16 May: Theme day AI / Data-driven Life Science
The practice of life science is continuously becoming more data-driven. The amount and complexity of data are growing exponentially, and more scientific discoveries are enabled when data is openly available to researchers across the world. The rapid technical developments made in life science, combined with innovations in data processing and AI, will have an increasingly important role in research and development and affect virtually all fields in medicine and natural science.
During this day, you will meet cutting-edge international researchers together with local researchers, and take part in current research and discuss open data, AI and ethics, and visualisation related to life science.
Registration is now closed.
Some lectures and presentations are livestreamed on zoom. If they can be viewed digitally, there is an (L) after the title. You do not need to have registered to take part in the lectures digitally.
For more information, contact Bengt Persson and Carolina Wählby
Location: Ångström Laboratory, Lägerhyddsvägen 1
Registration opens at 08.30 outside Eva von Bahr, house 10, Ångströmlaboratory.
All lectures and presentations takes place in Eva von Bahr.
09.15 - 09.30: Introduction. (L)
09.30 - 10.00: Data science approaches to decipher the infant gut microbiome. (L)
Moran Yassour, Faculty of Medicine & School of Computer Science & Engineering, The Hebrew University of Jerusalem
10.00 - 10.15: Connecting non-coding mutations in cancer to function by evoultionary constraint. (L)
Karin Forsberg Nilsson, Professor at the Department of Immunology, Genetics and Pathology
10.15 - 10.30: Using ancient and modern genomic data to reconstruct human history in Africa. (L)
Carina Schlebusch, Associate Professor at Department of Organismal Biology, Uppsala University
10.30 - 11.15: Coffee and poster-session
11.15 - 12.30 Visual demonstrations and scientific highlights from Uppsala University.
12.30 - 13.50: Lunch & Performance
Lunch salad can be picked up outside Eva von Bahr.
14.00 - 14.30: Longitudinal Phenotypes, Disease and Treatment Trajectories at Population Scale (L)
Søren Brunak, Novo Nordisk Foundation Center for Protein Research, University of Copenhagen
14.30 - 14.45: Revealing patterns of hidden biodiversity by combining AI and environmental DNA. (L)
Tobias Andermann, Data Driven Life Science Fellow, Uppsala University
14.45 - 15.00: Ethics, AI, and Life (Science). (L)
Thomas Lennerfors, Professor at the Department of Civil and Industrial Engineering and Mikael Laaksoharju, Seniror Lecturer at the Department of Information Technology
15.00 - 15.30: Coffee
15.30 - 16.30: Panel discussion. (L)
Data science approaches to decipher the infant gut microbiome.
The microbiome is the collection of microorganisms, mostly bacteria, living in and on our bodies. This complex community is integral to maintaining human health. The gut microbiome is the largest and most diverse community of microbes in our bodies. Interestingly, microbes that inhabit the infant gut in the first months of life influence development of the immune system and different diseases. In my talk I will describe the biological big-data that we generate in order to characterize microbial communities, and the computational tools we develop to analyze the dynamics of the infant gut microbiome and its role in pediatric health.
No biological knowledge is needed to understand the talk.
Short bio - Moran Yassour
Dr. Moran Yassour is a senior lecturer at the Hebrew University, Faculty of Medicine, with joint affiliation at the school of Computer Science and Engineering. The Yassour lab studies the development of the human microbiome in health and disease, by developing new cohorts to study the establishment of the newborn gut microbiome and characterize the mother-to-child bacterial transmission. During the covid-19 pandemic, the Yassour lab also joined forces with Hadassah Medical Center to analyze hundreds of thousands of SARS-CoV-2 tests, showing how pooling approaches can increase diagnostic labs' efficiency.
Dr. Yassour did her postdoctoral training at the Broad Institute of MIT and Harvard University, with Ramnik Xavier and Eric Lander, where she studied the human gut microbiome. During her PhD in the Friedman (HebrewU) and Regev (MIT/Broad) labs, she developed tools to reconstruct the transcriptome of partially assembled genomes and aberrant cancer genomes.
Dr Yassour received her B.Sc., M.Sc., and Ph.D. in the Computer Science and Computational Biology program at the Hebrew University of Jerusalem.
Longitudinal Phenotypes, Disease and Treatment Trajectories at Population Scale
Multi-step disease trajectories are key to the understanding of human disease progression patterns and their underlying molecular level etiologies. The number of human protein coding genes is small, and many genes are presumably impacting more than one disease, a fact that complicates the process of identifying actionable variation for use in precision medicine efforts. We present approaches to the identification of frequent disease and treatment trajectories from population-wide healthcare data comprising millions of patients and corresponding strategies for linking disease co-occurrences to genomic individuality. We carry out temporal analysis of clinical data in a life-course oriented fashion. We use data covering 7-10 million patients from Denmark collected over a 20-40 year period and use them to “condense” millions of individual trajectories into a smaller set of recurrent ones.