Sensitivity to horizontal and vertical corrugations defined by binocular disparity

AbstractSensitivity to corrugations defined by binocular disparity differs as a function of the modulation frequency. Such functions have proved to be useful descriptive and analytical tools in the study of the mechanisms involved in disparity processing. Indeed, given certain assumptions, these sensitivity functions can be used to predict certain perceptual outcomes. Given their importance, it is surprising that there is no comprehensive data set of disparity sensitivity functions (DSF) for a range of observers over a broad range of spatial frequencies and orientations. Here we report DSFs for six observers over an eight octave range of sinusoidal corrugations in disparity (0.0125–3.2 cpd). Multi-cycle, low frequency surfaces were used to assess the degree to which the fall-off in sensitivity at low corrugation frequencies is attributable to the decreasing number of cycles displayed. The data was found to form a continuous function despite the different number of cycles displayed. We conclude that the fall off in sensitivity is due to the spatial interactions in disparity processing. We also determined DSFs for the same observers to both vertically and horizontally oriented sinusoidal disparity corrugations in order to characterise the extent of the stereoscopic anisotropy In general, the best thresholds for detecting vertically oriented disparity corrugations were higher (∼4 arc sec) than for horizontally oriented corrugations (∼2 arc sec). Moreover, the functions were shifted toward the high spatial frequency end of the spectrum

Performance of a 120 m2 solar air heater for a commercial building in Victoria

The operation of two 60 m2 solar air heaters serving a large studio teaching space has been monitored for a twelve month period. The solar contribution of the heaters was found to be less than 5%, and in some instances the heaters actually contributed to the space heating load. A validated mathematical model of the studio and it&rsquo;s heating, ventilation and air conditioning system was used to investigate performance improvement strategies. It was found a different control strategy and recommissioned control sensors would substantially improve the solar air heater performance.<br /

Prediction of driver variants in the cancer genome via machine learning methodologies

Sequencing technologies have led to the identification of many variants in the human genome which could act as disease-drivers. As a consequence, a variety of bioinformatics tools have been proposed for predicting which variants may drive disease, and which may be causatively neutral. After briefly reviewing generic tools, we focus on a subset of these methods specifically geared toward predicting which variants in the human cancer genome may act as enablers of unregulated cell proliferation. We consider the resultant view of the cancer genome indicated by these predictors and discuss ways in which these types of prediction tools may be progressed by further research

SpliceGrapher: detecting patterns of alternative splicing from RNA-Seq data in the context of gene models and EST data

We propose a method for predicting splice graphs that enhances curated gene models using evidence from RNA-Seq and EST alignments. Results obtained using RNA-Seq experiments in Arabidopsis thaliana show that predictions made by our SpliceGrapher method are more consistent with current gene models than predictions made by TAU and Cufflinks. Furthermore, analysis of plant and human data indicates that the machine learning approach used by SpliceGrapher is useful for discriminating between real and spurious splice sites, and can improve the reliability of detection of alternative splicing. SpliceGrapher is available for download at http://SpliceGrapher.sf.net

Genome-wide analysis of alternative splicing in Chlamydomonas reinhardtii

<p>Abstract</p> <p>Background</p> <p>Genome-wide computational analysis of alternative splicing (AS) in several flowering plants has revealed that pre-mRNAs from about 30% of genes undergo AS. <it>Chlamydomonas</it>, a simple unicellular green alga, is part of the lineage that includes land plants. However, it diverged from land plants about one billion years ago. Hence, it serves as a good model system to study alternative splicing in early photosynthetic eukaryotes, to obtain insights into the evolution of this process in plants, and to compare splicing in simple unicellular photosynthetic and non-photosynthetic eukaryotes. We performed a global analysis of alternative splicing in <it>Chlamydomonas reinhardtii </it>using its recently completed genome sequence and all available ESTs and cDNAs.</p> <p>Results</p> <p>Our analysis of AS using BLAT and a modified version of the Sircah tool revealed AS of 498 transcriptional units with 611 events, representing about 3% of the total number of genes. As in land plants, intron retention is the most prevalent form of AS. Retained introns and skipped exons tend to be shorter than their counterparts in constitutively spliced genes. The splice site signals in all types of AS events are weaker than those in constitutively spliced genes. Furthermore, in alternatively spliced genes, the prevalent splice form has a stronger splice site signal than the non-prevalent form. Analysis of constitutively spliced introns revealed an over-abundance of motifs with simple repetitive elements in comparison to introns involved in intron retention. In almost all cases, AS results in a truncated ORF, leading to a coding sequence that is around 50% shorter than the prevalent splice form. Using RT-PCR we verified AS of two genes and show that they produce more isoforms than indicated by EST data. All cDNA/EST alignments and splice graphs are provided in a website at <url>http://combi.cs.colostate.edu/as/chlamy</url>.</p> <p>Conclusions</p> <p>The extent of AS in <it>Chlamydomonas </it>that we observed is much smaller than observed in land plants, but is much higher than in simple unicellular heterotrophic eukaryotes. The percentage of different alternative splicing events is similar to flowering plants. Prevalence of constitutive and alternative splicing in <it>Chlamydomonas</it>, together with its simplicity, many available public resources, and well developed genetic and molecular tools for this organism make it an excellent model system to elucidate the mechanisms involved in regulated splicing in photosynthetic eukaryotes.</p

Deciphering the Plant Splicing Code: Experimental and Computational Approaches for Predicting Alternative Splicing and Splicing Regulatory Elements

Extensive alternative splicing (AS) of precursor mRNAs (pre-mRNAs) in multicellular eukaryotes increases the protein-coding capacity of a genome and allows novel ways to regulate gene expression. In flowering plants, up to 48% of intron-containing genes exhibit AS. However, the full extent of AS in plants is not yet known, as only a few high-throughput RNA-Seq studies have been performed. As the cost of obtaining RNA-Seq reads continues to fall, it is anticipated that huge amounts of plant sequence data will accumulate and help in obtaining a more complete picture of AS in plants. Although it is not an onerous task to obtain hundreds of millions of reads using high-throughput sequencing technologies, computational tools to accurately predict and visualize AS are still being developed and refined. This review will discuss the tools to predict and visualize transcriptome-wide AS in plants using short-reads and highlight their limitations. Comparative studies of AS events between plants and animals have revealed that there are major differences in the most prevalent types of AS events, suggesting that plants and animals differ in the way they recognize exons and introns. Extensive studies have been performed in animals to identify cis-elements involved in regulating AS, especially in exon skipping. However, few such studies have been carried out in plants. Here, we review the current state of research on splicing regulatory elements (SREs) and briefly discuss emerging experimental and computational tools to identify cis-elements involved in regulation of AS in plants. The availability of curated alternative splice forms in plants makes it possible to use computational tools to predict SREs involved in AS regulation, which can then be verified experimentally. Such studies will permit identification of plant-specific features involved in AS regulation and contribute to deciphering the splicing code in plants

Scaling in Late Stage Spinodal Decomposition with Quenched Disorder

We study the late stages of spinodal decomposition in a Ginzburg-Landau mean field model with quenched disorder. Random spatial dependence in the coupling constants is introduced to model the quenched disorder. The effect of the disorder on the scaling of the structure factor and on the domain growth is investigated in both the zero temperature limit and at finite temperature. In particular, we find that at zero temperature the domain size, $R(t)$, scales with the amplitude, $A$, of the quenched disorder as $R(t) = A^{-\beta} f(t/A^{-\gamma})$ with $\beta \simeq 1.0$ and $\gamma \simeq 3.0$ in two dimensions. We show that $\beta/\gamma = \alpha$, where $\alpha$ is the Lifshitz-Slyosov exponent. At finite temperature, this simple scaling is not observed and we suggest that the scaling also depends on temperature and $A$. We discuss these results in the context of Monte Carlo and cell dynamical models for phase separation in systems with quenched disorder, and propose that in a Monte Carlo simulation the concentration of impurities, $c$, is related to $A$ by $A \sim c^{1/d}$.Comment: RevTex manuscript 5 pages and 5 figures (obtained upon request via email [email protected]

An integrative approach to predicting the functional effects of small indels in non-coding regions of the human genome

Background: Small insertions and deletions (indels) have a significant influence in human disease and, in terms of frequency, they are second only to single nucleotide variants as pathogenic mutations. As the majority of mutations associated with complex traits are located outside the exome, it is crucial to investigate the potential pathogenic impact of indels in non-coding regions of the human genome. Results: We present FATHMM-indel, an integrative approach to predict the functional effect, pathogenic or neutral, of indels in non-coding regions of the human genome. Our method exploits various genomic annotations in addition to sequence data. When validated on benchmark data, FATHMM-indel significantly outperforms CADD and GAVIN, state of the art models in assessing the pathogenic impact of non-coding variants. FATHMM-indel is available via a web server at indels.biocompute.org.uk. Conclusions: FATHMM-indel can accurately predict the functional impact and prioritise small indels throughout the whole non-coding genome