
Prof.dr.ir. M.J.T. Reinders
Prof.dr.ir. M.J.T. Reinders
Profiel
Resume
Prof Reinders holds a position at the Delft University of Technology as well as at the Leiden University Medical Center. In Delft he heads the
Pattern Recognition and Bioinformatics section in one of the Computer Science departments of the Faculty of Electtrical Engineering, Mathematics and Computer Science. The section consists of three research labs:
Delft Bioinformatics Lab (5 staff);
Pattern Recognition Lab (2 staff);
Computer Vision Lab (3 staff) and includes a group of ~60 people (incl. ~10 scientific staff members (HL/UHD/UD’s), ~30 PHDs/Postdocs, ~20MSCs). In Leiden he heads the
Leiden Computational Biology Center. This center generates new biological insights with clinical applicabilities using computational tools to analyse molecular data. The groupconsists of ~15 people (incl. 3 scientific staff memberts (tenure trackers), ~12PDs/MScs).
google sholar:
scholar.google.com/citations?user=h52_bg0AAAAJ
url prb:
www.prb.tudelft.nl
url lcbc:
www.lcbc.nl
Educational activities
- Coordinator of “Master track Bioinformatics” within the Computer Science program
- Supervised ~100 master students
- Lecturer of 7 graduate courses (currently 1), “Functional Genomics and Systems Biology”
- Lecturer of 10 undergraduate courses (currently 3), ao “Datamining” and “Bioinformatics”
- Lecturer of 7 postgraduate courses (currently 1), “NBIC course on Pattern Recognition”
Professional memberships
From 2017 Member scientific advisory board Informatics Platform Netherlands
From 2014 Member scientific advisory board Dutch Techcentre for Life Science
From 2013 Visiting professor at Clinical Genetics, Free University Medical Centre
From 2011 Director of the TUD-EEMCS Graduate School
2010-2017 Scientific Director of the Netherlands Bioinformatics Center (NBIC)
From 2009 Heading the Pattern Recognition and Bioinformatics Section (PRB), Computer 2005-2015 Chair of the TUD-EEMCS Scientific Advisory Board (VCWB)
Research description
Prof Reinders group in Delft is recognized as international experts on machine learning and in his bioinformatics research he applies the cutting-edge machine learning expertise to develop data-driven analysis methodologies to gain molecular biology insights. His group in Leiden uses computational biology to progress clinical applicability of molecular data with a focus on newest technologies, such as single cell or spatio-temporal omics data. He initiated work on molecular classification and genetic network modelling, and has a strong track record on next-generation sequencing analysis, network-based analysis, as well as integration of genomic data.
Expertise
Publicaties
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2023
A comprehensive performance analysis of sequence-based within-sample testing NIPT methods
T.O. Mokveld / Z. Al-Ars / Erik A. Sistermans / M.J.T. Reinders
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2023
Benchmarking Outlier Detection Methods for Detecting IEM Patients in Untargeted Metabolomics Data
Michiel Bongaerts / Purva Kulkarni / Alan Zammit / Ramon Bonte / Leo A. J. Kluijtmans / Henk J. Blom / Udo F. H. Engelke / D.M.J. Tax / George J.G. Ruijter / M.J.T. Reinders
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2023
Bioinformatics Strategies for the Analysis and Integration of Large-Scale Multiomics Data
Niccolo' Tesi / Sven van der Lee / Marc Hulsman / Henne Holstege / Marcel Reinders
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2023
Consequences and opportunities arising due to sparser single-cell RNA-seq datasets
Gerard A. Bouland / Ahmed Mahfouz / Marcel J.T. Reinders
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2023
Percolate
An Exponential Family JIVE Model to Design DNA-Based Predictors of Drug Response
Soufiane M.C. Mourragui / Marco Loog / Mirrelijn van Nee / Mark A.van de Wiel / Marcel J.T. Reinders / Lodewyk F.A. Wessels -
Nevenwerkzaamheden
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2018-11-01 - 2023-11-01
Onderwijs
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2014-01-01 - 2024-01-01
Advisering/onderzoek en overig
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2019-02-01 - 2024-12-01
Landbouw, bosbouw en visserij
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2016-01-01 - 2024-01-01
Onderwijs