Estimation of protein coding density in a corpus of DNA sequence data

A number of experimental methods have been reported for estimating the number of genes in a genome, or the closely related coding density of a genome, defined as the fraction of base pairs in codons. Recently, DNA sequence data representative of the genome as a whole have become available for several organisms, making the problem of estimating coding density amenable to sequence analytic methods. Estimates of coding density for a single genome vary widely, so that methods with characterized error bounds have become increasingly desirable. We present a method to estimate the protein coding density in a corpus of DNA sequence data, in which a ‘coding statistic’ is calculated for a large number of windows of the sequence under study, and the distribution of the statistic is decomposed into two normal distributions, assumed to be the distributions of the coding statistic in the coding and noncoding fractions of the sequence windows. The accuracy of the method is evaluated using known data and application is made to the yeast chromosome III sequence and to C.elegans cosmid sequences. It can also be applied to fragmentary data, for example a collection of short sequences determined in the course of STS mapping.

Identifying protein-coding genes in genomic sequences

The vast majority of the biology of a newly sequenced genome is inferred from the set of encoded proteins. Predicting this set is therefore invariably the first step after the completion of the genome DNA sequence. Here we review the main computational pipelines used to generate the human reference protein-coding gene sets.

Transcription, tagging and coding of bilingual corpora via LIDES

L'objectiu d'aquest informe és presentar l'aplicació d'una sèrie de propostes sobre transcripció, etiquetatge i codificació a dos corpus: el corpus bilingüe LC (La Canonja (Català-Espanyol)) i el corpus trilingüe CSCD (Code-switching as Communicative Design (Català-Espanyol-Anglès)). Aquestes propostes, que constitueixen l'aportació de l'equip IULA-LIPPS (Language Interaction in Plurilingual and Plurilectal Speakers) al manual de codificació del sistema LIDES (Language Interaction Database Exchange System), adoptat pel grup europeu LIPPS, poden ser útils per transcriure, etiquetar i codificar dades provinents de llengües tipològicament properes i distants.

Wavelet analysis residual kriging vs. neural network residual kriging

This paper deals with the problem of spatial data mapping. A new method based on wavelet interpolation and geostatistical prediction (kriging) is proposed. The method - wavelet analysis residual kriging (WARK) - is developed in order to assess the problems rising for highly variable data in presence of spatial trends. In these cases stationary prediction models have very limited application. Wavelet analysis is used to model large-scale structures and kriging of the remaining residuals focuses on small-scale peculiarities. WARK is able to model spatial pattern which features multiscale structure. In the present work WARK is applied to the rainfall data and the results of validation are compared with the ones obtained from neural network residual kriging (NNRK). NNRK is also a residual-based method, which uses artificial neural network to model large-scale non-linear trends. The comparison of the results demonstrates the high quality performance of WARK in predicting hot spots, reproducing global statistical characteristics of the distribution and spatial correlation structure.

Assaying the regulatory potential of mammalian conserved non-coding sequences in human cells.

BACKGROUND: Conserved non-coding sequences in the human genome are approximately tenfold more abundant than known genes, and have been hypothesized to mark the locations of cis-regulatory elements. However, the global contribution of conserved non-coding sequences to the transcriptional regulation of human genes is currently unknown. Deeply conserved elements shared between humans and teleost fish predominantly flank genes active during morphogenesis and are enriched for positive transcriptional regulatory elements. However, such deeply conserved elements account for <1% of the conserved non-coding sequences in the human genome, which are predominantly mammalian. RESULTS: We explored the regulatory potential of a large sample of these 'common' conserved non-coding sequences using a variety of classic assays, including chromatin remodeling, and enhancer/repressor and promoter activity. When tested across diverse human model cell types, we find that the fraction of experimentally active conserved non-coding sequences within any given cell type is low (approximately 5%), and that this proportion increases only modestly when considered collectively across cell types. CONCLUSIONS: The results suggest that classic assays of cis-regulatory potential are unlikely to expose the functional potential of the substantial majority of mammalian conserved non-coding sequences in the human genome.

Dual functions of DP1 promote biphasic Wnt-on and Wnt-off states during anteroposterior neural patterning.

DP1, a dimerization partner protein of the transcription factor E2F, is known to inhibit Wnt/β-catenin signalling along with E2F, although the function of DP1 itself was not well characterized. Here, we present a novel dual regulatory mechanism of Wnt/β-catenin signalling by DP1 independent from E2F. DP1 negatively regulates Wnt/β-catenin signalling by inhibiting Dvl-Axin interaction and by enhancing poly-ubiquitination of β-catenin. In contrast, DP1 positively modulates the signalling upon Wnt stimulation, via increasing cytosolic β-catenin and antagonizing the kinase activity of NLK. In Xenopus embryos, DP1 exerts both positive and negative roles in Wnt/β-catenin signalling during anteroposterior neural patterning. From subcellular localization analyses, we suggest that the dual roles of DP1 in Wnt/β-catenin signalling are endowed by differential nucleocytoplasmic localizations. We propose that these dual functions of DP1 can promote and stabilize biphasic Wnt-on and Wnt-off states in response to a gradual gradient of Wnt/β-catenin signalling to determine differential cell fates.

Identifying protein-coding genes in genomic sequences.

The vast majority of the biology of a newly sequenced genome is inferred from the set of encoded proteins. Predicting this set is therefore invariably the first step after the completion of the genome DNA sequence. Here we review the main computational pipelines used to generate the human reference protein-coding gene sets.

Neuronal autophagy as a mediator of life and death: contrasting roles in chronic neurodegenerative and acute neural disorders.

Autophagy is a cellular mechanism for degrading proteins and organelles. It was first described as a physiological process essential for cellular health and survival, and this is its role in most cells. However, it can also be a mediator of cell death, either by the triggering of apoptosis or by an independent "autophagic" cell death mechanism. This duality is important in the central nervous system, where the activation of autophagy has recently been shown to be protective in certain chronic neurodegenerative diseases but deleterious in acute neural disorders such as stroke and hypoxic/ischemic injury. The authors here discuss these distinct roles of autophagy in the nervous system with a focus on the role of autophagy in mediating neuronal death. The development of new therapeutic strategies based on the manipulation of autophagy will need to take into account these opposing roles of autophagy.

Mapping of the genes coding for the two major vaccinia virus core polypeptides.

We have mapped the genes coding for two major structural polypeptides of the vaccinia virus core by hybrid selection and transcriptional mapping. First, RNA was selected by hybridization to restriction fragments of the vaccinia virus genome, translated in vitro and the products were immunoprecipitated with antibodies against the two polypeptides. This approach allowed us to map the genes to the left hand end of the largest Hind III restriction fragment of 50 kilobase pairs. Second, transcriptional mapping of this region of the genome revealed the presence of the two expected RNAs. Both RNAs are transcribed from the leftward reading strand and the 5'-ends of the genes are separated by about 7.5 kilobase pairs of DNA. Thus, two genes encoding structural polypeptides with a similar location in the vaccinia virus particle are clustered at approximately 105 kilobase pairs from the left hand end of the 180 kilobase pair vaccinia virus genome.

Fuzzy coding in constrained ordinations

Canonical correspondence analysis and redundancy analysis are two methods of constrained ordination regularly used in the analysis of ecological data when several response variables (for example, species abundances) are related linearly to several explanatory variables (for example, environmental variables, spatial positions of samples). In this report I demonstrate the advantages of the fuzzy coding of explanatory variables: first, nonlinear relationships can be diagnosed; second, more variance in the responses can be explained; and third, in the presence of categorical explanatory variables (for example, years, regions) the interpretation of the resulting triplot ordination is unified because all explanatory variables are measured at a categorical level.

Morphometric shape analysis using learning vector quantization neural networks - an example distinguishing two microtine vole species

Closely related species may be very difficult to distinguish morphologically, yet sometimes morphology is the only reasonable possibility for taxonomic classification. Here we present learning-vector-quantization artificial neural networks as a powerful tool to classify specimens on the basis of geometric morphometric shape measurements. As an example, we trained a neural network to distinguish between field and root voles from Procrustes transformed landmark coordinates on the dorsal side of the skull, which is so similar in these two species that the human eye cannot make this distinction. Properly trained neural networks misclassified only 3% of specimens. Therefore, we conclude that the capacity of learning vector quantization neural networks to analyse spatial coordinates is a powerful tool among the range of pattern recognition procedures that is available to employ the information content of geometric morphometrics.

Neural control of vascular reactions: impact of emotion and attention.

This study investigated the neural regions involved in blood pressure reactions to negative stimuli and their possible modulation by attention. Twenty-four healthy human subjects (11 females; age = 24.75 ± 2.49 years) participated in an affective perceptual load task that manipulated attention to negative/neutral distractor pictures. fMRI data were collected simultaneously with continuous recording of peripheral arterial blood pressure. A parametric modulation analysis examined the impact of attention and emotion on the relation between neural activation and blood pressure reactivity during the task. When attention was available for processing the distractor pictures, negative pictures resulted in behavioral interference, neural activation in brain regions previously related to emotion, a transient decrease of blood pressure, and a positive correlation between blood pressure response and activation in a network including prefrontal and parietal regions, the amygdala, caudate, and mid-brain. These effects were modulated by attention; behavioral and neural responses to highly negative distractor pictures (compared with neutral pictures) were smaller or diminished, as was the negative blood pressure response when the central task involved high perceptual load. Furthermore, comparing high and low load revealed enhanced activation in frontoparietal regions implicated in attention control. Our results fit theories emphasizing the role of attention in the control of behavioral and neural reactions to irrelevant emotional distracting information. Our findings furthermore extend the function of attention to the control of autonomous reactions associated with negative emotions by showing altered blood pressure reactions to emotional stimuli, the latter being of potential clinical relevance.

A zero-delay sequential scheme for lossy coding of individual sequences

We consider adaptive sequential lossy coding of bounded individual sequences when the performance is measured by the sequentially accumulated mean squared distortion. Theencoder and the decoder are connected via a noiseless channel of capacity $R$ and both are assumed to have zero delay. No probabilistic assumptions are made on how the sequence to be encoded is generated. For any bounded sequence of length $n$, the distortion redundancy is defined as the normalized cumulative distortion of the sequential scheme minus the normalized cumulative distortion of the best scalarquantizer of rate $R$ which is matched to this particular sequence. We demonstrate the existence of a zero-delay sequential scheme which uses common randomization in the encoder and the decoder such that the normalized maximum distortion redundancy converges to zero at a rate $n^{-1/5}\log n$ as the length of the encoded sequence $n$ increases without bound.