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C1  Feature selection in high dimensional data for risk prognosis in oncology


lee.jpg
Dr. Lee, Sangkyun
Rahmann.JPG
Prof. Dr. Rahmann, Sven
Schramm.JPG
Prof. Dr. Schramm, Alexander
Reliable interpretation of very high-dimensional data with limited sample size is and remains a yet unsolved challenge for machine learning and data analysis. Robustness of feature selection and prediction is an important consideration. The long-term goal is to generate reliable prediction models for precise definition of patient risk in oncology using neuroblastoma, a common solid tumor of childhood, as a model. We will now proceed to develop probabilistic graphical models on the basis of next generation sequencing data and other high-throughput data not only for better interpretability of feature selection but also to analyze tumor development over different time points.

Project management:

Dr. Lee, Sangkyun
Prof. Dr. Rahmann, Sven
Prof. Dr. Schramm, Alexander

Project members:

Hess, Sibylle
Schulte, Marc
Timm, Henning

Alumni project management:


Morik.JPG
Prof. Dr. Morik, Katharina

Alumni:

D'Addario, Marianna
Dr. Fielitz, Kathrin
Dr. Koester, Johannes
Dr. Lee, Sangkyun
Schowe, Benjamin
Dr. Schwermer, Melanie

Software:

Optimization Plugin for RapidMiner
RapidMiner Feature Selection Extension
Spatio-Temporal Random Fields (STRF)
rsig: Robust Signature Selection for Survival Outcomes

Publications:

Kliewer/Lee/2016a Kliewer, Viktoria and Lee, Sangkyun. EasyTCGA: An R package for easy batch downloading of TCGA data from FireBrowse. No. 4, TU Dortmund, 2016.


Lee/etal/2016a Lee, Sangkyun and Brzyski, Damian and Bogdan, Malgorzata. Fast Saddle-Point Algorithm for Generalized Dantzig Selector and FDR Control with the Ordered l1-Norm. In Arthur Gretton and Christian C. Robert (editors), Proceedings of the 19th International Conference on Artificial Intelligence and Statistics (AISTATS), pages 780--789, JMLR W&CP, 2016.


Lee/Holzinger/2016a Sangkyun Lee and Andreas Holzinger. Knowledge Discovery from Complex High Dimensional Data. In Stefan Michaelis and Nico Piatkowski and Marco Stolpe (editors), Solving Large Scale Learning Tasks. Challenges and Algorithms - Essays Dedicated to Katharina Morik on the Occasion of Her 60th Birthday, Vol. 9580, pages 148--167, Springer, 2016.


Piatkowski/etal/2016a Nico Piatkowski and Sangkyun Lee and Katharina Morik. Integer undirected graphical models for resource-constrained systems. In Neurocomputing, Vol. 173, No. 1, pages 9--23, Elsevier, 2016.


Lee/2015a Sangkyun Lee. Signature Selection for Grouped Features with A Case Study on Exon Microarrays. In Urszula Stańczyk and Lakhmi C. Jain (editors), Feature Selection for Data and Pattern Classification, pages 329--349, Springer, 2015.


Lee/etal/2015b Lee, Sangkyun and Brzyski, Damian and Bogdan, Malgorzata. Fast Saddle-Point Algorithm for Generalized Dantzig Selector and FDR Control with the Ordered $\ell_1$-Norm. In arXiv:1511.05864, 2015.


Schramm/etal/2015a Schramm, Alexander and Köster, Johannes and Assenov, Yassen and Althoff, Kristina and Peifer, Martin and Mahlow, Ellen and Odersky, Andrea and Beisser, Daniela and Ernst, Corinna and Henssen, Anton G. and Stephan, Harald and Schröder, Christopher and Heukamp, Lukas and Engesser, Anne and Kahlert, Yvonne and Theissen, Jessica and Hero, Barbara and Roels, Frederik and Altmüller, Janine and Nürnberg, Peter and Astrahantseff, Kathy and Gloeckner, Christian and De Preter, Katleen and Plass, Christoph and Lee, Sangkyun and Lode, Holger N. and Henrich, Kai-Oliver and Gartlgruber, Moritz and Speleman, Frank and Schmezer, Peter and Westermann, Frank and Rahmann, Sven and Fischer, Matthias and Eggert, Angelika and Schulte, Johannes H.. Mutational dynamics between primary and relapse neuroblastomas. In Nature Genetics, Vol. advance online publication, 2015.


Schwermer/Lee/2015a Schwermer, Melanie and Lee, Sangkyun and Köster, Johannes and van Maerken, Tom and Stephan, Harald and Eggert, Angelika and Morik, Katharina and Schulte, Johannes H. and Schramm, Alexander. Sensitivity to cdk1-inhibition is modulated by p53 status in preclinical models of embryonal tumors. In Oncotarget, 2015.


Artikis/etal/2014a Alexander Artikis and Matthias Weidlich and Francois Schnitzler and Ioannis Boutsis and Thomas Liebig and Nico Piatkowski and Christian Bockermann and Katharina Morik and Vana Kalogeraki and Jakub Marecek and Avigdor Gal and Shie Mannor and Dimitrios Gunopulos and Dermot Kinane. Heterogeneous Stream Processing and Crowdsourcing for Urban Traffic Management. In Proceedings of the 17th International Conference on Extending Database Technology, 2014.


Lee/2014a Lee, Sangkyun. Sparse Inverse Covariance Estimation for Graph Representation of Feature Structure. In Holzinger, Andreas and Jurisica, Igor (editors), Interactive Knowledge Discovery and Data Mining in Biomedical Informatics, Vol. 8401, pages 227--240, Springer, 2014.


Lee/2014b Lee, Sangkyun. Characterization of Subgroup Patterns from Graphical Representation of Genomic Data. In \'Sl\c ezak, Dominik and Tan, Ah-Hwee and Peters, JamesF. and Schwabe, Lars (editors), Brain Informatics and Health, Vol. 8609, pages 516--527, Springer, 2014.


Lee/etal/2014a Sangkyun Lee and Jörg Rahnenführer and Michel Lang and Katleen de Preter and Pieter Mestdagh and Jan Koster and Rogier Versteeg and Raymond Stallings and Luigi Varesio and Shahab Asgharzadeh and Johannes Schulte and Kathrin Fielitz and Melanie Heilmann and Katharina Morik and Alexander Schramm. Robust Selection of Cancer Survival Signatures from High-Throughput Genomic Data Using Two-Fold Subsampling. In PLoS ONE, Vol. 9, pages e108818, 2014.


Lee/Poelitz/2014a Lee, Sangkyun and Pölitz, Christian. Kernel Completion for Learning Consensus Support Vector Machines in Bandwidth-Limited Sensor Networks. In International Conference on Pattern Recognition Applications and Methods, 2014.


Liebig/etal/2014d Thomas Liebig and Nico Piatkowski and Christian Bockermann and Katharina Morik. Route Planning with Real-Time Traffic Predictions. In Proceedings of the LWA 2014 Workshops: KDML, IR, FGWM, pages 83-94, 2014.


Piatkowski/etal/2014a Piatkowski, Nico and Sangkyun, Lee and Morik,Katharina. The Integer Approximation of Undirected Graphical Models. In De Marsico, Maria and Tabbone, Antoine and Fred, Ana (editors), ICPRAM 2014 - Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods, ESEO, Angers, Loire Valley, France, 6-8 March, 2014, pages 296--304, SciTePress, 2014.


Schnitzler/etal/2014b Schnitzler, Francois and Artikis, Alexander and Weidlich, Matthias and Boutsis, Ioannis and Liebig, Thomas and Piatkowski, Nico and Bockermann, Christian and Morik, Katharina and Kalogeraki, Vana and Marecek, Jakub and Gal, Avigdor and Mannor, Shie and Kinane, Dermot and Gunopulos, Dimitrios. Heterogeneous Stream Processing and Crowdsourcing for Traffic Monitoring: Highlights. In Proceedings of the European Conference on Machine Learning (ECML), Nectar Track, pages 520-523, Springer, 2014.


Lee/Schramm/2013a Lee, Sangkyun and Schramm, Alexander. Preprocessing of Affymetrix Exon Expression Arrays. No. 3, Technische Universität Dortmund, 2013.


Lee/Wright/2013a Lee, Sangkyun and Wright, Stephen J.. Stochastic Subgradient Estimation Training for Support Vector Machines. In Latorre Carmona, Pedro and S\'anchez, J. Salvador and Fred, Ana L.N. (editors), Mathematical Methodologies in Pattern Recognition and Machine Learning, Vol. 30, pages 67--82, Springer, 2013.


Martin/2013a Marcel Martin. Algorithms and Tools for the Analysis of High-Thoughput DNA Sequencing Data. TU Dortmund, 2013.


Rahmann/etal/2013a Sven Rahmann and Marcel Martin and Johannes H. Schulte and Johannes Köster and Tobias Marschall and Alexander Schramm. Identifying Transcriptional miRNA Biomarkers by Integrating High-Throughput Sequencing and Real-Time PCR Data. In Methods, Vol. 59, No. 1, pages 154--163, 2013.


Schramm/etal/2012a Alexander Schramm and Johannes Köster and Tobias Marschall and Marcel Martin and Melanie Heilmann and Kathrin Fielitz and Gabriele Büchel and Matthias Barann and Daniela Esser and Philip Rosenstiel and Sven Rahmann and Angelika Eggert and Johannes H. Schulte. Next-generation RNA sequencing reveals differential expression of MYCN target genes and suggests the mTOR pathway as a promising therapy target in MYCN-amplified neuroblastoma. In International Journal of Cancer, Vol. 132, No. 3, pages 154--163, 2013.


Schulte/etal/2013a Schulte, J H and Lindner, S and Bohrer, A and Maurer, J and De Preter, K and Lefever, S and Heukamp, L and Schulte, S and Molenaar, J and Versteeg, R and Thor, T and Künkele, A and Vandesompele, J and Speleman, F and Schorle, H and Eggert, A and Schramm, A. MYCN and ALKF1174L are sufficient to drive neuroblastoma development from neural crest progenitor cells. In Oncogene, Vol. 32, No. 8, pages 1059--1065, 2013.


Lee/2012a Lee, Sangkyun. Improving Confidence of Dual Averaging Stochastic Online Learning via Aggregation. In German Conference on Artificial Intelligence (KI 2012), pages 229--232, 2012.


Lee/etal/2012a Lee, S. and Stolpe, M. and Morik, K.. Separable Approximate Optimization of Support Vector Machines for Distributed Sensing. In Flach, Peter A.and De Bie, Tijland Cristianini, Nello (editors), Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2012, Bristol, UK, September 24-28, 2012. Proceedings, Part II, Vol. 7524, pages 387--402, Springer, 2012.


Lee/Wright/2012a Lee, Sangkyun and Wright, Stephen J.. ASSET: Approximate Stochastic Subgradient Estimation Training for Support Vector Machines. In International Conference on Pattern Recognition Applications and Methods (ICPRAM 2012), pages 223-228, 2012.


Lee/Wright/2012b Lee, Sangkyun and Wright, Stephen J.. Manifold Identification in Dual Averaging Methods for Regularized Stochastic Online Learning. In Journal of Machine Learning Research, Vol. 13, pages 1705--1744, 2012.


Molenaar/etal/2012a Molenaar, Jan J and Domingo-Fernandez, Raquel and Ebus, Marli E and Lindner, Sven and Koster, Jan and Drabek, Ksenija and Mestdagh, Pieter and van Sluis, Peter and Valentijn, Linda J and van Nes, Johan and Broekmans, Marloes and Haneveld, Franciska and Volckmann, Richard and Bray, Isabella and Heukamp, Lukas and Sprussel, Annika and Thor, Theresa and Kieckbusch, Kristina and Klein-Hitpass, Ludger and Fischer, Matthias and Vandesompele, Jo and Schramm, Alexander and van Noesel, Max M and Varesio, Luigi and Speleman, Frank and Eggert, Angelika and Stallings, Raymond L and Caron, Huib N and Versteeg, Rogier and Schulte, Johannes H. LIN28B induces neuroblastoma and enhances MYCN levels via let-7 suppression. In Nature Genetics, Vol. 44, No. 11, pages 1199--1206, 2012.


Piatkowski/etal/2012a Piatkowski, Nico and Lee, Sangkyun and Morik, Katharina. Spatio-Temporal Models For Sustainability. In Marwah, Manish and Ramakrishnan, Naren and Berges, Mario and Kolter, Zico (editors), Proceedings of the SustKDD Workshop within ACM KDD 2012, ACM, 2012.


Schramm/etal/2012b Alexander Schramm and Benjamin Schowe and Kathrin Fielitz and Melanie Heilmann and Marcel Martin and Tobias Marschall and Johannes Köster and Jo Vandesompele and Joelle Vermeulen and Katleen de Preter, Jan Koster and Rogier Versteeg and Rosa Noguera and Frank Speleman and Sven Rahmann and Angelika Eggert and Katharina Morik and and Johannes H. Schulte. Exon-level expression analyses identify MYCN and NTRK1 as major determinants of alternative exon usage and robustly predict primary neuroblastoma outcome. In British Journal of Cancer, Vol. 107, No. 8, pages 1409--1417, 2012.


Umaashankar/Lee/2012a Umaashankar, Venkatesh and Lee, Sangkyun. Optimization plugin for RapidMiner. No. 4, TU Dortmund University, 2012.


Esser/etal/2011a Esser, R. and Glienke, W. and Bochennek, K. and Erben, S. and Quaiser, A. and Pieper, C. and Eggert, A. and Schramm, A. and Astrahantseff, K. and Hansmann, M. L. and Schwabe, D. and Klingebiel, T. and Koehl U.. Detection of Neuroblastoma Cells during Clinical Follow Up: Advanced Flow Cytometry and RT-PCR for Tyrosine Hydroxylase Using Both Conventional and Real-Time PCR. In Klin Padiatr, Vol. 223, pages 326-331, 2011.


Lee/Bockermann/2011a Lee, Sangkyun and Bockermann, Christian. Scalable stochastic gradient descent with improved confidence. In Big Learning -- Algorithms, Systems, and Tools for Learning at Scale, 2011.


Lee/etal/2011a Lee, Sangkyun and Schowe, Benjamin and Sivakumar, Viswanath and Morik, Katharina. Feature Selection for High-Dimensional Data with RapidMiner. No. 1, TU Dortmund University, 2011.


Schowe/Morik/2011b Schowe, Benjamin and Morik, Katharina. Fast-Ensembles of Minimum Redundancy Feature Selection. In Okun, Oleg and Valentini, Giorgio and Re, Matteo (editors), Ensembles in Machine Learning Applications, pages 75--95, Springer, 2011.


  • Kliewer/Lee/2016a - EasyTCGA: An R package for easy batch downloading of TCGA data from FireBrowse
  • Lee/etal/2016a - Fast Saddle-Point Algorithm for Generalized Dantzig Selector and FDR Control with the Ordered l1-Norm
  • Lee/Holzinger/2016a - Knowledge Discovery from Complex High Dimensional Data
  • Piatkowski/etal/2016a - Integer undirected graphical models for resource-constrained systems
  • Lee/2015a - Signature Selection for Grouped Features with A Case Study on Exon Microarrays
  • Lee/etal/2015b - Fast Saddle-Point Algorithm for Generalized Dantzig Selector and FDR Control with the Ordered $\ell_1$-Norm
  • Schramm/etal/2015a - Mutational dynamics between primary and relapse neuroblastomas
  • Schwermer/Lee/2015a - Sensitivity to cdk1-inhibition is modulated by p53 status in preclinical models of embryonal tumors
  • Artikis/etal/2014a - Heterogeneous Stream Processing and Crowdsourcing for Urban Traffic Management
  • Lee/2014a - Sparse Inverse Covariance Estimation for Graph Representation of Feature Structure
  • Lee/2014b - Characterization of Subgroup Patterns from Graphical Representation of Genomic Data
  • Lee/etal/2014a - Robust Selection of Cancer Survival Signatures from High-Throughput Genomic Data Using Two-Fold Subsampling
  • Lee/Poelitz/2014a - Kernel Completion for Learning Consensus Support Vector Machines in Bandwidth-Limited Sensor Networks
  • Liebig/etal/2014d - Route Planning with Real-Time Traffic Predictions
  • Piatkowski/etal/2014a - The Integer Approximation of Undirected Graphical Models
  • Schnitzler/etal/2014b - Heterogeneous Stream Processing and Crowdsourcing for Traffic Monitoring: Highlights
  • Lee/Schramm/2013a - Preprocessing of Affymetrix Exon Expression Arrays
  • Lee/Wright/2013a - Stochastic Subgradient Estimation Training for Support Vector Machines
  • Martin/2013a - Algorithms and Tools for the Analysis of High-Thoughput DNA Sequencing Data
  • Rahmann/etal/2013a - Identifying Transcriptional miRNA Biomarkers by Integrating High-Throughput Sequencing and Real-Time PCR Data
  • Schramm/etal/2012a - Next-generation RNA sequencing reveals differential expression of MYCN target genes and suggests the mTOR pathway as a promising therapy target in MYCN-amplified neuroblastoma
  • Schulte/etal/2013a - MYCN and ALKF1174L are sufficient to drive neuroblastoma development from neural crest progenitor cells
  • Lee/2012a - Improving Confidence of Dual Averaging Stochastic Online Learning via Aggregation
  • Lee/etal/2012a - Separable Approximate Optimization of Support Vector Machines for Distributed Sensing
  • Lee/Wright/2012a - ASSET: Approximate Stochastic Subgradient Estimation Training for Support Vector Machines
  • Lee/Wright/2012b - Manifold Identification in Dual Averaging Methods for Regularized Stochastic Online Learning
  • Molenaar/etal/2012a - LIN28B induces neuroblastoma and enhances MYCN levels via let-7 suppression
  • Piatkowski/etal/2012a - Spatio-Temporal Models For Sustainability
  • Schramm/etal/2012b - Exon-level expression analyses identify MYCN and NTRK1 as major determinants of alternative exon usage and robustly predict primary neuroblastoma outcome
  • Umaashankar/Lee/2012a - Optimization plugin for RapidMiner
  • Esser/etal/2011a - Detection of Neuroblastoma Cells during Clinical Follow Up: Advanced Flow Cytometry and RT-PCR for Tyrosine Hydroxylase Using Both Conventional and Real-Time PCR
  • Lee/Bockermann/2011a - Scalable stochastic gradient descent with improved confidence
  • Lee/etal/2011a - Feature Selection for High-Dimensional Data with RapidMiner
  • Schowe/Morik/2011b - Fast-Ensembles of Minimum Redundancy Feature Selection

Final Thesis:

  • Hess/2015a - Untersuchung von Code-Tabellen zur Kompression von binären Datenbanken
  • Schwitalla/2015a - Optimierung von Genomsequenzanalysen mit Hauptspeicherdatenbanksystemen
  • Egorov/2012a - Logistic regression with group ell 1 vs. elastic net regularization

Preliminary Work:

Morik/2010a Morik, Katharina. Medicine: Applications in Machine Learning. In Sammut, Claude and Webb, Geoffrey I. (editors), Encyclopedia of Machine Learning, pages 654-661, Springer, 2010.


Schulte/Schowe/2010a Johannes H. Schulte and Benjamin Schowe and Pieter Mestdagh and Lars Kaderali and Prabhav Kalaghatgi and Stefanie Schlierf and Joelle Vermeulen and Bent Brockmeyer and Kristian Pajtler and Theresa Thor and Katleen de Preter and Frank Speleman and Katharina Morik and Angelika Eggert and Jo Vandesompele and Alexander Schramm. Accurate Prediction of Neuroblastoma Outcome based on miRNA Expression Profiles. In International Journal of Cancer, 2010.


Huebener/etal/2009a Huebener, N. and Fest, S. and Hilt, K. and Schramm, A. and Eggert, A. and Durmus, T. and Woehler, A. and Stermann, A. and Bleeke, M. and Baykan, B. and Weixler, S. and Gaedicke, G. and Lode, H. N.. Xenogeneic immunization with human tyrosine hydroxylase DNA vaccines suppresses growth of established neuroblastoma. In Molecular Cancer Therapeutics, Vol. 8, No. 8, pages 2392-401, 2009.


Schramm/Mierswa/2009a Schramm, Alexander and Mierswa, Ingo and Kaderali, Lars and Morik, Katharina and Eggert, Angelika and Schulte, Johannes H.. Reanalysis of neuroblastoma expression profiling data using improved methodology and extended follow-up increases validity of outcome prediction. In Cancer Letters, Vol. 282, No. 1, pages 56--62, 2009.


Schulte/etal/2009a Schulte, J. H. and Horn, S. and Schlierf, S. and Schramm, A. and Heukamp, L. C. and Christiansen, H. and Buettner, R. and Berwanger, B. and Eggert, A.. MicroRNAs in the pathogenesis of neuroblastoma. In Cancer Letters, Vol. 274, No. 1, pages 10-5, 2009.


Schulte/etal/2009b Schulte, J. H. and Pentek, F. and Hartmann, W. and Schramm, A. and Friedrichs, N. and Ora, I. and Koster, J. and Versteeg, R. and Kirfel, J. and Buettner, R. and Eggert, A.. The low-affinity neurotrophin receptor, p75, is upregulated in ganglioneuroblastoma/ganglioneuroma and reduces tumorigenicity of neuroblastoma cells in vivo. In International Journal of Cancer, Vol. 124, No. 10, pages 2488-94, 2009.


Schulte/etal/2009c Schulte, J. H. and Lim, S. and Schramm, A. and Friedrichs, N. and Koster, J. and Versteeg, R. and Ora, I. and Pajtler, K. and Klein-Hitpass, L. and Kuhfittig-Kulle, S. and Metzger, E. and Schule, R. and Eggert, A. and Buettner, R. and Kirfel, J.. Lysine-specific demethylase 1 is strongly expressed in poorly differentiated neuroblastoma: implications for therapy. In Cancer Research, Vol. 69, No. 5, pages 2065-71, 2009.


Schulte/etal/2008a Schulte, J. H. and Kuhfittig-Kulle, S. and Klein-Hitpass, L. and Schramm, A. and Biard, D. S. and Pfeiffer, P. and Eggert, A.. Expression of the TrkA or TrkB receptor tyrosine kinase alters the double-strand break (DSB) repair capacity of SY5Y neuroblastoma cells. In DNA Repair (Amst), Vol. 7, No. 10, pages 1757-64, 2008.


Vandesompele/etal/2008a Vandesompele, J. and Michels, E. and De Preter, K. and Menten, B. and Schramm, A. and Eggert, A. and Ambros, P. F. and Combaret, V. and Francotte, N. and Antonacci, F. and De Paepe, A. and Laureys, G. and Speleman, F. and Van Roy, N.. Identification of 2 putative critical segments of 17q gain in neuroblastoma through integrative genomics. In International Journal of Cancer, Vol. 122, No. 5, pages 1177-82, 2008.


Schramm/etal/2007a Schramm, A. and Vandesompele, J. and Schulte, J. H. and Dreesmann, S. and Kaderali, L. and Brors, B. and Eils, R. and Speleman, F. and Eggert, A.. Translating expression profiling into a clinically feasible test to predict neuroblastoma outcome. In Clinical Cancer Research, Vol. 13, No. 5, pages 1459-65, 2007.


Scaruffi/etal/2005a Scaruffi, P. and Valent, A. and Schramm, A. and Astrahantseff, K. and Eggert, A. and Tonini, G. P.. Application of microarray-based technology to neuroblastoma. In Cancer Letters, Vol. 228, No. 1-2, pages 13-20, 2005.


Schramm/etal/2005a Schramm, A. and Schulte, J. H. and Klein-Hitpass, L. and Havers, W. and Sieverts, H. and Berwanger, B. and Christiansen, H. and Warnat, P. and Brors, B. and Eils, J. and Eils, R. and Eggert, A.. Prediction of clinical outcome and biological characterization of neuroblastoma by expression profiling. In Oncogene, Vol. 24, No. 53, pages 7902-12, 2005.


  • Morik/2010a - Medicine: Applications in Machine Learning
  • Schulte/Schowe/2010a - Accurate Prediction of Neuroblastoma Outcome based on miRNA Expression Profiles
  • Huebener/etal/2009a - Xenogeneic immunization with human tyrosine hydroxylase DNA vaccines suppresses growth of established neuroblastoma
  • Schramm/Mierswa/2009a - Reanalysis of neuroblastoma expression profiling data using improved methodology and extended follow-up increases validity of outcome prediction
  • Schulte/etal/2009a - MicroRNAs in the pathogenesis of neuroblastoma
  • Schulte/etal/2009b - The low-affinity neurotrophin receptor, p75, is upregulated in ganglioneuroblastoma/ganglioneuroma and reduces tumorigenicity of neuroblastoma cells in vivo
  • Schulte/etal/2009c - Lysine-specific demethylase 1 is strongly expressed in poorly differentiated neuroblastoma: implications for therapy
  • Schulte/etal/2008a - Expression of the TrkA or TrkB receptor tyrosine kinase alters the double-strand break (DSB) repair capacity of SY5Y neuroblastoma cells
  • Vandesompele/etal/2008a - Identification of 2 putative critical segments of 17q gain in neuroblastoma through integrative genomics
  • Schramm/etal/2007a - Translating expression profiling into a clinically feasible test to predict neuroblastoma outcome
  • Scaruffi/etal/2005a - Application of microarray-based technology to neuroblastoma
  • Schramm/etal/2005a - Prediction of clinical outcome and biological characterization of neuroblastoma by expression profiling