ProbCD: enrichment analysis accounting for categorization uncertainty

As in many other areas of science, systems biology makes extensive use of statistical association and significance estimates in contingency tables, a type of categorical data analysis known in this field as enrichment (also over-representation or enhancement) analysis. In spite of efforts to create probabilistic annotations, especially in the Gene Ontology context, or to deal with uncertainty in high throughput-based datasets, current enrichment methods largely ignore this probabilistic information since they are mainly based on variants of the Fisher Exact Test. We developed an open-source R package to deal with probabilistic categorical data analysis, ProbCD, that does not require a static contingency table. The contingency table for
the enrichment problem is built using the expectation of a Bernoulli Scheme stochastic process given the categorization probabilities. An on-line interface was created to allow usage by non-programmers and is available at: http://xerad.systemsbiology.net/ProbCD/. We present an analysis framework and software tools to address the issue of uncertainty in categorical data analysis. In particular, concerning the enrichment analysis, ProbCD can accommodate: (i) the stochastic nature of the high-throughput experimental techniques and (ii) probabilistic gene annotation

Neural Modeling and Control of Diesel Engine with Pollution Constraints

The paper describes a neural approach for modelling and control of a turbocharged Diesel engine. A neural model, whose structure is mainly based on some physical equations describing the engine behaviour, is built for the rotation speed and the exhaust gas opacity. The model is composed of three interconnected neural submodels, each of them constituting a nonlinear multi-input single-output error model. The structural identification and the parameter estimation from data gathered on a real engine are described. The neural direct model is then used to determine a neural controller of the engine, in a specialized training scheme minimising a multivariable criterion. Simulations show the effect of the pollution constraint weighting on a trajectory tracking of the engine speed. Neural networks, which are flexible and parsimonious nonlinear black-box models, with universal approximation capabilities, can accurately describe or control complex nonlinear systems, with little a priori theoretical knowledge. The presented work extends optimal neuro-control to the multivariable case and shows the flexibility of neural optimisers. Considering the preliminary results, it appears that neural networks can be used as embedded models for engine control, to satisfy the more and more restricting pollutant emission legislation. Particularly, they are able to model nonlinear dynamics and outperform during transients the control schemes based on static mappings.Comment: 15 page

Infinite factorization of multiple non-parametric views

Combined analysis of multiple data sources has increasing application interest, in particular for distinguishing shared and source-specific aspects. We extend this rationale of classical canonical correlation analysis into a flexible, generative and non-parametric clustering setting, by introducing a novel non-parametric hierarchical mixture model. The lower level of the model describes each source with a flexible non-parametric mixture, and the top level combines these to describe commonalities of the sources. The lower-level clusters arise from hierarchical Dirichlet Processes, inducing an infinite-dimensional contingency table between the views. The commonalities between the sources are modeled by an infinite block model of the contingency table, interpretable as non-negative factorization of infinite matrices, or as a prior for infinite contingency tables. With Gaussian mixture components plugged in for continuous measurements, the model is applied to two views of genes, mRNA expression and abundance of the produced proteins, to expose groups of genes that are co-regulated in either or both of the views. Cluster analysis of co-expression is a standard simple way of screening for co-regulation, and the two-view analysis extends the approach to distinguishing between pre- and post-translational regulation

Large mammal diets and paleoecology across the Oldowan–Acheulean transition at Olduvai Gorge, Tanzania from stable isotope and tooth wear analyses

The well-dated Pleistocene sediments at Olduvai Gorge have yielded a rich record of hominin fossils, stone tools, and vertebrate faunal remains that, taken together, provide insight to hominin behavior and paleoecology. Since 2008, the Olduvai Geochronology and Archaeology Project (OGAP) has undertaken extensive excavations in Bed II that have yielded a large collection of early Pleistocene stone tools and fossils. The strata of Lower, Middle and Upper Bed II at Olduvai Gorge capture the critical transition from Oldowan to Acheulean technology and therefore provide an opportunity to explore the possible role of biotic and abiotic change during the transition. Here, we analyze newly discovered and existing fossil teeth from Bed II sites using stable isotope and tooth wear methods to investigate the diets of large mammals. We reconstruct the dietary ecology of Bed II mammals and evaluate whether vegetation or hydroclimate shifts are associated with the technological change. Combined isotope and tooth wear data suggest most mammals were C4 grazers or mixed feeders. Carbon isotope data from bulk enamel samples indicate that a large majority of Bed II large mammals analyzed had diets comprising mostly C4 vegetation (>75% of diet), whereas only a small number of individuals had either mixed C3–C4 or mostly C3 diets (<25% C4). Mesowear generally indicates an increase of the abrasiveness of the diet between intervals IIA and IIB (∼1.66 Ma), probably reflecting increased grazing. Microwear indicates more abrasive diets in interval IIA suggesting stronger seasonal differences at the time of death during this interval. This is also supported by the intratooth isotope profiles from Equus oldowayensis molars, which suggest a possible decrease in seasonality across the transition. Neither stable isotope nor tooth wear analyses indicate major vegetation or hydrological change across the Oldowan–Acheulean transition

Dietary traits of the ungulates from the HWK EE site at Olduvai Gorge (Tanzania): Diachronic changes and seasonality

The Oldowan site HWK EE (Olduvai Gorge, Tanzania) has yielded a large fossil and stone tool assemblage at the transition from Lower to Middle Bed II, ∼1.7 Ma. Integrated tooth wear and stable isotope analyses were performed on the three most abundant ungulate taxa from HWK EE, namely Alcelaphini, cf. Antidorcas recki (Antilopini) and Equus oldowayensis (Equini), to infer dietary traits in each taxon. Some paleodietary changes were observed for cf. A. recki and E. oldowayensis based on tooth wear at the transition from the Lemuta to the Lower Augitic Sandstone (LAS) interval within the HWK EE sequence. Stable carbon and oxygen isotope data show no significant changes in bulk diet or hydroclimate between the Lemuta and LAS intervals. The combined tooth wear and stable isotope data suggest similar paleoecological conditions across the two HWK EE intervals, but that differences in vegetation consumed among ungulates may have resulted in changes in dietary niches. Integrating tooth wear and stable isotope analyses permits the characterization of ungulate diets and habitats at HWK EE where C4 dominated and minor mixed C3 and C4 habitats were present. Our results provide a better understanding of the paleoenvironmental conditions of the Lemuta and LAS intervals. The LAS assemblage was mostly accumulated during relatively dry periods at Olduvai Gorge when grasses were not as readily available and grazing animals may have been more nutritionally-stressed than during the formation of the Lemuta assemblage. This helps to contextualize variations in hominin and carnivore feeding behavior observed from the faunal assemblages produced during the two main occupations of the site

Detecting microsatellites within genomes: significant variation among algorithms

<p>Abstract</p> <p>Background</p> <p>Microsatellites are short, tandemly-repeated DNA sequences which are widely distributed among genomes. Their structure, role and evolution can be analyzed based on exhaustive extraction from sequenced genomes. Several dedicated algorithms have been developed for this purpose. Here, we compared the detection efficiency of five of them (TRF, Mreps, Sputnik, STAR, and RepeatMasker).</p> <p>Results</p> <p>Our analysis was first conducted on the human X chromosome, and microsatellite distributions were characterized by microsatellite number, length, and divergence from a pure motif. The algorithms work with user-defined parameters, and we demonstrate that the parameter values chosen can strongly influence microsatellite distributions. The five algorithms were then compared by fixing parameters settings, and the analysis was extended to three other genomes (<it>Saccharomyces cerevisiae</it>, <it>Neurospora crassa </it>and <it>Drosophila melanogaster</it>) spanning a wide range of size and structure. Significant differences for all characteristics of microsatellites were observed among algorithms, but not among genomes, for both perfect and imperfect microsatellites. Striking differences were detected for short microsatellites (below 20 bp), regardless of motif.</p> <p>Conclusion</p> <p>Since the algorithm used strongly influences empirical distributions, studies analyzing microsatellite evolution based on a comparison between empirical and theoretical size distributions should therefore be considered with caution. We also discuss why a typological definition of microsatellites limits our capacity to capture their genomic distributions.</p

The cerebellar transcriptome during postnatal development of the Ts1Cje mouse, a segmental trisomy model for Down syndrome

The central nervous system of persons with Down syndrome presents cytoarchitectural abnormalities that likely result from gene-dosage effects affecting the expression of key developmental genes. To test this hypothesis, we have investigated the transcriptome of the cerebellum of the Ts1Cje mouse model of Down syndrome during postnatal development using microarrays and quantitative PCR (qPCR). Genes present in three copies were consistently overexpressed, with a mean ratio relative to euploid of 1.52 as determined by qPCR. Out of 63 three-copy genes tested, only five, nine and seven genes had ratios >2 or <1.2 at postnatal days 0 (P0), P15 and P30, respectively. This gene-dosage effect was associated with a dysregulation of the expression of some two-copy genes. Out of 8258 genes examined, the Ts1Cje/euploid ratios differed significantly from 1.0 for 406 (80 and 154 with ratios above 1.5 and below 0.7, respectively), 333 (11 above 1.5 and 55 below 0.7) and 246 genes (59 above 1.5 and 69 below 0.7) at P0, P15 and P30, respectively. Among the two-copy genes differentially expressed in the trisomic cerebellum, six homeobox genes, two belonging to the Notch pathway, were severely repressed. Overall, at P0, transcripts involved in cell differentiation and development were over-represented among the dysregulated genes, suggesting that cell differentiation and migration might be more altered than cell proliferation. Finally, global gene profiling revealed that transcription in Ts1Cje mice is more affected by the developmental changes than by the trisomic state, and that there is no apparent detectable delay in the postnatal development of the cerebellum of Ts1Cje mic

String Matching and 1d Lattice Gases

We calculate the probability distributions for the number of occurrences $n$ of a given $l$ letter word in a random string of $k$ letters. Analytical expressions for the distribution are known for the asymptotic regimes (i) $k \gg r^l \gg 1$ (Gaussian) and $k,l \to \infty$ such that $k/r^l$ is finite (Compound Poisson). However, it is known that these distributions do now work well in the intermediate regime $k \gtrsim r^l \gtrsim 1$. We show that the problem of calculating the string matching probability can be cast into a determining the configurational partition function of a 1d lattice gas with interacting particles so that the matching probability becomes the grand-partition sum of the lattice gas, with the number of particles corresponding to the number of matches. We perform a virial expansion of the effective equation of state and obtain the probability distribution. Our result reproduces the behavior of the distribution in all regimes. We are also able to show analytically how the limiting distributions arise. Our analysis builds on the fact that the effective interactions between the particles consist of a relatively strong core of size $l$, the word length, followed by a weak, exponentially decaying tail. We find that the asymptotic regimes correspond to the case where the tail of the interactions can be neglected, while in the intermediate regime they need to be kept in the analysis. Our results are readily generalized to the case where the random strings are generated by more complicated stochastic processes such as a non-uniform letter probability distribution or Markov chains. We show that in these cases the tails of the effective interactions can be made even more dominant rendering thus the asymptotic approximations less accurate in such a regime.Comment: 44 pages and 8 figures. Major revision of previous version. The lattice gas analogy has been worked out in full, including virial expansion and equation of state. This constitutes the main part of the paper now. Connections with existing work is made and references should be up to date now. To be submitted for publicatio

Unraveling a Neanderthal palimpsest from a zooarcheological and taphonomic perspective

Practically all archeological assemblages are palimpsests. In spite of the high temporal resolution of Abric Romaní site, level O, dated to around 55 ka, is not an exception. This paper focuses on a zooarcheological and taphonomic analysis of this level, paying special attention to spatial and temporal approaches. The main goal is to unravel the palimpsest at the finest possible level by using different methods and techniques, such as archeostratigraphy, anatomical and taxonomical identification, taphonomic analysis, faunal refits and tooth wear analysis. The results obtained are compared to ethnoarcheological data so as to interpret site structure. In addition, activities carried out over different time spans (from individual episodes to long-term behaviors) are detected, and their spatial extent is explored, allowing to do inferences on settlement dynamics. This leads us to discuss the temporal and spatial scales over which Neanderthals carried out different activities within the site, and how they can be studied through the archeological record