Author Kramer, Frank

• 2014 | Conference Paper
  ​ ​Abstract 247: A functional genomics and a systems biology approach identify POMP as a potential therapeutic target for colorectal cancer​
  Camps, J.; Hummon, A. H.; Emons, G.; Kramer, F.; Pitt, J. J.; Grade, M. & Nguyen, Q. T. et al.​ (2014)
  pp. 247​-247. ​Proceedings: AACR 101st Annual Meeting 2010‐‐ Apr 17‐21, 2010; Washington, DC​
  American Association for Cancer Research. DOI: https://doi.org/10.1158/1538-7445.AM10-247 
  ​Details  DOI 

• 2016 | Journal Article
  ​ ​Building pathway graphs from BioPAX data in R​
  Benis, N.; Schokker, D.; Kramer, F.; Smits, M. A. & Suarez-Diez, M.​ (2016) 
  F1000Research, 5 pp. 2414​.​ DOI: https://doi.org/10.12688/f1000research.9582.2 
  ​Details  DOI 

• 2016 | Book Chapter
  ​ ​Reconstruction of Protein Networks Using Reverse-Phase Protein Array Data​
  von der Heyde, S.; Sonntag, J.; Kramer, F.; Bender, C.; Korf, U.& Beißbarth, T. ​ (2016)
  In: Statistical Analysis in Proteomics pp. 227​-246.  DOI: https://doi.org/10.1007/978-1-4939-3106-4_15 
  ​Details  DOI  PMID  PMC 

• 2016 | Journal Article | 
  ​ ​Prognostic Value of MicroRNAs in Preoperative Treated Rectal Cancer​
  Azizian, A.; Epping, I.; Kramer, F.; Jo, P.; Bernhardt, M.; Kitz, J. & Salinas, G. et al.​ (2016) 
  International Journal of Molecular Sciences, 17(4) art. 568​.​ DOI: https://doi.org/10.3390/ijms17040568 
  ​Details  DOI  PMID  PMC  WoS 

• 2019 | Journal Article | 
  ​ ​The histone methyltransferase DOT1L is required for proper DNA damage response, DNA repair, and modulates chemotherapy responsiveness​
  Kari, V.; Raul, S. K; Henck, J. M; Kitz, J.; Kramer, F.; Kosinsky, R. L & Übelmesser, N. et al.​ (2019) 
  Clinical Epigenetics, 11(1) art. 4​.​ DOI: https://doi.org/10.1186/s13148-018-0601-1 
  ​Details  DOI 

• 2019 | Book Chapter
  ​ ​Utilizing Molecular Network Information via Graph Convolutional Neural Networks to Predict Metastatic Event in Breast Cancer​
  Chereda, H.; Bleckmann, A.; Kramer, F.; Leha, A.& Beißbarth, T. ​ (2019)
  In: Utilizing Molecular Network Information via Graph Convolutional Neural Networks to Predict Metastatic Event in Breast Cancer pp. 181​-186.  DOI: https://doi.org/10.3233/SHTI190824 
  ​Details  DOI  PMID  PMC 

• 2021 | Journal Article | 
  ​ ​Explaining decisions of graph convolutional neural networks: patient-specific molecular subnetworks responsible for metastasis prediction in breast cancer​
  Chereda, H.; Bleckmann, A.; Menck, K.; Perera-Bel, J.; Stegmaier, P.; Auer, F. & Kramer, F. et al.​ (2021) 
  Genome Medicine, 13(1) art. 42​.​ DOI: https://doi.org/10.1186/s13073-021-00845-7 
  ​Details  DOI 

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