Jonathan Filée also created these companion sites
Other Companion Sites on same paper
Other Companion Sites relative to similar papers
ScrewFit : combining localization and description of protein secondary structure
A simple and efficient method is presented to describe the secondary structure of proteins in terms of orientational distances between consecutive peptide planes and local helix parameters. The method uses quaternion-based superposition fits of the protein peptide planes in conjunction with Chasles’ theorem, which states that any rigid-body displacement can be described by a screw motion. The helix parameters are derived from the best superposition of consecutive peptide planes and the ‘worst’ fit is used to define the orientational distance. Applications are shown for standard secondary-structure motifs of peptide chains for several proteins belonging to different fold classes and for a description of structural changes in lysozyme under hydrostatic pressure. In the latter case, published reference data obtained by X-ray crystallo- graphy and by structural NMR measurements are used.
Dendrodendritic Inhibition and Simulated Odor Responses in a Detailed Olfactory Bulb Network Model
In the olfactory bulb, both the spatial distribution and the temporal structure of neuronal activity appear to be important for processing odor information, but it is currently impossible to measure both of these simultaneously with high resolution and in all layers of the bulb. We have developed a biologically realistic model of the mammalian olfactory bulb, incorporating the mitral and granule cells and the dendrodendritic synapses between them, which allows us to observe the network behavior in detail. The cell models were based on previously published work. The attributes of the synapses were obtained from the literature. The pattern of synaptic connections was based on the limited experimental data in the literature on the statistics of connections between neurons in the bulb. The results of simulation experiments with electrical stimulation agree closely in most details with published experimental data. This gives confidence that the model is capturing features of network interactions in the real olfactory bulb. The model predicts that the time course of dendrodendritic inhibition is dependent on the network connectivity as well as on the intrinsic parameters of the synapses. In response to simulated odor stimulation, strongly activated mitral cells tend to suppress neighboring cells, the mitral cells readily synchronize their firing, and increasing the stimulus intensity increases the degree of synchronization. Preliminary experiments suggest that slow temporal changes in the degree of synchronization are more useful in distinguishing between very similar odorants than is the spatial distribution of mean firing rate.
Generic allometric models including height best estimate forest biomass and carbon stocks in Indonesia
The choice of an appropriate allometric model is a critical step in reducing uncertainties in forest biomass stock estimates. With large greenhouse gases emissions due to deforestation, a systematic assessment and comparison of the models available in Indonesia is crucial for accurate assessments of forest carbon stocks and implementing REDD+ projects. In the present study, we compared the ability of two regional and two generic (pantropical) allometric models to estimate biomass at both tree and plot levels. We showed that regional models had lower performance in estimating tree biomass, with greater bias (-31 to 8 %) and higher AIC (177 to 204), compared to generic models (bias: -2 to 2 %; AIC: 57 to 67). At the plot level, the regional models underestimated biomass stocks by 0 – 40 % compared to the best generic model. The error in plot biomass stocks associated to models relying solely upon DBH ranged between -5 to +15 %. The integration of tree height estimated regionally resulted in an overestimate of 5 – 10 % in unmanaged forests. Despite the difficulty to accurately assess tree heights in tropical forests, integrating all or part of them in biomass assessment can reduce uncertainties.
Didn't find your answer ?
Frequently Asked Questions