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Dimitrios Kleftogiannis's picture

Dimitrios Kleftogiannis

Postdoctoral Fellow

I am working on the development and application of computational approaches to tackle emerging problems in cancer research. I have particular experience in the analysis of cancer genomic (NGS) data from liquid biopsies, in identifying and characterizing genomic alterations, with applications in cancer therapeutics and precision oncology. I have also expertise on the analysis of CyTOF datasets to characterise cellular features with single cell-resolution. During my research career, I have successfully applied different machine learning techniques in biomarker discovery studies, in gene regulation studies, and in identifying and characterising DNA regulatory elements such as enhancers, promoters and microRNAs. I have also particular expertise in big data integration from multi-omics technologies (genomic, transcriptomic, proteomic and epigenomic), and I am specialist in facilitating biological discoveries using high performance computing (HPC) systems. I have worked in different institutes worldwide, and I have demonstrated dedicated commitment towards working with undergraduate, graduate and research fellows with multidisciplinary scientific backgrounds.

Academic article
  • Show author(s) (2020). Genome-wide plasma DNA methylation features of metastatic prostate cancer. Journal of Clinical Investigation.
  • Show author(s) (2020). Detection of genomic alterations in breast cancer with circulating tumour DNA sequencing. Scientific Reports.
  • Show author(s) (2020). Circulating Tumour DNA Sequencing Identifies a Genetic Resistance-Gap in Colorectal Cancers with Acquired Resistance to EGFR-Antibodies and Chemotherapy. Cancers.

More information in national current research information system (CRIStin)

 

  1. Zhu G, Guo A, [...], Kleftogiannis D, [...] and Anders Skanderup, Tissue-specific cell-free DNA degradation quantifies circulating tumor DNA burden, Nature Communications, (2021), doi: https://doi.org/10.1038/s41467-021-22463-y
  2. Knebel F, Barber L , Newey A, Kleftogiannis D, [...] and Gerlinger M, Circulating Tumour DNA Sequencing Identifies a Genetic Resistance-Gap in Colorectal Cancers with Acquired Resistance to EGFR-Antibodies and Chemotherapy, Cancers, (2020),doi: 10.3390/cancers12123736.
  3. Kleftogiannis D, Ho D, […], and Ng S, Detection of genomic alterations in breast cancer with circulating free DNA sequencing, Scientific Reports, (2020), doi: 10.1038/s41598-020-72818-6.
  4. Wu A, Cremaschi P, […], Kleftogiannis D, […] and Attard G, The plasma methylome of metastatic prostate cancer, Journal of Clinical Investigation, (2020), doi: 10.1172/JCI130887.
  5. Massoti C, Knebel F, […], Kleftogiannis D and Bettoni F, Detection of ESR1 mutations in plasma cell-free DNA from metastatic ER-positive breast cancer patients resistant to hormone therapy, Clinical Cancer Research, AACR, (2020), doi: 10.1158/1557-3265.LiqBiop20-A19
  6. Yogev O, Almedia G, [...], Kleftogiannis D, [...], and Chesler L, In vivo modelling of chemo-resistant neuroblastoma provides new insights into chemo-refractory disease and metastatic progression, Cancer Research, (2019) ,doi:10.1158/0008-5472.CAN-18-2759.
  7. Kleftogiannis D, Punta M, […], Lise S, Identification of single nucleotide variants using position-specific error estimation in deep sequencing data, BMC Medical Genomics, (2019), doi: 10.1186/s12920-019-0557-9.
  8. Kleftogiannis D, Ashoor A, Bajic VB. TELS: a novel computational framework for identifying motif signatures of transcribed enhancers, Genomics, Proteomics & Bioinformatics, (2018), doi.org/10.1016/j.gpb.2018.05.003.
  9. Mansukhani S, Barber L, Kleftogiannis D, […] and Gerlinger M, Ultra-sensitive mutation detection and genome-wide DNA copy number reconstruction by error corrected circulating tumor DNA sequencing, Clinical Chemistry (2018), doi: 10.1373/clinchem.2018.289629.
  10. Kleftogiannis D, Kalnis P, Arner E, Bajic VB. Discriminative identification of promoters and enhancers transcriptional responses after stimulus, Nucleic Acids Research (2016), doi: 10.1093/nar/gkw1015.
  11. Kleftogiannis D, Kalnis P, Bajic VB. Progress and challenges in bioinformatics approaches for enhancer identification, Briefings in Bioinformatics (2015), doi:  10.1093/bib/bbv101.
  12. Ashoor A, Kleftogiannis D, Radovanovic A, Bajic VB. DENdb: Database of integrated human enhancers, Database: The journal of Biological Database and Curation (2015), doi:10.10.93/database/bav085.
  13. Kleftogiannis D, Wong L, Archer JA, Kalnis P. Hi-Jack: a novel computational framework for pathway-based inference of host-pathogen interactions, Bioinformatics (2015), doi: 10.1093/bioinformatics/btv138.
  14. Soufan O, Kleftogiannis D, Kalnis P, Bajic VB. DWFS: Feature selection with a parallel genetic algorithm. PloS ONE (2015), doi: 10.1371/journal.pone.0117988.
  15. Kleftogiannis D, Theofilatos K, Lykothanasis S, Mavroudi S. YamiPred: A novel evolutionary method for predicting pre-miRNAs and selecting relevant features, IEEE/ACM Transactions on Computational Biology and Bioinformatics (2015), doi: 10.1109/TCBB.2014.2388227.
  16. Korfiati A, Theofilatos K, Kleftogiannis D, et al. Predicting Human miRNA Target Genes Using a Novel Computational Intelligent Framework, Information Sciences (2015), doi: 10.1016/j.ins.2014.09.016.
  17. Karathanou K, Theofilatos K, Kleftogiannis D, et al. ncRNAclass: A Web Platform for Non-Coding RNA Feature Calculation and MicroRNAs and Targets Prediction, International Journal on Artificial Intelligence Tools (2015), https://doi.org/10.1142/S0218213015400023.
  18. Kleftogiannis D, Kalnis P, Bajic VB, DEEP: A general computational framework for predicting enhancers, Nucleic Acids Research (2014), doi: 10.1093/nar/gku1058.
  19. Rapakoulia T, Theofilatos K, Kleftogiannis D, et al. EnsembleGASVR: A novel ensemble method for classifying missense Single Nucleotide Polymorphisms, Bioinformatics (2014), doi: 10.1093/bioinformatics/btu297.
  20. Theofilatos K, Dimitrakopoulos C, Likothanassis S, Kleftogiannis D, et al. The Human Interactome Knowledge Base (HINT-KB): an integrative human protein interaction database enriched with predicted protein–protein interaction scores using a novel hybrid technique, Artificial Intelligence Review (2014), doi: 10.1007/s10462-013-9409-8.
  21. Kleftogiannis D, Korfiati A, Theofilatos K, et al. Where we stand, where we are moving: Surveying computational techniques for identifying miRNA genes and uncovering their regulatory role. Journal of Biomedical Informatics (2013), doi: 10.1016/j.jbi.2013.02.002.
  22. Kleftogiannis D, Kalnis P, Bajic VB. Comparing Memory-Efficient Genome Assemblers on Stand-Alone and Cloud Infrastructures. PLoS ONE (2013), doi:10.1371/journal.pone.0075505.
  23. Kleftogiannis D, Theofilatos K, Papadimitriou S, et al. ncRNA-Class web tool: non-coding RNA feature extraction and pre-miRNA classification web tool, Artificial Intelligence Applications and Innovations (2012), doi:10.1007/978-3-642-33412-2_65.

My main project is titled "Improved Treatments of Acute Myeloid Leukaemias by Personalised Medicine (AML_PM)" funded by ERAPerMed.

It is a joint collaborative effort between University of Bergen (CBU and Helse Bergen Haukeland University Hospital), University of Groningen , German Cancer Research Center (DKFZ), University of Freiburg, and Princess Margaret Cancer Centre in Canada.