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Home>Research>Subarea 5: Computational and Systems Biology of Aging
Research focus of Subarea 5.

Subarea 5: Computational and Systems Biology of Aging

Subarea 5 focuses on the development of methods to analyse and understand complex biological systems. This work includes the design of computer algorithms and biostatistical approaches as well as the development of novel Omic strategies (i.e. genomics/epigenomics, transcriptomics, proteomics, and metabolomics) to study aging and aging-related diseases. According to the FLI, due to the Subarea's expertise in computational data analysis, it is deeply interconnected with all other Subareas. The Subarea hosts two critical core facilities (Life Science Computing, Proteomics) and provides consulting services in statistics. Furthermore, it organizes courses on data analysis and statistics.

The research is defined by five focus areas:

  • Mapping extrinsic and intrinsic factors influencing stem cells during aging,
  • Integration of spatiotemporal proteomics and transcriptomics data,
  • Comprehensive evaluation of qualitative and quantitative expression changes,
  • Identification and analysis of epigenomic alterations during aging and age-related diseases, and
  • Network analysis of genomic, transcriptomic and epigenomic alterations during aging.

Research focus of Subarea 5.

The biology of aging can be viewed as a multilayered array of networks at the level of organs, cells, molecules, and genes. The FLI wants to meet this complexity by establishing the new Subarea on “Computational and Systems Biology of Aging”. The overall goal is to interconnect research at different scales, taking place in Subareas 1-4 of the Institute’s research program. The new group on Systems Biology will integrate data from networks at multiple scales and will thus point to mechanisms and interactions that would not be seen in unilayer approaches.

Publications

(since 2016)

2024

  • An artificial intelligence-assisted clinical framework to facilitate diagnostics and translational discovery in hematologic neoplasia.
    Tang M, Antić Ž, Fardzadeh P, Pietzsch S, Schröder C, Eberhardt A, van Bömmel A, Escherich G, Hofmann W, Horstmann MA, Illig T, McCrary JM, Lentes J, Metzler M, Nejdl W, Schlegelberger B, Schrappe M, Zimmermann M, Miarka-Walczyk K, Patsorczak A, Cario G, Renard BY, Stanulla M, Bergmann AK
    EBioMedicine 2024, 104, 105171
  • SEPTIN10-mediated crosstalk between cytoskeletal networks controls mechanotransduction and oncogenic YAP/TAZ signaling.
    Weiler SME, Bissinger M, Rose F, von Bubnoff F, Lutz T, Ori A, Schirmacher P, Breuhahn K
    Cancer Lett 2024, 584, 216637

2023

  • Author Correction: Disruption of chromatin folding domains by somatic genomic rearrangements in human cancer.
    Akdemir KC, Le VT, Chandran S, Li Y, Verhaak RG, Beroukhim R, Campbell PJ, Chin L, Dixon JR, Futreal PA, PCAWG Structural Variation Working Group, PCAWG Consortium
    Nat Genet 2023, 55(6), 1079
  • Author Correction: The repertoire of mutational signatures in human cancer.
    Alexandrov LB, Kim J, Haradhvala NJ, Huang MN, Tian Ng AW, Wu Y, Boot A, Covington KR, Gordenin DA, Bergstrom EN, Islam SMA, Lopez-Bigas N, Klimczak LJ, McPherson JR, Morganella S, Sabarinathan R, Wheeler DA, Mustonen V, PCAWG Mutational Signatures Working Group, Getz G, Rozen SG, Stratton MR, PCAWG Consortium
    Nature 2023, 614(7948), E41
  • Recurrent DNMT3B rearrangements are associated with unfavorable outcome in dicentric (9;20)-positive pediatric BCP-ALL.
    Antić Ž, van Bömmel A, Riege K, Lentes J, Schröder C, Alten J, Eckert C, Fuhrmann L, Steinemann D, Lenk L, Schewe DM, Zimmermann M, Schrappe M, Schlegelberger B, Cario G, Hoffmann S, Bergmann AK
    Leukemia 2023, 37(12), 2522-5
  • Human NMDAR autoantibodies disrupt excitatory-inhibitory balance, leading to hippocampal network hypersynchrony.
    Ceanga M, Rahmati V, Haselmann H, Schmidl L, Hunter D, Brauer AK, Liebscher S, Kreye J, Prüss H, Groc L, Hallermann S, Dalmau J, Ori A, Heckmann M, Geis C
    Cell Rep 2023, 42(10), 113166
  • Genetic separation of chronic myeloid leukemia stem cells from normal hematopoietic stem cells at single-cell resolution.
    Chen Y, Möbius S, Riege K, Hoffmann S, Hochhaus A, Ernst* T, Rudolph* KL
    Leukemia 2023, 37(7), 1561-6 * equal contribution
  • Author Correction: Comprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing.
    Cortés-Ciriano I, Lee JJK, Xi R, Jain D, Jung YL, Yang L, Gordenin D, Klimczak LJ, Zhang CZ, Pellman DS, PCAWG Structural Variation Working Group, Park PJ, PCAWG Consortium
    Nat Genet 2023, 55(6), 1076
  • Integrated omics approaches to study protein complexes in neuronal differentiation and brain aging
    Di Fraia D
    Dissertation 2023, Jena, Germany
  • Impaired biogenesis of basic proteins impacts multiple hallmarks of the aging brain
    Di Fraia* D, Marino* A, Ho Lee* J, Kelmer Sacramento E, Baumgart M, Bagnoli S, Tomaz da Silva P, Kumar Sahu A, Siano G, Tiessen M, Terzibasi-Tozzini E, Gagneur J, Frydman** J, Cellerino** A, Ori** A
    bioRxiv 2023, 10.1101/2023.07.20.549210 * equal contribution, ** co-corresponding authors