Research at Systems Biology and Epigenetics group

Our research focuses on molecular systems biology, applying methodologies like epigenomics and transcriptomics together with cutting-edge data analysis and integration techniques, including statistical methods, machine learning, and network-based approaches. Our interdisciplinary research projects usually combine both experimental laboratory work and computational biology approaches. More specifically we are working on:

Epigenomics / Network Reconstruction

Most of the experimental and computational tools we are developing are applicable to a wide range of biological systems and processes.

Ongoing more general work in the different applications comprises:

• Genome-wide Epigenomics / Transcriptomics approaches like RNA-seq, ChIP-seq, (single nuclei) ATAC-seq, Multiome ATAC+RNA analysis, CUT&Tag, Low-C, and nanopore sequencing, including downstream data analysis (Epigenetics team led by Dr. Lasse Sinkkonen)
• Gene regulatory network reconstruction via integration of transcriptomic and epigenomic data (30544251, 38177910)
• Metabolic network reconstruction  (24453953, 36557249, 31126892, 26834640, 26480823, 26615025): FASTCORE algorithms
• Multiscale metabolic modelling  (26904548, 30787451)
• Signalling network reconstruction / Fast contextualisation of logical networks (28673016, 29872402, 23815817, 24983623): FALCON toolbox

Network Analysis / Machine Learning:

Once large-scale data are integrated in a network or machine learning model, these can be analysed for systemic features and experimental design:

• Data Mining of human cohort data & Disease Risk Stratification (33244054)
• Metabolic network based Drug Repositioning  (31126892, 32369553)
• Signalling network based Drug Target Identification (30416750, 30323272)
• Identification of Key Transcription Factors and Reprogramming Determinants (38177910, 30544251, 34686322, 34503558, AlgoReCell, GENERIC)
• Integrated analysis of transcript-level regulation of metabolism (26480823, 24198249, IHEC)

Cancer specific Molecular Networks / Drug Discovery:

By reconstructing and analysing cancer and subtype specific molecular networks, data integration is achieved, and specific drug discovery is enabled, ultimately aiming for personalized treatment. A specific interest lays in drug repositioning of established drugs for novel use in cancer treatment. We are contributing to fight:

• Melanoma (37495601, 30416750, 32410672, 30323272, 30240588, 24675998, 22815735, 35022419)
• Colorectal cancer (31126892, 31042485)
• Head and Neck cancer  (31308358, 30142511)
• Breast cancer (26631483)

Epigenetic Regulation in Cellular Differentiation and Disease

The research focus of the Epigenetics team is understanding gene regulation and epigenetic mechanisms that determine cell identity in differentiation and disease in mammalian cells. We use in vitro cell culture systems, human cell types derived from induced pluripotent stem cells and primary cells from human and mouse tissues to apply genome-wide epigenomics approaches like RNA-seq, ChIP-seq, CUT&Tag, Lo-C, single nuclei ATAC+RNA-seq, and nanopore sequencing to study how cells differentiate and maintain their identity. We focus on gene control at the chromatin level and how this is perturbed in disease states like Parkinson’s disease and cancer, for example through regulatory genetic variation, changes in gene regulatory networks, or altered activity of chromatin modifiers. Through collaborative projects also other model organisms such as budding yeast are being studied.

• Epigenetic control of cell identity and differentiation (38177910, 34686322, 34503558 30544251, 24457907, 31044623, GENERIC)
• Non-coding regulatory variation in complex traits and diseases (34503558, 34453370, 32248367, 33173537, 31621607, 26338775)
• Interplay of metabolism and epigenetic regulation (38011998, 36848289, 35892629, 24198249)