This workshop provides resources to advanced tools for analysis of spatial datasets . It is aimed towards biologists, researchers, computer scientists or data analysts planning to run, analyse and interpret single cells RNA-seq experiments independently.

Spatial Omics Data Analysis

This course if aimed for those who seek to deepen their biostatistical and machine learning skills. Building on the Introduction to Biostatistics and Machine Learning course, this course expands on common  life science data analysis methods, including dimensionality reduction techniques beyond PCA, mixed-effects models for analysis of  repeated measures, and survival analysis.  We will also dive deeper into machine learning, covering more classification algorithms, ensemble techniques, optimization strategies and PLS methods for single and multi-omics data analysis.

This course is aimed for those who seek to deepen their biostatistical and machine learning skills. Building on the Introduction to Biostatistics and Machine Learning course, this course expands on common  life science data analysis methods, including dimensionality reduction techniques beyond PCA, mixed-effects models for analysis of  repeated measures, and survival analysis.  We will also dive deeper into machine learning, covering more classification algorithms, ensemble techniques, optimization strategies and PLS methods for single and multi-omics data analysis.

Machine Learning for Life Sciences

One of the national services offered by NBIS/SciLifeLab is the Bioinformatics Peer review Support track (a.k.a. WABI), providing competence in large-scale data analysis for genomics, transcriptomics, proteomics, metabolomics, Cryo-EM/ET and other technologies. This support has been enabled by funding from the Knut and Alice Wallenberg Foundation, and is a part of the SciLifeLab & Wallenberg National Program for Data-Driven Life Science. We offer a senior bioinformatician to work on your project for up to 500 hours. The support is fully subsidized and free of charge, but extensive hands-on involvement is required by the applying research groups. For more information along with the application form is found at the online submission here:
https://www.nbis.se/services/bioinformatics/peerreview/apply 

Note: This support track is also open to projects involving Cryo-EM applications (potentially combined with other structural biology and structure prediction methods).  

Projects are selected based on their scientific quality. The deadline for the next round of applications to be reviewed by the national evaluation committee is
THURSDAY OCTOBER 1st, 2026 (23:59)

For further questions, please do not hesitate to get in touch with the Bioinformatics support directly at bioinformatics_wabi@scilifelab.se. Also note that the NBIS platform provides bioinformatics support in several different tracks as outlined here: 
https://nbis.se/services

For technical questions regarding cryo-EM/ET, please also refer to the SciLifeLab cryo-EM units:
https://www.scilifelab.se/units/cryo-em/


Apply now! October 1st: Bioinformatics Peer review Support track (including Cryo-EM)

One of the national services offered by NBIS/SciLifeLab is the Bioinformatics Peer review Support track (a.k.a. WABI), providing competence in large-scale data analysis for genomics, transcriptomics, proteomics, metabolomics, Cryo-EM/ET and other technologies. This support has been enabled by funding from the Knut and Alice Wallenberg Foundation, and is a part of the SciLifeLab & Wallenberg National Program for Data-Driven Life Science. We offer a senior bioinformatician to work on your project for up to 500 hours. The support is fully subsidized and free of charge, but extensive hands-on involvement is required by the applying research groups. For more information along with the application form is found at the online submission here:
https://www.nbis.se/services/bioinformatics/peerreview/apply 

Note: This support track is also open to projects involving Cryo-EM applications (potentially combined with other structural biology and structure prediction methods).  

Projects are selected based on their scientific quality. The deadline for the next round of applications to be reviewed by the national evaluation committee is
THURSDAY APRIL 23rd, 2026 (23:59)


For further questions, please do not hesitate to get in touch with the Bioinformatics support directly at bioinformatics_wabi@scilifelab.se. Also note that the NBIS platform provides bioinformatics support in several different tracks as outlined here: 
https://nbis.se/services

For technical questions regarding cryo-EM/ET, please also refer to the SciLifeLab cryo-EM units:
https://www.scilifelab.se/units/cryo-em/



Apply now! April 23rd: Bioinformatics Peer review Support track (including Cryo-EM)

Bioinformatics Drop-in for researchers wanting to discuss bioinformatics problems with experts from NBIS. No advance registration, just drop by - Welcome!
We will be in the SciLifeLab entrance hall, at the line of tables opposite of Café Delta (address: Tomtebodavägen 23A).

Bioinformatics Drop-in Stockholm (SciLifeLab)

The Open Pollen API provides pollen forecasts and data to the broad public. An updated version with even more information was released recently.

NBIS makes data about pollen accessible

A large clinical trial led by researchers at Karolinska Institutet, Karolinska University Hospital and SciLifeLab shows that low-dose aspirin can reduce the risk of stage I–III colorectal cancer relapse by about 50%. The results are published in The New England Journal of Medicine (NEJM)

Aspirin halves recurrence in colorectal cancers

In a recently published study in Science, researchers at the Royal Swedish Academy of Sciences and Stockholm University show that fungi, just like humans, separate their germ cells early in their development. These new and unexpected findings change our understanding of how evolution works among fungi.

Evolution of fungi in a study of fairy rings

SciLifeLab researchers have developed a new tool called AF_unmasked, designed to overcome the limitations of AlphaFold when predicting large and flexible protein complex structures. The new tool was published in Nature Communications the same day that the creators of AlphaFold were awarded the Nobel Prize in Chemistry. Read the full story at [SciLifeLab news](https://www.scilifelab.se/news/new-scilifelab-developed-tool-overcomes-prediction-limitations-of-nobel-prize-winning-alphafold/)


Next drop in

Upcoming courses

NBIS makes data about pollen accessible

Aspirin halves recurrence in colorectal cancers

Evolution of fungi in a study of fairy rings

New tool enhancing Nobel Prize-winning AlphaFold

Vision and mission

International collaborations

Open positions

News

	2026-10-06 to 2026-10-09	Spatial Omics Data Analysis
	2026-10-12 to 2026-10-16	Machine Learning for Life Sciences