My Google Scholar profile contains a manually curated list of my publications and patents.

Patents

  1. Oligonucleotides for modulating RTEL1 expression. (2020)
  2. Pyrrolo[2,3-b]pyrazine compounds as cccDNA inhibitors for the treatment of Hepatitis B Virus (HBV) infection. (2018)

Book chapters

  1. Edited by Adetayo Kasim, S. H., Ziv Shkedy, Sebastian Kaiser & Talloen, W. Applied Biclustering Methods for Big and High-Dimensional Data Using R (Chapman & Hall/CRC Biostatistics Series). Chapman and Hall/CRC (2016). (Publisher’s Link, Amazon).

Preprints

  1. Gatti, L. et al. Cross-reactive immunity drives global oscillation and opposed alternation patterns of seasonal influenza A viruses (2017).
  2. Fang, T., Davydov, I., Marbach, D. & Zhang, J. D. Gene-set enrichment with regularized regression (2019).
  3. Mädler, S. et al. Besca, a single-cell transcriptomics analysis toolkit to accelerate translational research (2020).

Peer-reviewed publications

2020
  1. Roudnicky, F. et al. Inducers of the endothelial cell barrier identified through chemogenomic screening in genome-edited hPSC-endothelial cells. Proceedings of the National Academy of Sciences (2020)
  2. Gutbier, S. et al. Large-Scale Production of Human iPSC-Derived Macrophages for Drug Screening. International Journal of Molecular Sciences (2020)
  3. Zaidan, M. et al. Signaling pathways predisposing to chronic kidney disease progression. JCI Insight (2020)
  4. Badillo, S. et al. An Introduction to Machine Learning. Clinical Pharmacology & Therapeutics (2020).
2019
  1. Zhang, J. D., Sach-Peltason, L., Kramer, C., Wang, K. & Ebeling, M. Multiscale modelling of drug mechanism and safety. Drug Discovery Today (2019).
  2. Sturm, G. et al. Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics 35, i436–i445 (2019).
  3. Roudnicky, F. et al. Modeling the Effects of Severe Metabolic Disease by Genome Editing of hPSC-Derived Endothelial Cells Reveals an Inflammatory Phenotype. International Journal of Molecular Sciences 20, 6201 (2019).
  4. Choobdar, S. et al. Assessment of network module identification across complex diseases. Nature Methods 16, 843–852 (2019).
2018
  1. Mueller, H. et al. A novel orally available small molecule that inhibits hepatitis B virus expression. Journal of Hepatology 68, 412–420 (2018).
2017
  1. Zhang, J. D. et al. Detect tissue heterogeneity in gene expression data with BioQC. BMC Genomics 18, 277 (2017).
  2. Moisan, A. et al. Inhibition of EGF Uptake by Nephrotoxic Antisense Drugs In Vitro and Implications for Preclinical Safety Profiling. Molecular Therapy-Nucleic Acids 6, 89–105 (2017).
  3. Drawnel, F. M. et al. Molecular Phenotyping Combines Molecular Information, Biological Relevance, and Patient Data to Improve Productivity of Early Drug Discovery. Cell Chemical Biology 24, 624–634 (2017).
  4. Boess, F. et al. Use of early phenotypic in vivo markers to assess human relevance of an unusual rodent non-genotoxic carcinogen in vitro. Toxicology 379, 48–61 (2017).
2016
  1. Raza, U. et al. The miR-644a/CTBP1/p53 axis suppresses drug resistance by simultaneous inhibition of cell survival and epithelial-mesenchymal transition in breast cancer. Oncotarget (2016).
  2. Grabole, N. et al. Genomic analysis of the molecular neuropathology of tuberous sclerosis using a human stem cell model. Genome Medicine 8, 94 (2016).
2015
  1. Zhang, J. D., Küng, E., Boess, F., Certa, U. & Ebeling, M. Pathway reporter genes define molecular phenotypes of human cells. BMC Genomics 16, 342 (2015).
  2. Xu, J. et al. 14-3-3$\zeta$ turns TGF-$\beta$’s function from tumor suppressor to metastasis promoter in breast cancer by contextual changes of Smad partners from p53 to Gli2. Cancer Cell 27, 177–192 (2015).
  3. van der Vries, E. et al. Outcomes and susceptibility to neuraminidase inhibitors in individuals infected with different influenza B lineages: the influenza resistance information study. The Journal of Infectious Diseases 213, 183–190 (2015).
  4. Moisan, A. et al. White-to-brown metabolic conversion of human adipocytes by JAK inhibition. Nature Cell Biology 17, 57–67 (2015).
  5. Lenz, N. et al. Antiviral Innate Immune Activation in HIV-Infected Adults Negatively Affects H1/IC31-Induced Vaccine-Specific Memory CD4+ T Cells. Clinical and Vaccine Immunology 22, 688–696 (2015).
  6. Haller, F. et al. Combined DNA methylation and gene expression profiling in gastrointestinal stromal tumors reveals hypomethylation of SPP1 as an independent prognostic factor. International Journal of Cancer 136, 1013–1023 (2015).
2014
  1. Zhang, J. D., Schindler, T., Küng, E., Ebeling, M. & Certa, U. Highly sensitive amplicon-based transcript quantification by semiconductor sequencing. BMC Genomics 15, 565 (2014).
  2. Zhang, J., Berntenis, N., Roth, A. & Ebeling, M. Data mining reveals a network of early-response genes as a consensus signature of drug-induced in vitro and in vivo toxicity. The Pharmacogenomics Journal 14, 208–216 (2014).
  3. Yuk, I. H. et al. Effects of copper on CHO cells: insights from gene expression analyses. Biotechnology Progress 30, 429–442 (2014).
  4. Rehman, S. K. et al. 14-3-3$\zeta$ Orchestrates Mammary Tumor Onset and Progression via miR-221–Mediated Cell Proliferation. Cancer Research 74, 363–373 (2014).
  5. Raza, U., Zhang, J. D. & Sahin, Ö. MicroRNAs: master regulators of drug resistance, stemness, and metastasis. Journal of Molecular Medicine 92, 321–336 (2014).
  6. Aigner, S., Heckel, T., Zhang, J. D., Andreae, L. C. & Jagasia, R. Human pluripotent stem cell models of autism spectrum disorder: emerging frontiers, opportunities, and challenges towards neuronal networks in a dish. Psychopharmacology 231, 1089–1104 (2014).
2013
  1. Ward, A. et al. Re-expression of microRNA-375 reverses both tamoxifen resistance and accompanying EMT-like properties in breast cancer. Oncogene 32, 1173–1182 (2013).
  2. Horvát, E.-Á., Zhang, J. D., Uhlmann, S., Sahin, Ö. & Zweig, K. A. A network-based method to assess the statistical significance of mild co-regulation effects. PLOS One 8, e73413 (2013).
  3. Adam, L. et al. Plasma microRNA profiles for bladder cancer detection. Urologic Oncology: Seminars and Original Investigations vol. 31 1701–1708 (Elsevier, 2013).
2012
  1. Ward, A. et al. Abstract A14: Re-expression of microRNA-375 reverses both tamoxifen resistance and accompanying EMT-like properties in breast cancer. Clinical Cancer Research 18, A14–A14 (2012).
  2. Uhlmann, S. et al. Global miRNA regulation of a local protein network: Case study with the EGFR-driven cell cycle network in breast cancer. Molecular Systems Biology 8, 570 (2012).
  3. Keklikoglou, I. et al. MicroRNA-520/373 family functions as a tumor suppressor in estrogen receptor negative breast cancer by targeting NF-kappaB and TGF-ß signaling pathways. Oncogene 31, 4150 (2012).
  4. Jurmeister, S. et al. MicroRNA-200c represses migration and invasion of breast cancer cells by targeting actin-regulatory proteins FHOD1 and PPM1F. Molecular and Cellular Biology 32, 633–651 (2012).
2011
  1. Zhang, J. D. et al. Time-resolved human kinome RNAi screen identifies a network regulating mitotic-events as early regulators of cell proliferation. PLOS One 6, e22176 (2011).
2010
  1. Uhlmann, S. et al. miR-200bc/429 cluster targets PLC$\gamma$1 and differentially regulates proliferation and EGF-driven invasion than miR-200a/141 in breast cancer. Oncogene 29, 4297–4306 (2010).
  2. Haller, F. et al. Localization-and mutation-dependent microRNA (miRNA) expression signatures in gastrointestinal stromal tumours (GISTs), with a cluster of co-expressed miRNAs located at 14q32. 31. The Journal of Pathology 220, 71-86 (2010).
2009
  1. Zhang, J. D. & Wiemann, S. KEGGgraph: a graph approach to KEGG PATHWAY in R and Rioconductor. Bioinformatics 25, 1470-1471 (2009).