KTH Royal Institute of Technology & Science for Life Laboratory (Stockholm)
Disease signatures in plasma proteomics data from patients of cancer, cardiovascular conditions, among others.
Postdoctoral researcher at Karolinska Institutet (Centre for Translational Microbiome
Association of gut microbiome with different cancer types.
PhD Student at Gedea Biotech AB (Lund) and Centre for Translational Microbiome Research, Karolinska Institutet (Stockholm).
Impact of novel antibiotics for bacterial vaginosis on the vaginal microbiome.
Alejandro Rodríguez Gijón
PhD Student at Stockholm University and SciLifeLab (Sarahi Garcia’s group).
Comparative genomics of Archaea and Bacteria in aquatic microbial ecology.
PhD Student at Stockholm University and SciLifeLab.
MicroRNA biology and single cells.
Postdoc at Karolinska Institute and SciLifeLab (Vincent Pelenchano’s group).
Development of computational tools to impute complex cell features from molecular profiling data (single-cell and multi-omics data).
Systems developer and affiliation is Centre for Translational Microbiome Research (CTMR), KI (Stockholm).
Development of Biobank application for the National Pandemic Centre and support researchers at CTMR.
Postdoctoral bioinformatician at Karolinska Institutet (Centre for Translational Microbiome Research, Stockholm).
Microbiome study of women with recurrent pregnancy loss.
Scientific Advisory Board
Arne Elofsson (Stockholm University),
Olof Emanuelsson (KTH),
Olga Dethlefsen (NBIS),
Fredrik Boulund (Karolinska Institute),
Kristoffer Sahlin (Stockholm University),
Carolina Wahlby (Uppsala University),