About CBB

Carsten Daub is an Associate Professor (“Docent” in the Swedish academic system) and group leader for the Clinical Transcriptomics research group at the Department of Biosciences and Nutrition at Karolinska Institutet. His bioinformatics expertise includes analysis of transcriptomics and epigenomics datasets, genome annotation and gene regulation. 

Links: 
https://www.daublab.org/

https://staff.ki.se/people/carsten-daub
 

Hannes Hagström is a consultant in Hepatology at the Karolinska University Hospital. He is also an adjunct professor and group leader for Hannes Hagström group (https://ki.se/en/medh/hagstrom-group) at Karolinska Institutet. His research is focused on clinical and epidemiological studies of liver diseases. 

I hold a PhD in molecular and cellular biology but eventually transitioned into the field of bioinformatics. My initial focus encompassed the analysis of microarray gene expression studies and chromatin immunoprecipitation sequencing. Since then, I have acquired extensive experience in numerous applications where massively parallel sequencing can be applied. Specifically, my expertise extends to gene expression analysis (RNAseq), chromatin exploration (ChIPseq, ATACseq, RRBS), single-cell analysis, and extensive data visualization. I am proficient in R, which serves as the primary platform for conducting analyses. Furthermore, I have developed a robust understanding of Linux and bash scripting, essential for big data management and many analysis pipelines. 

Due to my position at the BEA core facility, I have actively contributed to numerous projects spanning a broad spectrum of biological systems. This includes diverse areas such as cancer dynamics, developmental processes, and immune responses, encompassing a wide range of organisms from humans to viruses.

Davide is a PhD statistician with many years of experience in working with biological, epidemiological, genetic, and social data of different kind and in various contexts. During the last years his work has been focused on the analysis of immunological and survival data of patients after cell-therapy and allogeneic stem cell transplantation. His other main interest is education: teaching and mentoring students, and organizing seminars and workshops.

Ghada Nouairia is a computational biologist and a bioinformatician with experience in different computational methods (clustering, networks, phylogeny, etc.). She has also worked with a wide range of omics data including proteomics, transcriptomics, epigenomics and genomes.

Currently, her research is directed to clinical application for diagnosis and prognosis in oncology.

Henrike Häbel has a doctoral degree in mathematical statistics from Chalmers University of Technology and University of Gothenburg. Before joining Karolinska Institutet, she completed a post-doctoral fellowship at the Natural Resources Institute Finland. As part of the Medical Statistics Unit (Medstat), Department of Learning, Informatics, Management and Ethics (LIME) and the Centre for Bioinformatics and Biostatistics (CBB), Henrike mainly works with statistical consultation and teaching. Her main tasks include data management, survival and regression analysis in epidemiologic and population-based studies. Her research and teaching interests are in biostatistics, statistical epidemiology, spatial statistics and image analysis. Henrike has software experience in R, STATA, SAS and SPSS.

Michael Ingre is a biostatistician at the Centre for Bioinformatics and Biostatistics (CBB) and the Department of Medicine (MedH) at Karolinska Institutet. He has earned a PhD in Psychology, and in his early research focused on stress, sleep, health, and working hours. Over the years Michael’s research intertest has expanded to include methodological research, meta-science, clinical research, and epidemiology. 

Michael’s work primarily involves data management and transferring research questions, theories and hypotheses into statistical models that can be tested on data, as well as mentoring and teaching. He is experienced in using SPSS, Stata, and R, but prefer R. 

Rickard Strandberg has a PhD in Biostatistics. His main expertise is in regression modelling and prediction, including linear models, longitudinal models, survival analysis, and multi-state models. He has experience working with cohorts and register-based data, and is adept with missing data. 

As a researcher, Rickard currently works with clinical prediction models of chronic liver disease as a member of the Hagström research group at Karolinska Institutet Huddinge