Yann Guédon

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The plant hormone auxin is thought to provide positional information for patterning during development. It is still unclear, however, precisely how auxin is distributed across tissues and how the hormone is sensed in space and time. The control of gene expression in response to auxin involves a complex network of over 50 potentially interacting(More)
How biological systems generate reproducible patterns with high precision is a central question in science. The shoot apical meristem (SAM), a specialized tissue producing plant aerial organs, is a developmental system of choice to address this question. Organs are periodically initiated at the SAM at specific spatial positions and this spatiotemporal(More)
The hidden Markov tree models were introduced by Crouse et al. in 1998 for modeling nonindependent, non-Gaussian wavelet transform coefficients. In their paper, they developed the equivalent of the forward-backward algorithm for hidden Markov tree models and called it the "upward-downward algorithm". This algorithm is subject to the same numerical(More)
The structure resulting from branching on 1-year-old apple tree trunks was analysed in a set of apple cultivars with diverse branching and fruiting habits. Four different lateral types borne on successive nodes were observed when vegetative and flowering fates, as well as sylleptic and proleptic branching, were taken into account. The location and grouping(More)
In the architectural approach to the study of plants, a major issue is to analyse branching and axillary flowering patterns. Due to the structured expression of the branching process and the noisy character of the observed patterns, we propose an analysis framework which is both structural and probabilistic. Data take the form of sequences which naturally(More)
Plant architecture is the result of repetitions that occur through growth and branching processes. During plant ontogeny, changes in the morphological characteristics of plant entities are interpreted as the indirect translation of different physiological states of the meristems. Thus connected entities can exhibit either similar or very contrasted(More)
The knowledge of the state sequences that explain a given observed sequence for a known hidden Markovian model is the basis of various methods that may be divided into three categories: (i) enumeration of state sequences; (ii) summary of the possible state sequences in state profiles; (iii) computation of a global measure of the state sequence uncertainty.(More)
Models that combine Markovian states with implicit geometric state occupancy distributions and semi-Markovian states with explicit state occupancy distributions, are investigated. This type of model retains the flexibility of hidden semi-Markov chains for the modeling of short or medium size homogeneous zones along sequences but also enables the modeling of(More)
An architectural analysis of the root system of young oil-palm (Elaeis guineensis Jacq.) seedlings was made. In this analysis, root branching was modelled by a Markov chain (discrete-time, discrete-state space stochastic process). This study has been realized on radicles of young oil-palm seedlings which were considered as main axes which branch. We defined(More)
BACKGROUND AND AIMS Neoformation is the process by which organs not preformed in a bud are developed on a growing shoot, generally after preformation extension. The study of neoformation in trees has been hindered due to methodological reasons. The present report is aimed at assessing the relative importance of preformation and neoformation in the(More)