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}



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  title = {High-Resolution Temporal Profiling of Transcripts during Arabidopsis Leaf Senescence Reveals a Distinct Chronology of Processes and Regulation},
  volume = {23},
  number = {3},
  pages = {873--894},
  year = {2011},
  doi = {10.1105/tpc.111.083345},
  publisher = {American Society of Plant Biologists},
  abstract = {Leaf senescence is an essential developmental process that impacts dramatically on crop yields and involves altered regulation of thousands of genes and many metabolic and signaling pathways, resulting in major changes in the leaf. The regulation of senescence is complex, and although senescence regulatory genes have been characterized, there is little information on how these function in the global control of the process. We used microarray analysis to obtain a high-resolution time-course profile of gene expression during development of a single leaf over a 3-week period to senescence. A complex experimental design approach and a combination of methods were used to extract high-quality replicated data and to identify differentially expressed genes. The multiple time points enable the use of highly informative clustering to reveal distinct time points at which signaling and metabolic pathways change. Analysis of motif enrichment, as well as comparison of transcription factor (TF) families showing altered expression over the time course, identify clear groups of TFs active at different stages of leaf development and senescence. These data enable connection of metabolic processes, signaling pathways, and specific TF activity, which will underpin the development of network models to elucidate the process of senescence.},
  issn = {1040-4651},
  URL = {http://www.plantcell.org/content/23/3/873},
  eprint = {http://www.plantcell.org/content/23/3/873.full.pdf},
  journal = {The Plant Cell Online}
}


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    publisher = {American Society of Plant Biologists},
    abstract = {Water availability is the biggest single limitation on plant productivity worldwide. In Arabidopsis, changes in metabolism and gene expression drive increased drought tolerance and initiate diverse drought avoidance and escape responses. To address regulatory processes that link these responses together, we set out to identify novel genes that govern early responses to drought. To do this, a high-resolution time series transcriptomics dataset was produced, coupled with detailed physiological and metabolic analyses of plants subjected to a slow transition from well-watered to drought conditions. 1815 drought-responsive differentially expressed genes were identified. The major early changes in gene expression coincided with a drop in carbon assimilation, and only in the late stages with an increase in foliar abscisic acid content. In order to identify gene regulatory networks (GRNs) mediating the transition between the early and late stages of drought, we used Bayesian network modelling of differentially expressed transcription factor (TF) genes. This approach identified AGAMOUS-LIKE22 as key hub gene in a TF GRN. It has previously been shown that AGL22 is involved in the transition from vegetative state to flowering but here we show that AGL22 expression influences steady state photosynthetic rates and lifetime water use. This suggests that AGL22 uniquely regulates a transcriptional network during drought stress, linking changes in primary metabolism and the initiation of stress responses.},
    issn = {1040-4651},
    URL = {http://www.plantcell.org/content/early/2016/02/03/tpc.15.00910},
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    Title                    = {How to infer gene networks from expression profiles},
    Author                   = {Bansal, Mukesh and Belcastro, Vincenzo and Ambesi-Impiombato, Alberto and Di Bernardo, Diego},
    Journal                  = {Molecular systems biology},
    Year                     = {2007},
    Number                   = {1},
    Volume                   = {3},

    Publisher                = {Wiley Online Library}
    }

    @Article{bar2004analyzing,
    Title                    = {Analyzing time series gene expression data},
    Author                   = {Bar-Joseph, Ziv},
    Journal                  = {Bioinformatics},
    Year                     = {2004},
    Number                   = {16},
    Pages                    = {2493--2503},
    Volume                   = {20},

    Publisher                = {Oxford Univ Press}
    }

    @Book{billings2013nonlinear,
    Title                    = {Nonlinear system identification: NARMAX methods in the time, frequency, and spatio-temporal domains},
    Author                   = {Billings, Stephen A},
    Publisher                = {John Wiley \& Sons},
    Year                     = {2013}
    }

    @Article{chen1989representations,
    Title                    = {Representations of non-linear systems: the NARMAX model},
    Author                   = {Chen, S and Billings, SA},
    Journal                  = {International Journal of Control},
    Year                     = {1989},
    Number                   = {3},
    Pages                    = {1013--1032},
    Volume                   = {49},

    Publisher                = {Taylor \& Francis}
    }

    @InProceedings{chen1999modeling,
    Title                    = {Modeling gene expression with differential equations.},
    Author                   = {Chen, Ting and He, Hongyu L and Church, George M and others},
    Booktitle                = {Pacific symposium on biocomputing},
    Year                     = {1999},
    Number                   = {29},
    Pages                    = {4},
    Volume                   = {4}
    }

    @Article{conesa2006masigpro,
    Title                    = {maSigPro: a method to identify significantly differential expression profiles in time-course microarray experiments},
    Author                   = {Conesa, Ana and Nueda, Mar{\'\i}a Jos{\'e} and Ferrer, Alberto and Tal{\'o}n, Manuel},
    Journal                  = {Bioinformatics},
    Year                     = {2006},
    Number                   = {9},
    Pages                    = {1096--1102},
    Volume                   = {22},

    Publisher                = {Oxford Univ Press}
    }

    @Article{della2008direct,
    Title                    = {Direct targets of the TRP63 transcription factor revealed by a combination of gene expression profiling and reverse engineering},
    Author                   = {Della Gatta, Giusy and Bansal, Mukesh and Ambesi-Impiombato, Alberto and Antonini, Dario and Missero, Caterina and di Bernardo, Diego},
    Journal                  = {Genome research},
    Year                     = {2008},
    Number                   = {6},
    Pages                    = {939--948},
    Volume                   = {18},

    Publisher                = {Cold Spring Harbor Lab}
    }

    @Article{dudoit2002statistical,
    Title                    = {Statistical methods for identifying differentially expressed genes in replicated cDNA microarray experiments},
    Author                   = {Dudoit, Sandrine and Yang, Yee Hwa and Callow, Matthew J and Speed, Terence P},
    Journal                  = {Statistica sinica},
    Year                     = {2002},
    Number                   = {1},
    Pages                    = {111--140},
    Volume                   = {12},

    Publisher                = {C/O DR HC HO, INST STATISTICAL SCIENCE, ACADEMIA SINICA, TAIPEI 115, TAIWAN}
    }

    @InProceedings{friederich2009data,
    Title                    = {Data modelling for analysis of adaptive changes in fly photoreceptors},
    Author                   = {Friederich, Uwe and Coca, Daniel and Billings, Stephen and Juusola, Mikko},
    Booktitle                = {Neural Information Processing},
    Year                     = {2009},
    Organization             = {Springer},
    Pages                    = {34--48}
    }

    @Article{Gao2008,
    Title                    = {Gaussian process modelling of latent chemical species: applications to inferring transcription factor activities},
    Author                   = {Gao, Pei and Honkela, Antti and Rattray, Magnus and Lawrence, Neil D},
    Journal                  = {Bioinformatics},
    Year                     = {2008},
    Number                   = {16},
    Pages                    = {i70--i75},
    Volume                   = {24},

    Owner                    = {jing},
    Publisher                = {Oxford Univ Press},
    Timestamp                = {2014.08.27},
    Url                      = {http://bioinformatics.oxfordjournals.org/content/24/16/i70.short}
    }

    @Article{hardcastle2010bayseq,
    Title                    = {baySeq: empirical {B}ayesian methods for identifying differential expression in sequence count data},
    Author                   = {Hardcastle, Thomas J and Kelly, Krystyna A},
    Journal                  = {BMC bioinformatics},
    Year                     = {2010},
    Number                   = {1},
    Pages                    = {422},
    Volume                   = {11},

    Publisher                = {BioMed Central Ltd}
    }

    @Article{hecker2009gene,
    Title                    = {Gene regulatory network inference: data integration in dynamic models—a review},
    Author                   = {Hecker, Michael and Lambeck, Sandro and Toepfer, Susanne and Van Someren, Eugene and Guthke, Reinhard},
    Journal                  = {Biosystems},
    Year                     = {2009},
    Number                   = {1},
    Pages                    = {86--103},
    Volume                   = {96},

    Publisher                = {Elsevier}
    }

    @Article{Heinonen2014,
    Title                    = {Detecting time periods of differential gene expression using Gaussian processes: An application to endothelial cells exposed to radiotherapy dose fraction.},
    Author                   = {Heinonen, Markus and Guipaud, Olivier and Milliat, Fabien and Buard, Val{\'{e}}rie and Micheau, B{\'{e}}atrice and Tarlet, Georges and Benderitter, Marc and Zehraoui, Farida and d'Alch{\'{e}}-Buc, Florence},
    Journal                  = {Bioinformatics},
    Year                     = {2014},
    Month                    = {Oct},
    Abstract                 = {Identifying the set of genes differentially expressed along time is an important task in two-sample time course experiments. Furthermore, estimating at which time periods the differential expression is present can provide additional insight into the temporal gene functions. The current differential detection methods are designed to detect difference along observation time intervals or on single measurement points, warranting dense measurements along time to characterise the full temporal differential expression patterns.We propose a novel Bayesian likelihood ratio test to estimate the differential expression time periods. Applying the ratio test to systems of genes provides the temporal response timings and durations of gene expression to a biological condition. We introduce a novel non-stationary Gaussian process as the underlying expression model, with major improvements on model fitness on perturbation and stress experiments. The method is robust to uneven or sparse measurements along time. We assess the performance of the method on realistically simulated dataset and compare against state-of-the-art methods. We additionally apply the method to the analysis of primary human endothelial cells under an ionizing radiation stress to study the transcriptional perturbations over 283 measured genes in an attempt to better understand the role of endothelium in both normal and cancer tissues during radiotherapy. As a result, using the cascade of differential expression periods, domain literature and gene enrichment analysis, we gain insights into the dynamic response of endothelial cells to irradiation. Availability: R package is available at www.ibisc.fr/en/logiciels_arobas CONTACT: markus.heinonen@ibisc.fr SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.},
    Doi                      = {10.1093/bioinformatics/btu699},
    Institution              = {IBISC, Universite d'Évry Val d'Essonne, 23 boulevard de France, 91025 Évry, France AMIB, INRIA-Saclay, LRI UMR CNRS 8623, Université Paris Sud, Orsay, France.},
    Language                 = {eng},
    Medline-pst              = {aheadofprint},
    Owner                    = {mbasszmr},
    Pii                      = {btu699},
    Pmid                     = {25355790},
    Timestamp                = {2014.11.10},
    Url                      = {http://dx.doi.org/10.1093/bioinformatics/btu699}
    }

    @Article{Hensman2013,
    Title                    = {Hierarchical {B}ayesian modelling of gene expression time series across irregularly sampled replicates and clusters.},
    Author                   = {Hensman, James and Lawrence, Neil D and Rattray, Magnus},
    Journal                  = {BMC bioinformatics},
    Year                     = {2013},
    Number                   = {1},
    Pages                    = {252},
    Volume                   = {14},
    Owner                    = {jing},
    Timestamp                = {2014.08.27}
    }

    @Article{honkela2010model,
    Title                    = {Model-based method for transcription factor target identification with limited data},
    Author                   = {Honkela, Antti and Girardot, Charles and Gustafson, E Hilary and Liu, Ya-Hsin and Furlong, Eileen EM and Lawrence, Neil D and Rattray, Magnus},
    Journal                  = {Proceedings of the National Academy of Sciences},
    Year                     = {2010},
    Number                   = {17},
    Pages                    = {7793--7798},
    Volume                   = {107},

    Publisher                = {National Acad Sciences}
    }

    @Article{Kalaitzis2011,
    Title                    = {A simple approach to ranking differentially expressed gene expression time courses through {G}aussian process regression},
    Author                   = {Kalaitzis, Alfredo A and Lawrence, Neil D},
    Journal                  = {BMC bioinformatics},
    Year                     = {2011},
    Number                   = {1},
    Pages                    = {180},
    Volume                   = {12},

    Owner                    = {jing},
    Publisher                = {BioMed Central Ltd},
    Timestamp                = {2014.08.27}
    }

    @Article{kalaitzis2011simple,
    Title                    = {A simple approach to ranking differentially expressed gene expression time courses through {G}aussian process regression},
    Author                   = {Kalaitzis, Alfredo A and Lawrence, Neil D},
    Journal                  = {BMC bioinformatics},
    Year                     = {2011},
    Number                   = {1},
    Pages                    = {180},
    Volume                   = {12},

    Publisher                = {BioMed Central Ltd}
    }

    @Article{kerr2000analysis,
    Title                    = {Analysis of variance for gene expression microarray data},
    Author                   = {Kerr, M Kathleen and Martin, Mitchell and Churchill, Gary A},
    Journal                  = {Journal of computational biology},
    Year                     = {2000},
    Number                   = {6},
    Pages                    = {819--837},
    Volume                   = {7},

    Publisher                = {Mary Ann Liebert, Inc.}
    }

    @Article{kim2013method,
    Title                    = {A method to identify differential expression profiles of time-course gene data with Fourier transformation},
    Author                   = {Kim, Jaehee and Ogden, Robert Todd and Kim, Haseong},
    Journal                  = {BMC bioinformatics},
    Year                     = {2013},
    Number                   = {1},
    Pages                    = {310},
    Volume                   = {14},

    Publisher                = {BioMed Central Ltd}
    }

    @Article{Lawrence2005,
    Title                    = {Probabilistic non-linear principal component analysis with Gaussian process latent variable models},
    Author                   = {Lawrence, Neil},
    Journal                  = {The Journal of Machine Learning Research},
    Year                     = {2005},
    Pages                    = {1783--1816},
    Volume                   = {6},
    Owner                    = {jing},
    Publisher                = {JMLR. org},
    Timestamp                = {2014.08.27},
    Url                      = {http://dl.acm.org/citation.cfm?id=1194904}
    }

    @Book{press1996numerical,
    Title                    = {Numerical recipes in C},
    Author                   = {Press, William H and Teukolsky, Saul A and Vetterling, William T and Flannery, Brian P},
    Publisher                = {Cambridge: Cambridge university press},
    Year                     = {1996},
    Volume                   = {2}
    }

    @Article{rapaport2013comprehensive,
    Title                    = {Comprehensive evaluation of differential gene expression analysis methods for RNA-seq data},
    Author                   = {Rapaport, Franck and Khanin, Raya and Liang, Yupu and Pirun, Mono and Krek, Azra and Zumbo, Paul and Mason, Christopher E and Socci, Nicholas D and Betel, Doron},
    Journal                  = {Genome biology},
    Year                     = {2013},
    Number                   = {9},
    Pages                    = {R95},
    Volume                   = {14},

    Publisher                = {BioMed Central Ltd}
    }

    @Article{robinson2010edger,
    Title                    = {edgeR: a Bioconductor package for differential expression analysis of digital gene expression data},
    Author                   = {Robinson, Mark D and McCarthy, Davis J and Smyth, Gordon K},
    Journal                  = {Bioinformatics},
    Year                     = {2010},
    Number                   = {1},
    Pages                    = {139--140},
    Volume                   = {26},

    Publisher                = {Oxford Univ Press}
    }

    @InCollection{smyth2005limma,
    Title                    = {Limma: linear models for microarray data},
    Author                   = {Smyth, Gordon K},
    Booktitle                = {Bioinformatics and computational biology solutions using R and Bioconductor},
    Publisher                = {Springer},
    Year                     = {2005},
    Pages                    = {397--420}
    }

    @Article{Stegle2010robust,
    Title                    = {A robust Bayesian two-sample test for detecting intervals of differential gene expression in microarray time series},
    Author                   = {Stegle, Oliver and Denby, Katherine J and Cooke, Emma J and Wild, David L and Ghahramani, Zoubin and Borgwardt, Karsten M},
    Journal                  = {Journal of Computational Biology},
    Year                     = {2010},
    Number                   = {3},
    Pages                    = {355--367},
    Volume                   = {17},
    Owner                    = {jing},
    Publisher                = {Mary Ann Liebert, Inc. 140 Huguenot Street, 3rd Floor New Rochelle, NY 10801 USA},
    Timestamp                = {2014.06.23},
    Url                      = {http://online.liebertpub.com/doi/abs/10.1089/cmb.2009.0175}
    }


    @article{yang2016inferring,
    title={Inferring the perturbation time from biological time course data},
    author={Yang, Jing and Penfold, Christopher A and Grant, Murray R and Rattray, Magnus},
    journal={arXiv preprint arXiv:1602.01743},
    year={2016}
    }

    @article{wang2010pseudomonas,
    title={A \emph{Pseudomonas syringae} {ADP}-ribosyltransferase inhibits {A}rabidopsis mitogen-activated protein kinase kinases},
    author={Wang, Yujing and Li, Jifeng and Hou, Shuguo and Wang, Xingwei and Li, Yuan and Ren, Dongtao and Chen, She and Tang, Xiaoyan and Zhou, Jian-Min},
    journal={The Plant Cell},
    volume={22},
    number={6},
    pages={2033--2044},
    year={2010},
    publisher={Am Soc Plant Biol}
    }

    @article{hua2006activation,
    title={Activation of the NaCl-and drought-induced {RD29A} and {RD29B} promoters by constitutively active {A}rabidopsis {MAPKK} or {MAPK} proteins},
    author={HUA, ZHI-MING and Yang, Xianci and Fromm, Michael E},
    journal={Plant, cell \& environment},
    volume={29},
    number={9},
    pages={1761--1770},
    year={2006},
    publisher={Wiley Online Library}
    }

    @article{kong2012mekk1,
    title={The {MEKK1}-{MKK1}/{MKK2}-{MPK4} kinase cascade negatively regulates immunity mediated by a mitogen-activated protein kinase kinase kinase in {A}rabidopsis},
    author={Kong, Qing and Qu, Na and Gao, Minghui and Zhang, Zhibin and Ding, Xiaojun and Yang, Fan and Li, Yingzhong and Dong, Oliver X and Chen, She and Li, Xin and others},
    journal={The Plant Cell},
    volume={24},
    number={5},
    pages={2225--2236},
    year={2012},
    publisher={Am Soc Plant Biol}
    }

    @Article{storey2005significance,
    Title                    = {Significance analysis of time course microarray experiments},
    Author                   = {Storey, John D and Xiao, Wenzhong and Leek, Jeffrey T and Tompkins, Ronald G and Davis, Ronald W},
    Journal                  = {Proceedings of the National Academy of Sciences of the United States of America},
    Year                     = {2005},
    Number                   = {36},
    Pages                    = {12837--12842},
    Volume                   = {102},
    Publisher                = {National Acad Sciences}
    }

    @Article{wang2009extended,
    Title                    = {An extended Kalman filtering approach to modeling nonlinear dynamic gene regulatory networks via short gene expression time series},
    Author                   = {Wang, Zidong and Liu, Xiaohui and Liu, Yurong and Liang, Jinling and Vinciotti, Veronica},
    Journal                  = {IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)},
    Year                     = {2009},
    Number                   = {3},
    Pages                    = {410--419},
    Volume                   = {6},
    Publisher                = {IEEE Computer Society Press}
    }

    @Article{weber2011modeling,
    Title                    = {Modeling, inference and optimization of regulatory networks based on time series data},
    Author                   = {Weber, Gerhard-Wilhelm and Defterli, Ozlem and Alparslan G{\"o}k, S{\i}rma Zeynep and Kropat, Erik},
    Journal                  = {European Journal of Operational Research},
    Year                     = {2011},
    Number                   = {1},
    Pages                    = {1--14},
    Volume                   = {211},
    Publisher                = {Elsevier}
    }

    @Book{Williams2006,
    Title                    = {Gaussian processes for machine learning},
    Author                   = {Williams, Christopher KI and Rasmussen, Carl Edward},
    Publisher                = {the MIT Press},
    Year                     = {2006},
    Volume                   = {2},
    Owner                    = {root},
    Pages                    = {4},
    Timestamp                = {2014.06.19}
    }

    @InProceedings{wu2004modeling,
    Title                    = {Modeling gene expression from microarray expression data with state-space equations.},
    Author                   = {Wu, Fang-Xiang and Zhang, Wen-Jun and Kusalik, Anthony J},
    Booktitle                = {Pacific Symposium on Biocomputing},
    Year                     = {2004},
    Pages                    = {581--592},
    Volume                   = {9}
    }

    @Article{yuan2006flexible,
    Title                    = {Flexible temporal expression profile modelling using the Gaussian process},
    Author                   = {Yuan, Ming},
    Journal                  = {Computational statistics \& data analysis},
    Year                     = {2006},
    Number                   = {3},
    Pages                    = {1754--1764},
    Volume                   = {51},

    Publisher                = {Elsevier}
    }

@ARTICLE{Park2016,
author={Park, H.S. and Rinehart, M.T. and Walzer, K.A. and Ashley Chi, J.-T. and Wax, A.},
title={Automated Detection of P. falciparum using machine learning algorithms with quantitative phase images of unstained cells},
journal={PLoS ONE},
year={2016},
volume={11},
number={9},
doi={10.1371/journal.pone.0163045},
art_number={e0163045},
url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-84992390993&doi=10.1371%2fjournal.pone.0163045&partnerID=40&md5=e482a85eb642e2b94c75121f9cd9540d}
}