Marcel J. T. Reinders

M. J. T. Reinders received his M.S. degree in applied physics and a Ph.D. degree in electrical engineering from Delft University of Technology, The Netherlands, in 1990 and 1995, respectively. Recently he became a Professor in bioinformatics in the Mediamatics Department of the Faculty of Electrical Engineering, Mathematics and Computer Science at the Delft University of Technology. The background of Professor Reinders is in pattern recognition. Besides studying fundamental issues, he applies pattern recognition techniques to the areas of bioinformatics, computer vision, and context-aware recommender systems. His special interest goes towards understanding complex systems (such as biological systems) that are severely undersampled.

Biography Updated on 19 May 2005

Personal Home Page

http://ict.ewi.tudelft.nl/index.php?option=com_contact&task=view&id=54

Articles in Scholarly Journals [Incomplete List]

  1. Integration of prior knowledge of measurement noise in kernel density classification
    Pattern Recognition, vol. 41, no. 1, pp. 320–330, 2008
  2. Erratum to “Classification in the presence of class noise using a probabilistic kernel fisher method”[Pattern Recognition 40 (12) 3349–3357]
    Pattern Recognition, vol. 41, no. 3, pp. 1214–1214, 2008
  3. Integration of Known Transcription Factor Binding Site Information and Gene Expression Data to Advance from Co-Expression to Co-Regulation
    Genomics, Proteomics & Bioinformatics, vol. 5, no. 2, pp. 86–101, 2007
  4. Classification in the presence of class noise using a probabilistic Kernel Fisher method
    Pattern Recognition, vol. 40, no. 12, pp. 3349–3357, 2007
  5. Personalization on a peer-to-peer television system
    Multimedia Tools and Applications, vol. 36, no. 1-2, pp. 89–113, 2007
  6. Co-occurrence analysis of insertional mutagenesis data reveals cooperating oncogenes
    Bioinformatics, vol. 23, no. 13, pp. i133–i141, 2007
  7. Quantitative proteomics and transcriptomics of anaerobic and aerobic yeast cultures reveals post-transcriptional regulation of key cellular processes
    Microbiology, vol. 153, no. 11, pp. 3864–3878, 2007
  8. Ectopic retroviral expression of LMO2, but not IL2R?, blocks human T-cell development from CD34+ cells: implications for leukemogenesis in gene therapy
    Leukemia, Article ID 2404563, 2007
  9. Generic and specific transcriptional responses to different weak organic acids in anaerobic chemostat cultures of Saccharomyces cerevisiae
    FEMS Yeast Research, vol. 7, no. 6, pp. 819–833, 2007
  10. PROTEIN COMPLEX PREDICTION USING AN INTEGRATIVE BIOINFORMATICS APPROACH
    Journal of Bioinformatics and Computational Biology, vol. 05, no. 04, p. 839, 2007
  11. BMC Genomics, vol. 8, no. 1, p. 25, 2007
  12. Detecting Statistically Significant Common Insertion Sites in Retroviral Insertional Mutagenesis Screens
    PLoS Computational Biology, vol. 2, no. 12, p. e166, 2006
  13. BMC Bioinformatics, vol. 7, no. 1, p. 105, 2006
  14. BMC Bioinformatics, vol. 7, no. 1, p. 235, 2006
  15. Gene therapy: Is IL2RG oncogenic in T-cell development?
    Nature, vol. 443, no. 7109, Article ID nature05218, 2006
  16. Artifacts of Markov blanket filtering based on discretized features in small sample size applications
    Pattern Recognition Letters, vol. 27, no. 7, pp. 709–714, 2006
  17. Random subspace method for multivariate feature selection
    Pattern Recognition Letters, vol. 27, no. 10, pp. 1067–1076, 2006
  18. An expression profile for diagnosis of lymph node metastases from primary head and neck squamous cell carcinomas
    Nature Genetics, vol. 37, no. 2, Article ID ng1502, 4 pages, 2005
  19. Computational estimation of the composition of fat/oil mixtures containing interesterifications from gas and liquid chromatography data
    Journal of the American Oil Chemists' Society, vol. 82, no. 10, pp. 707–716, 2005
  20. Microarray analysis reveals expression regulation of Wnt antagonists in differentiating osteoblasts
    Bone, vol. 36, no. 5, pp. 803–811, 2005
  21. Purity for clarity: the need for purification of tumor cells in DNA microarray studies
    Leukemia, Article ID 2403685, 2005
  22. New insights on human T cell development by quantitative T cell receptor gene rearrangement studies and gene expression profiling
    Journal of Experimental Medicine, vol. 201, no. 11, pp. 1715–1723, 2005
  23. A protocol for building and evaluating predictors of disease state based on microarray data
    Bioinformatics, vol. 21, no. 19, pp. 3755–3762, 2005
  24. Maximum significance clustering of oligonucleotide microarrays
    Bioinformatics, vol. 22, no. 3, pp. 326–331, 2005
  25. Least absolute regression network analysis of the murine osteoblast differentiation network
    Bioinformatics, vol. 22, no. 4, pp. 477–484, 2005
  26. Constrained Texture Restoration
    EURASIP Journal on Applied Signal Processing, vol. 2005, no. 17, pp. 2758–2771, 2005
  27. The Nearest Subclass Classifier: A Compromise between the Nearest Mean and Nearest Neighbor Classifier
    IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 27, no. 9, pp. 1417–1429, 2005
  28. Edge-Based Image Restoration
    IEEE Transactions on Image Processing, vol. 14, no. 10, pp. 1454–1468, 2005
  29. DNA microarrays for comparison of gene expression profiles between diagnosis and relapse in precursor-B acute lymphoblastic leukemia: choice of technique and purification influence the identification of potential diagnostic markers
    Leukemia, vol. 18, no. 5, Article ID 2403373, 1 pages, 2004
  30. Multi-criterion optimization for genetic network modeling
    Signal Processing, vol. 83, no. 4, pp. 763–775, 2003
  31. DNA microarrays for comparison of gene expression profiles between diagnosis and relapse in precursor-B acute lymphoblastic leukemia: choice of technique and purification influence the identification of potential diagnostic markers
    Leukemia, vol. 17, no. 7, Article ID 2402974, 8 pages, 2003
  32. Establishing motion correspondence using extended temporal scope
    Artificial Intelligence, vol. 145, no. 1-2, pp. 227–243, 2003
  33. Motion tracking as a constrained optimization problem
    Pattern Recognition, vol. 36, no. 9, pp. 2049–2067, 2003
  34. A cellular coevolutionary algorithm for image segmentation
    IEEE Transactions on Image Processing, vol. 12, no. 3, pp. 304–316, 2003
  35. Studying the Conditions for Learning Dynamic Bayesian Networks to Discover Genetic Regulatory Networks
    SIMULATION: Transactions of the Society for Modeling and Simulation, vol. 79, no. 12, pp. 689–702, 2003
  36. Genetic network modeling
    Pharmacogenomics, vol. 3, no. 4, pp. 507–525, 2002
  37. A maximum variance cluster algorithm
    IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, no. 9, pp. 1273–1280, 2002
  38. Scale-invariant segmentation of dynamic contrast-enhanced perfusion MR images with inherent scale selection
    The Journal of Visualization and Computer Animation, vol. 13, no. 1, pp. 1–19, 2002
  39. Utility map reconstruction
    International Journal of Geographical Information Science, vol. 15, no. 1, pp. 7–26, 2001
  40. Resolving motion correspondence for densely moving points
    IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 23, no. 1, pp. 54–72, 2001
  41. Image sharpening by morphological filtering
    Pattern Recognition, vol. 33, no. 6, pp. 997–1012, 2000
  42. On-line detection of red blood cell shape using deformable templates
    Pattern Recognition Letters, vol. 21, no. 5, pp. 413–424, 2000
  43. Information processing for intelligent molecular diagnosis
    Pattern Recognition Letters, vol. 20, no. 11-13, pp. 1457–1465, 1999
  44. Facial feature localization and adaptation of a generic face model for model-based coding
    Signal Processing: Image Communication, vol. 7, no. 1, pp. 57–74, 1995