Complete List of Works

@article{info:hdl:2013/138318,

title = {Accurate prediction of the dynamical changes within the second PDZ domain of PTP1e.},

author = {Elisa Cilia and Geerten W Vuister and Tom Lenaerts},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/138318/4/doi_121267.pdf},

year  = {2012},

date = {2012-01-01},

journal = {PLoS computational biology},

volume = {8},

number = {11},

pages = {e1002794},

abstract = {Experimental NMR relaxation studies have shown that peptide binding induces dynamical changes at the side-chain level throughout the second PDZ domain of PTP1e, identifying as such the collection of residues involved in long-range communication. Even though different computational approaches have identified subsets of residues that were qualitatively comparable, no quantitative analysis of the accuracy of these predictions was thus far determined. Here, we show that our information theoretical method produces quantitatively better results with respect to the experimental data than some of these earlier methods. Moreover, it provides a global network perspective on the effect experienced by the different residues involved in the process. We also show that these predictions are consistent within both the human and mouse variants of this domain. Together, these results improve the understanding of intra-protein communication and allostery in PDZ domains, underlining at the same time the necessity of producing similar data sets for further validation of thses kinds of methods.},

note = {DOI: 10.1371/journal.pcbi.1002794},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/138059,

title = {Purification, crystallization and preliminary X-ray diffraction analysis of the Fyn SH2 domain and its complex with a phosphotyrosine peptide.},

author = {Radu Huculeci and Lieven Buts and Tom Lenaerts and Nico A J van Nuland and Abel Garcia-Pino},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/138059/4/PMC3310552.pdf},

year  = {2012},

date = {2012-01-01},

journal = {Acta Crystallographica. Section F: Structural Biology and Crystallization Communications Online},

volume = {68},

number = {Pt 3},

pages = {359-364},

abstract = {SH2 domains are widespread protein-binding modules that recognize phosphotyrosines and play central roles in intracellular signalling pathways. The SH2 domain of the human protein tyrosine kinase Fyn has been expressed, purified and crystallized in the unbound state and in complex with a high-affinity phosphotyrosine peptide. X-ray data were collected to a resolution of 2.00 Å for the unbound form and 1.40 Å for the protein in complex with the phosphotyrosine peptide.},

note = {DOI: 10.1107/S1744309112004186},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/133921,

title = {Emergence of fairness in repeated group interactions.},

author = {Sven Van Segbroeck and Jorge J M Pacheco and Tom Lenaerts and F C Santos},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/133921},

year  = {2012},

date = {2012-01-01},

journal = {Physical review letters},

volume = {108},

number = {15},

pages = {158104},

abstract = {Often groups need to meet repeatedly before a decision is reached. Hence, most individual decisions will be contingent on decisions taken previously by others. In particular, the decision to cooperate or not will depend on one's own assessment of what constitutes a fair group outcome. Making use of a repeated N-person prisoner's dilemma, we show that reciprocation towards groups opens a window of opportunity for cooperation to thrive, leading populations to engage in dynamics involving both coordination and coexistence, and characterized by cycles of cooperation and defection. Furthermore, we show that this process leads to the emergence of fairness, whose level will depend on the dilemma at stake.},

note = {Language of publication: en},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/138318b,

title = {Accurate prediction of the dynamical changes within the second PDZ domain of PTP1e.},

author = {Elisa Cilia and Geerten W Vuister and Tom Lenaerts},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/138318},

year  = {2012},

date = {2012-01-01},

journal = {PLoS computational biology},

volume = {8},

number = {11},

pages = {e1002794},

note = {DOI: 10.1371/journal.pcbi.1002794},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/134336b,

title = {A complete workflow for the analysis of full-size ChIP-seq (and similar) data sets using peak-motifs.},

author = {Morgane Thomas-Chollier and Elodie Darbo and Carl Herrmann and Matthieu Defrance and Denis Thieffry and Jacques Helden},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/134336},

year  = {2012},

date = {2012-01-01},

journal = {Nature Protocols (Online)},

volume = {7},

number = {8},

pages = {1551-1568},

note = {DOI: 10.1038/nprot.2012.088},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/133921b,

title = {Emergence of fairness in repeated group interactions.},

author = {Sven Van Segbroeck and Jorge J. M. Pacheco and Tom Lenaerts and F C Santos},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/133921},

year  = {2012},

date = {2012-01-01},

journal = {Physical review letters},

volume = {108},

number = {15},

pages = {158104},

note = {Language of publication: en},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/138059b,

title = {Purification, crystallization and preliminary X-ray diffraction analysis of the Fyn SH2 domain and its complex with a phosphotyrosine peptide.},

author = {Radu Huculeci and Lieven Buts and Tom Lenaerts and Nico A J Nuland and Abel Garcia-Pino},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/138059},

year  = {2012},

date = {2012-01-01},

journal = {Acta Crystallographica. Section F: Structural Biology and Crystallization Communications Online},

volume = {68},

number = {Pt 3},

pages = {359-364},

note = {DOI: 10.1107/S1744309112004186},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/262167b,

title = {DNA methylation profiling identifies epigenetic dysregulation in pancreatic islets from type 2 diabetic patients.},

author = {Michael Volkmar and Sarah Dedeurwaerder and Daniel Andrade Da Cunha and Matladi N. Ndlovu and Matthieu Defrance and Rachel Deplus and Emilie Calonne and Ute Volkmar and Mariana Igoillo Esteve and Najib Naamane and Silvia Del Guerra and Matilde Masini and Marco Bugliani and Piero Marchetti and Miriam Cnop and Decio L. Eizirik and Franccois Fuks},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/262167},

year  = {2012},

date = {2012-01-01},

journal = {EMBO journal},

volume = {31},

number = {6},

pages = {1405-1426},

note = {DOI: 10.1038/emboj.2011.503},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/135461b,

title = {A three-gene model to robustly identify breast cancer molecular subtypes.},

author = {Benjamin Haibe-Kains and Christine Desmedt and Sherene Loi and Aedin C Culhane and Gianluca Bontempi and John Quackenbush and Christos Sotiriou},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/135461},

year  = {2012},

date = {2012-01-01},

journal = {Journal of the National Cancer Institute},

volume = {104},

number = {4},

pages = {311-325},

note = {DOI: 10.1093/jnci/djr545},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/123728b,

title = {RSAT peak-motifs: motif analysis in full-size ChIP-seq datasets.},

author = {Morgane Thomas-Chollier and Carl Herrmann and Matthieu Defrance and Olivier Sand and Denis Thieffry and Jacques Helden},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/123728},

year  = {2012},

date = {2012-01-01},

journal = {Nucleic acids research},

volume = {40},

number = {4},

pages = {e31},

note = {DOI: 10.1093/nar/gkr1104},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/109024b,

title = {A review and comparison of strategies for multi-step ahead time series forecasting based on the NN5 forecasting competition},

author = {Souhaib Ben Taieb and Gianluca Bontempi and Amir F. Atiya and Antti Sorjamaa},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/109024},

year  = {2012},

date = {2012-01-01},

journal = {Expert systems with applications},

volume = {39},

number = {8},

pages = {7067-7083},

note = {DOI: 10.1016/j.eswa.2012.01.039},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/109023b,

title = {Adaptive local learning techniques for multiple-step-ahead wind speed forecasting},

author = {Alfredo A. Vaccaro and Gianluca Bontempi and Souhaib Ben Taieb and Domenico D. Villacci},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/109023},

year  = {2012},

date = {2012-01-01},

journal = {Electric power systems research},

volume = {83},

number = {1},

pages = {129-135},

note = {DOI: 10.1016/j.epsr.2011.10.008},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/169032b,

title = {Time series prediction for energy-efficient wireless sensors: Applications to environmental monitoring and video games},

author = {Yann-A"el Le Borgne and Gianluca Bontempi},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/169032},

year  = {2012},

date = {2012-01-01},

journal = {Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering},

volume = {102 LNICST},

pages = {63-72},

note = {DOI: 10.1007/978-3-642-32778-0_5},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/145205b,

title = {Predictive networks: a flexible, open source, web application for integration and analysis of human gene networks.},

author = {Benjamin Haibe-Kains and Catharina Olsen and Amira Djebbari and Gianluca Bontempi and Mick Correll and Christopher Bouton and John Quackenbush},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/145205},

year  = {2012},

date = {2012-01-01},

journal = {Nucleic acids research},

volume = {40},

number = {Database issue},

pages = {D866-D875},

note = {DOI: 10.1093/nar/gkr1050},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/145204b,

title = {D-peaks: a visual tool to display ChIP-seq peaks along the genome.},

author = {Sylvain Brohée and Gianluca Bontempi},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/145204},

year  = {2012},

date = {2012-01-01},

journal = {Transcription},

volume = {3},

number = {5},

pages = {255-259},

note = {DOI: 10.4161/trns.22457},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/135461,

title = {A three-gene model to robustly identify breast cancer molecular subtypes.},

author = {Benjamin Haibe-Kains and Christine Desmedt and Sherene Loi and Aedin C Culhane and Gianluca Bontempi and John Quackenbush and Christos Sotiriou},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/135461/4/doi_118025.pdf},

year  = {2012},

date = {2012-01-01},

journal = {Journal of the National Cancer Institute},

volume = {104},

number = {4},

pages = {311-325},

abstract = {Single sample predictors (SSPs) and Subtype classification models (SCMs) are gene expression-based classifiers used to identify the four primary molecular subtypes of breast cancer (basal-like, HER2-enriched, luminal A, and luminal B). SSPs use hierarchical clustering, followed by nearest centroid classification, based on large sets of tumor-intrinsic genes. SCMs use a mixture of Gaussian distributions based on sets of genes with expression specifically correlated with three key breast cancer genes (estrogen receptor [ER], HER2, and aurora kinase A [AURKA]). The aim of this study was to compare the robustness, classification concordance, and prognostic value of these classifiers with those of a simplified three-gene SCM in a large compendium of microarray datasets.},

note = {DOI: 10.1093/jnci/djr545},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/109023,

title = {Adaptive local learning techniques for multiple-step-ahead wind speed forecasting},

author = {Alfredo A Vaccaro and Gianluca Bontempi and Souhaib Ben Taieb and Domenico D Villacci},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/109023/1/Elsevier_89123.pdf},

year  = {2012},

date = {2012-01-01},

journal = {Electric power systems research},

volume = {83},

number = {1},

pages = {129-135},

abstract = {A massive deployment of wind energy in power systems is expected in the near future. However, a still open issue is how to integrate wind generators into existing electrical grids by limiting their side effects on network operations and control. In order to attain this objective, accurate short and medium-term wind speed forecasting is required. This paper discusses and compares a physical (white-box) model (namely a limited-area non hydrostatic model developed by the European consortium for small-scale modeling) with a family of local learning techniques (black-box) for short and medium term forecasting. Also, an original model integrating machine learning techniques with physical knowledge modeling (grey-box) is proposed. A set of experiments on real data collected from a set of meteorological sensors located in the south of Italy supports the methodological analysis and assesses the potential of the different forecasting approaches. copyright 2011 Elsevier B.V. All rights reserved.},

note = {DOI: 10.1016/j.epsr.2011.10.008},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/109024,

title = {A review and comparison of strategies for multi-step ahead time series forecasting based on the NN5 forecasting competition},

author = {Souhaib Ben Taieb and Gianluca Bontempi and Amir F Atiya and Antti Sorjamaa},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/109024/1/Elsevier_89124.pdf},

year  = {2012},

date = {2012-01-01},

journal = {Expert systems with applications},

volume = {39},

number = {8},

pages = {7067-7083},

abstract = {Multi-step ahead forecasting is still an open challenge in time series forecasting. Several approaches that deal with this complex problem have been proposed in the literature but an extensive comparison on a large number of tasks is still missing. This paper aims to fill this gap by reviewing existing strategies for multi-step ahead forecasting and comparing them in theoretical and practical terms. To attain such an objective, we performed a large scale comparison of these different strategies using a large experimental benchmark (namely the 111 series from the NN5 forecasting competition). In addition, we considered the effects of deseasonalization, input variable selection, and forecast combination on these strategies and on multi-step ahead forecasting at large. The following three findings appear to be consistently supported by the experimental results: Multiple-Output strategies are the best performing approaches, deseasonalization leads to uniformly improved forecast accuracy, and input selection is more effective when performed in conjunction with deseasonalization. copyright 2011 Elsevier Ltd. All rights reserved.},

note = {DOI: 10.1016/j.eswa.2012.01.039},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/145205,

title = {Predictive networks: a flexible, open source, web application for integration and analysis of human gene networks.},

author = {Benjamin Haibe-Kains and Catharina Olsen and Amira Djebbari and Gianluca Bontempi and Mick Correll and Christopher Bouton and John Quackenbush},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/145205/4/PMC3245161.pdf},

year  = {2012},

date = {2012-01-01},

journal = {Nucleic acids research},

volume = {40},

number = {Database issue},

pages = {D866-D875},

abstract = {Genomics provided us with an unprecedented quantity of data on the genes that are activated or repressed in a wide range of phenotypes. We have increasingly come to recognize that defining the networks and pathways underlying these phenotypes requires both the integration of multiple data types and the development of advanced computational methods to infer relationships between the genes and to estimate the predictive power of the networks through which they interact. To address these issues we have developed Predictive Networks (PN), a flexible, open-source, web-based application and data services framework that enables the integration, navigation, visualization and analysis of gene interaction networks. The primary goal of PN is to allow biomedical researchers to evaluate experimentally derived gene lists in the context of large-scale gene interaction networks. The PN analytical pipeline involves two key steps. The first is the collection of a comprehensive set of known gene interactions derived from a variety of publicly available sources. The second is to use these 'known' interactions together with gene expression data to infer robust gene networks. The PN web application is accessible from http://predictivenetworks.org. The PN code base is freely available at https://sourceforge.net/projects/predictivenets/.},

note = {DOI: 10.1093/nar/gkr1050},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/145204,

title = {D-peaks: a visual tool to display ChIP-seq peaks along the genome.},

author = {Sylvain Brohée and Gianluca Bontempi},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/145204/4/PMC3632623.pdf},

year  = {2012},

date = {2012-01-01},

journal = {Transcription},

volume = {3},

number = {5},

pages = {255-259},

abstract = {ChIP-sequencing is a method of choice to localize the positions of protein binding sites on DNA on a whole genomic scale. The deciphering of the sequencing data produced by this novel technique is challenging and it is achieved by their rigorous interpretation using dedicated tools and adapted visualization programs. Here, we present a bioinformatics tool (D-peaks) that adds several possibilities (including, user-friendliness, high-quality, relative position with respect to the genomic features) to the well-known visualization browsers or databases already existing. D-peaks is directly available through its web interface http://rsat.ulb.ac.be/dpeaks/ as well as a command line tool.},

note = {DOI: 10.4161/trns.22457},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/169032,

title = {Time series prediction for energy-efficient wireless sensors: Applications to environmental monitoring and video games},

author = {Yann-A{"e}l Le Borgne and Gianluca Bontempi},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/169032},

year  = {2012},

date = {2012-01-01},

journal = {Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering},

volume = {102 LNICST},

pages = {63-72},

abstract = {Time series prediction techniques have been shown to significantly reduce the radio use and energy consumption of wireless sensor nodes performing periodic data collection tasks. In this paper, we propose an implementation of exponential smoothing, a standard time series prediction technique, for wireless sensors. We rely on a framework called Adaptive Model Selection (AMS), specifically designed for running time series prediction techniques on resource-constrained wireless sensors. We showcase our implementation with two demos, related to environmental monitoring and video games. The demos are implemented with TinyOS, a reference operating system for low-power embedded systems, and TMote Sky and TMote Invent wireless sensors. copyright 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering.},

note = {DOI: 10.1007/978-3-642-32778-0_5},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/134336,

title = {A complete workflow for the analysis of full-size ChIP-seq (and similar) data sets using peak-motifs.},

author = {Morgane Thomas-Chollier and Elodie Darbo and Carl Herrmann and Matthieu Defrance and Denis Thieffry and Jacques van Helden},

url = {http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/134336},

year  = {2012},

date = {2012-01-01},

journal = {Nature Protocols (Online)},

volume = {7},

number = {8},

pages = {1551-1568},

abstract = {This protocol explains how to use the online integrated pipeline 'peak-motifs' (http://rsat.ulb.ac.be/rsat/) to predict motifs and binding sites in full-size peak sets obtained by chromatin immunoprecipitation-sequencing (ChIP-seq) or related technologies. The workflow combines four time- and memory-efficient motif discovery algorithms to extract significant motifs from the sequences. Discovered motifs are compared with databases of known motifs to identify potentially bound transcription factors. Sequences are scanned to predict transcription factor binding sites and analyze their enrichment and positional distribution relative to peak centers. Peaks and binding sites are exported as BED tracks that can be uploaded into the University of California Santa Cruz (UCSC) genome browser for visualization in the genomic context. This protocol is illustrated with the analysis of a set of 6,000 peaks (8 Mb in total) bound by the Drosophila transcription factor Krüppel. The complete workflow is achieved in about 25 min of computational time on the Regulatory Sequence Analysis Tools (RSAT) Web server. This protocol can be followed in about 1 h.},

note = {DOI: 10.1038/nprot.2012.088},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/123728,

title = {RSAT peak-motifs: motif analysis in full-size ChIP-seq datasets.},

author = {Morgane Thomas-Chollier and Carl Herrmann and Matthieu Defrance and Olivier Sand and Denis Thieffry and Jacques van Helden},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/123728/4/PMC3287167.pdf},

year  = {2012},

date = {2012-01-01},

journal = {Nucleic acids research},

volume = {40},

number = {4},

pages = {e31},

abstract = {ChIP-seq is increasingly used to characterize transcription factor binding and chromatin marks at a genomic scale. Various tools are now available to extract binding motifs from peak data sets. However, most approaches are only available as command-line programs, or via a website but with size restrictions. We present peak-motifs, a computational pipeline that discovers motifs in peak sequences, compares them with databases, exports putative binding sites for visualization in the UCSC genome browser and generates an extensive report suited for both naive and expert users. It relies on time- and memory-efficient algorithms enabling the treatment of several thousand peaks within minutes. Regarding time efficiency, peak-motifs outperforms all comparable tools by several orders of magnitude. We demonstrate its accuracy by analyzing data sets ranging from 4000 to 1,28,000 peaks for 12 embryonic stem cell-specific transcription factors. In all cases, the program finds the expected motifs and returns additional motifs potentially bound by cofactors. We further apply peak-motifs to discover tissue-specific motifs in peak collections for the p300 transcriptional co-activator. To our knowledge, peak-motifs is the only tool that performs a complete motif analysis and offers a user-friendly web interface without any restriction on sequence size or number of peaks.},

note = {DOI: 10.1093/nar/gkr1104},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{info:hdl:2013/262167,

title = {DNA methylation profiling identifies epigenetic dysregulation in pancreatic islets from type 2 diabetic patients.},

author = {Michael Volkmar and Sarah Dedeurwaerder and Daniel Andrade Da Cunha and Matladi N Ndlovu and Matthieu Defrance and Rachel Deplus and Emilie Calonne and Ute Volkmar and Mariana Igoillo Esteve and Najib Naamane and Silvia Del Guerra and Matilde Masini and Marco Bugliani and Piero Marchetti and Miriam Cnop and Decio L Eizirik and Fran{c c}ois Fuks},

url = {https://dipot.ulb.ac.be/dspace/bitstream/2013/262167/4/PMC3321176.pdf},

year  = {2012},

date = {2012-01-01},

journal = {EMBO journal},

volume = {31},

number = {6},

pages = {1405-1426},

abstract = {In addition to genetic predisposition, environmental and lifestyle factors contribute to the pathogenesis of type 2 diabetes (T2D). Epigenetic changes may provide the link for translating environmental exposures into pathological mechanisms. In this study, we performed the first comprehensive DNA methylation profiling in pancreatic islets from T2D and non-diabetic donors. We uncovered 276 CpG loci affiliated to promoters of 254 genes displaying significant differential DNA methylation in diabetic islets. These methylation changes were not present in blood cells from T2D individuals nor were they experimentally induced in non-diabetic islets by exposure to high glucose. For a subgroup of the differentially methylated genes, concordant transcriptional changes were present. Functional annotation of the aberrantly methylated genes and RNAi experiments highlighted pathways implicated in β-cell survival and function; some are implicated in cellular dysfunction while others facilitate adaptation to stressors. Together, our findings offer new insights into the intricate mechanisms of T2D pathogenesis, underscore the important involvement of epigenetic dysregulation in diabetic islets and may advance our understanding of T2D aetiology.},

note = {DOI: 10.1038/emboj.2011.503},

keywords = {},

pubstate = {published},

tppubtype = {article}

}