Molly Hammell

Transposon Genomics — from single loci to single cells

Cold Spring Harbor Laboratory

The Gale Hammell lab uses a combination of computational and experimental methods to understand how gene regulatory networks are perturbed in human disease. This includes an emphasis on developing novel tools for the statistical analysis of high-throughput data, developing novel algorithms for modeling the flow of signals through genetic pathways, and importantly, testing these models using the tools of molecular genetics. One particular focus of the M. Hammell lab is to apply these novel statistical analysis methods to better understand how transposable elements are normally controlled. Mounting evidence has implicated transposon activity in a host of human diseases, with particular evidence for activation in several neurodegenerative diseases, including Amyotrophic lateral sclerosis (ALS), Fronto-Temporal Dementia (FTD), and Alzheimer’s Disease (AD). By combining the power of systems-level, high-throughput data analysis with patient-derived ALS, FTD, and AD tissue samples, the lab aims to better understand how these viral-like sequences contribute to cell death and disease.

Fabian Theis

Single-cell latent space learning across labs, modalities and perturbations

Helmholtz Zentrum München

Fabian is the director of the Institute of Computational Biology at the Helmholtz Center Munich and scientific director of the Helmholtz Artificial Intelligence Cooperation Unit (HelmholtzAI) which was launched in 2019. He is a full professor at the Technical University of Munich, holding the chair ‘Mathematical Modelling of Biological Systems’, associate faculty at the Wellcome Trust Sanger Institute as well as adjunct faculty at the Northwestern University. Fabian holds a Master’s degree in Mathematics and Physics and Ph.D. Degrees in Physics and Computer Science. He worked as visiting researcher at the Department of Architecture and Computer Technology (University of Granada, Spain), at the RIKEN Brain Science Institute (Wako, Japan), at FAMU-FSU (Florida State University, USA), and TUAT’s Laboratory for Signal and Image Processing (Tokyo, Japan), and headed the ‘signal processing & information theory’ group at the Institute of Biophysics (Regensburg, Germany). In 2006, he started working as a Bernstein fellow leading a junior research group at the Bernstein Center for Computational Neuroscience, located at the Max Planck Institute for Dynamics and Self-Organisation at Göttingen. In summer 2007, Fabian became working group head of CMB at the Institute of Bioinformatics at the Helmholtz Center Munich. In spring 2009, he became associate Professor for Mathematics in Systems Biology at the Math Department of the TU Munich. 2009-2014 he was a member of the ‘Young Academy’ (founded by the Berlin-Brandenburg Academy of Sciences and Humanities and the German Academy of Natural Scientists Leopoldina) and was awarded an ERC starting grant in 2010. In 2017 he was awarded the Erwin Schrödinger prize together within an interdisciplinary team at the ETH Zürich. Fabian is part of and also coordinates various consortia (i.e. sparse2big involving 8 Helmholtz Centers) and founded the network SingleCellOmics Germany (SCOG). Furthermore, he coordinates the 2019-launched Munich School for Data Science (MUDS) and is co-directing the ELLIS Munich Unit, the local hub of the European Machine Learning network ELLIS. Since 2020, he holds the position of co-chair of the Bavarian AI Council of the Bavarian Ministry for Science and Art and supports the TUM with his expertise as start-up Ambassador.

Marina Panova

eDNA metabarcoding in biodiversity monitoring

University of Gothenburg

Marina has a PhD in Marine Ecology and is docent in Evolutionary Genetics at the University of Gothenburg. For many years her research focus was on genomics of marine organisms and applying NGS tools to non-model, hard-to-sequence organisms. A few years back she became part of the SWEDNA project (https://www.gu.se/en/research/swedna) and now works with testing and developing eDNA methods for biodiversity monitoring.

Oliver Stegle

From genotype to phenotype with single-cell resolution

German Cancer Research Center (DKFZ); European Molecular Biology Laboratory (EMBL)

Oliver Stegle is the Head of the Computational Genomics and Systems Genetics Division at the German Cancer Research Center (DKFZ) and group leader at EMBL in Heidelberg, Germany. His group’s main interest lies in computational methods to unravel the genotype–phenotype map on a genome-wide scale. To address this question, the team carries out research at the interface of statistical inference, machine learning and computational biology, pioneering computational methods for integrating large and heterogeneous datasets across individual and at the single-cell level. The methods and models they develop allow for tying together molecular changes with genetic variation and disease phenotypes and are applied in the context of important studies. Their most recent advances are in the area of single-cell genomics, deriving approaches both for interpreting conventional single-cell RNA-seq variability as well for the analysis of data from spatial technologies. A current direction in the lab is to extend the boundaries of single-cell analysis to integrate single-cell RNA-seq with somatic mutations and clonal substructure in tissues. Oliver obtained his PhD from the University of Cambridge in Physics in 2009 and worked as a postdoc at the Max Planck Institute for Intelligent Systems in Tübingen. He was a group leader at the EMBL European Bioinformatics before moving to Heidelberg in 2018, where he obtained a full professorship (W3) at Heidelberg University in 2020. He has received several recognitions, coordinates the ELLIS Health program and is an ERC investigator.

About the talk: The study of genetic effects on gene expression and other molecular traits using bulk sequencing has allowed for the functional annotation of disease variants in diverse human tissues. Advances in single-cell RNA sequencing and multi-omics protocols provide for unprecedented opportunities to greatly increase the resolution of such genetic analyses, allowing to assess gene regulatory effects at the resolution of cell types, cell states and even in individual cells in human tissues. In this talk, I will present computational strategies for analyzing and integrating population-scale multi-omics dataset. I will then describe applications of these strategies to population-scale single-cell sequencing dataset from genetically diverse human iPSCs across differentiation towards a neuronal fate. Our data provide unprecedented opportunities to map regulatory variants both in major cell types but also in subtle subtypes and across cellular differentiation, revealing dynamic changes of regulatory variants. We describe novel disease-relevant linkages of several of the regulatory variants identified, thereby illustrating how this technology can open novel opportunities to study risk factors for human diseases.

Aaron Scott

Machine learning applications for the analysis of mass spectrometry proteomics data

Lund University

Aaron is a PhD student at the department of Infection Medicine, where he focuses on the development of modern methods for the analysis of Mass Spectrometry Proteomics data. He mainly does this through algorithmic development, implementation and application of machine learning methods.

Alexander Suh

Genomics of germline/soma genome differences

Uppsala University, University of East Anglia

Alex is a lecturer at the University of East Anglia (UK) and group leader at Uppsala University. His research group focuses on understanding evolution of animal genomes from the perspective of transposable elements, endogenous viruses, and germline-restricted chromosomes.

Carina Farah Mugal

Integration of population genomic and phylogenomic analysis - theory and applications

Uppsala University

Carina is a researcher at Uppsala University. Her research group focuses on fundamental questions of molecular evolution, such as understanding the molecular mechanisms that cause mutations in the genome sequence of an individual and the evolutionary forces that determine the fate of novel mutations over evolutionary time. Their research approach can be characterized as a multi-disciplinary approach, that is a combination of mathematical modeling, methodological developments and genomic data analysis.

Charlie Cornwallis

Understanding the emergence of biological organisation at different levels of life

Lund University

Charlie is an Associate Professor in Evolutionary Biology at Lund University. His group focuses on understanding the evolution of complex life. Throughout the history of earth, the complexity of life has changed through a series of major evolutionary transitions. For example, transitions to multicellularity, the formation of animal societies, and the establishment of obligate symbiotic relationships have all played fundamental roles in the development of life. His research group aims to understand how and why some organisms undergo transitions in complexity while others do not, and what the consequences are for patterns of biodiversity.

Christian Brueffer

Sponsor talk

SAGA Diagnostics

Christian earned his MSc and PhD in Bioinformatics and Cancer Genomics at Lund University, working on RNA-seq-based breast cancer diagnostics. Before moving to Sweden he completed his BSc in Scientific Programming in Germany, and worked in software engineering positions in the mechanical engineering and geomonitoring areas in Germany and Switzerland. He now works as Senior Bioinformatician at SAGA Diagnostics–a Lund University spin-out company working on ultra-sensitive cancer diagnostics. In addition to his education and research, Christian has been active in the open source software community for 20 years, first primarily working on the FreeBSD operating system, then also on open source bioinformatics and reproducible research infrastructure projects such as conda-forge, Bioconda, and Biopython.

Jonathan Robinson

Career panel

BioInnovation Institute

Jonathan received a PhD in Chemical & Biological Engineering from Princeton University in 2016, after which he joined Jens Nielsen’s group at Chalmers University as a postdoctoral researcher. He later joined National Bioinformatic Infrastructure Sweden (NBIS) as a bioinformatician until 2021 when he began his current position as a Scientific Data Developer at the BioInnovation Institute (BII) in Copenhagen. At BII, Jonathan is helping to establish their digital infrastructure, which aims to support early-stage life science start-ups with bioinformatic or other data management needs.

Karin Engström

Lund University Bioinformatics Infrastructure (LUBI)

Karin Engström is the coordinator for Lund University Bioinformatics Infrastructure (LUBI) and will here have a brief presentation of LUBI and its activities.

Kristiina Ausmees

Deep learning for characterization of genotype data

Uppsala University

Kristiina is a PhD student at the dept. of IT at Uppsala University, working on an interdisciplinary project where scientific computing is applied in the study of human evolutionary and demographic history. Her main focus is on computational methods for genetic inference and their application to ancient human DNA; designing new methods and adapting existing ones to the context of highly sparse and uncertain data. Her current focus lies in investigating the use of deep learning methods on genotype data, with applications including dimensionality reduction, genetic clustering as well as the study of quantitative traits.

Lokeshwaran Manoharan

Career panel

NBIS

Lokesh did his PhD in soil microbial ecology followed by a postdoc in Archaea evolution. He has a general research interest in microbial genomic ecology and evolution. Currently he is working on different scientific questions as a Bioinformatics expert for NBIS at Lund University in Lund, Sweden. Lokesh will be one of four professionals in the SBW2021 career panel organized by RSG-Sweden.

Marija Cvijovic

Career panel

Chalmers University of Technology and University of Gothenburg

Marija is a professor and group leader in systems biology at the University of Gothenburg. The driving force of her research group is answering fundamental biological questions: why and how we age. The group is approaching these questions by studying aging in unicellular organisms focusing on damage accumulation, metabolism, and nutrient signaling. We are developing both dynamic (ODE and PDE) and Boolean models as well as methods for model selection together with experimental and theoretical methods for collecting and analyzing data on the single-cell level.

Mihail Anton

Sponsor talk

NBIS

Mihail has a background in software development and computer science enabled him to purse a growing scientific interest in protein structures and surfaces, which materialized in working for a research project, and later in his master’s thesis. His scientific interest has expanded to include systems biology when he started working in the space of genome-scale metabolic models. Currently, his main activities are to project manage and lead the development of Metabolic Atlas with Vue.js, Neo4j, Docker, GitHub and Jira.

Paul Franks

Combining multidimensional, individual level data to predict person-specific blood glucose responses to meals

Lund University

Paul Franks is currently the Scientific Director in Clinical Science at the Novo Nordisk Foundation where he is responsible for the precision medicine portfolio. Since 2010, Paul has also been a Professor in Genetic Epidemiology at Lund University Diabetes Center in Sweden and an Adjunct Professor at Harvard Chan School of Public Health in Boston. He was deputy-director of Lund University Diabetes Center from 2016-2021. Paul trained in epidemiology, biostatistics and genetics at the University of Cambridge and the US National Institutes of Health. He co-chairs the ADA/EASD Precision Medicine in Diabetes Initiative. His research focuses on precision diabetes medicine, with special emphasis on lifestyle, having published >400 papers on related topics and with an H-index >100.

Phil Ewels

Reproducible bioinformatics workflows with nf-core

National Genomics Infrastructure, Science for Life Laboratory

Phil Ewels is the Team Leader for Bioinformatics development at the National Genomics Infrastructure (NGI) at SciLifeLab in Stockholm, Sweden. SciLifeLab is a national centre for molecular biosciences for Sweden; the NGI is the largest platform at SciLifeLab. We provide DNA library preparation, sequencing and bioinformatics analysis support for research groups across the country. He and his team focus on the development and scaling up of new lab protocols and bioinformatics solutions for the ISO accredited NGI Genomics Production facility. They develop new analysis pipelines and try to ensure that the tools they write are scalable, reproducible and transferable.

Phil has been working at SciLifeLab for seven years and moved to Sweden after a PhD and postdoc at the University of Cambridge and Babraham Institute in Cambridge, UK. He has has a history of lab and bioinformatics work in epigenetics and has a soft spot for software development with a focus on user friendliness. He is the co-founder of the nf-core community building best-practice Nextflow analysis pipelines and is the author of MultiQC, SRA-Explorer, QCFail.com and several other pet projects.

Sonja Aits

AI for biomedical text and image analysis

Lund University

Sonja’s group studies the molecular regulation of cell death and lysosomes and their role in various diseases (especially neurodegenerative diseases, lysosomal storage disorders, stroke and cancer) with the aim of finding new treatments. For this, they combine basic cell biology, model organism work, clinical aspects, bioimaging, structural biology and different forms of computational science.

Sophia Zackrisson

Screening for breast cancer - approaches for the future

Lund University

Prof. Zackrisson is Professor of Radiology at Lund University and senior consultant radiologist at Skåne University Hospital Malmö, Sweden. She has a PhD in Epidemiology with a thesis on mammography screening. In 2011 she was visiting scholar at Stanford University, CA, USA, focusing on molecular imaging and magnetic resonance imaging. One of her largest clinical and epidemiological studies as a PI is the Malmö Breast Tomosynthesis Screening Trial. Further research and clinical interests are colorectal and prostate cancer and metastatic disease. Prof. Zackrisson is chair of the Swedish Society of Breast Imaging, chair of the Swedish Translational Research in Breast Cancer and executive board member of European Society of Breast Imaging since 2017. She is author of numerous scientific papers and book chapters. In 2020 she was named “Cancer Researcher of the Year” by the Swedish Cancer Society for her contributions in cancer imaging.

Stefan Larsson

Associate Professor in Technology and Social Change, Senior lecturer, Department of Technology and Society

Stefan Larsson is a senior lecturer and Associate Professor in Technology and Social Change at Lund University, Sweden, Department of Technology and Society. He will present the SBW sponsor AI Lund.

Ufuk Kirik

Career panel

AstraZeneca

Ufuk is a Lund University alumni from the Engineering Mathematics Program at LTH. Being drawn into the field of bioinformatics in connection with his MSc thesis project, he carried on with research at Lund University in the Dept of Immunotechnology working on mass-spectrometry proteomics data. There he published papers both on method development and data science application into cancer proteomics. After a short project working on NGS data and antibodies following his PhD, he relocated to Novo Nordisk Foundation Center for Protein Research, where he stayed for 3 years as a postdoc working with phosphoproteomics data, as well as text-mining and systems biology. Currently Ufuk is working at the Quantitative Biology Unit at AstraZeneca in Mölndal, working on applying graph data science methods on different phases of the drug discovery process.