A copula method for modeling directional dependence of genes

<p>Abstract</p> <p>Background</p> <p>Genes interact with each other as basic building blocks of life, forming a complicated network. The relationship between groups of genes with different functions can be represented as gene networks. With the deposition of huge microarray data sets in public domains, study on gene networking is now possible. In recent years, there has been an increasing interest in the reconstruction of gene networks from gene expression data. Recent work includes linear models, Boolean network models, and Bayesian networks. Among them, Bayesian networks seem to be the most effective in constructing gene networks. A major problem with the Bayesian network approach is the excessive computational time. This problem is due to the interactive feature of the method that requires large search space. Since fitting a model by using the copulas does not require iterations, elicitation of the priors, and complicated calculations of posterior distributions, the need for reference to extensive search spaces can be eliminated leading to manageable computational affords. Bayesian network approach produces a discretely expression of conditional probabilities. Discreteness of the characteristics is not required in the copula approach which involves use of uniform representation of the continuous random variables. Our method is able to overcome the limitation of Bayesian network method for gene-gene interaction, i.e. information loss due to binary transformation.</p> <p>Results</p> <p>We analyzed the gene interactions for two gene data sets (one group is eight histone genes and the other group is 19 genes which include DNA polymerases, DNA helicase, type B cyclin genes, DNA primases, radiation sensitive genes, repaire related genes, replication protein A encoding gene, DNA replication initiation factor, securin gene, nucleosome assembly factor, and a subunit of the cohesin complex) by adopting a measure of directional dependence based on a copula function. We have compared our results with those from other methods in the literature. Although microarray results show a transcriptional co-regulation pattern and do not imply that the gene products are physically interactive, this tight genetic connection may suggest that each gene product has either direct or indirect connections between the other gene products. Indeed, recent comprehensive analysis of a protein interaction map revealed that those histone genes are physically connected with each other, supporting the results obtained by our method.</p> <p>Conclusion</p> <p>The results illustrate that our method can be an alternative to Bayesian networks in modeling gene interactions. One advantage of our approach is that dependence between genes is not assumed to be linear. Another advantage is that our approach can detect directional dependence. We expect that our study may help to design artificial drug candidates, which can block or activate biologically meaningful pathways. Moreover, our copula approach can be extended to investigate the effects of local environments on protein-protein interactions. The copula mutual information approach will help to propose the new variant of ARACNE (Algorithm for the Reconstruction of Accurate Cellular Networks): an algorithm for the reconstruction of gene regulatory networks.</p

Occlusion-Aware Depth Estimation with Adaptive Normal Constraints

We present a new learning-based method for multi-frame depth estimation from a color video, which is a fundamental problem in scene understanding, robot navigation or handheld 3D reconstruction. While recent learning-based methods estimate depth at high accuracy, 3D point clouds exported from their depth maps often fail to preserve important geometric feature (e.g., corners, edges, planes) of man-made scenes. Widely-used pixel-wise depth errors do not specifically penalize inconsistency on these features. These inaccuracies are particularly severe when subsequent depth reconstructions are accumulated in an attempt to scan a full environment with man-made objects with this kind of features. Our depth estimation algorithm therefore introduces a Combined Normal Map (CNM) constraint, which is designed to better preserve high-curvature features and global planar regions. In order to further improve the depth estimation accuracy, we introduce a new occlusion-aware strategy that aggregates initial depth predictions from multiple adjacent views into one final depth map and one occlusion probability map for the current reference view. Our method outperforms the state-of-the-art in terms of depth estimation accuracy, and preserves essential geometric features of man-made indoor scenes much better than other algorithms.Comment: ECCV 202

A single origin of the photosynthetic organelle in different Paulinella lineages

<p>Abstract</p> <p>Background</p> <p>Gaining the ability to photosynthesize was a key event in eukaryotic evolution because algae and plants form the base of the food chain on our planet. The eukaryotic machines of photosynthesis are plastids (e.g., chloroplast in plants) that evolved from cyanobacteria through primary endosymbiosis. Our knowledge of plastid evolution, however, remains limited because the primary endosymbiosis occurred more than a billion years ago. In this context, the thecate "green amoeba" <it>Paulinella chromatophora </it>is remarkable because it very recently (i.e., minimum age of ≈ 60 million years ago) acquired a photosynthetic organelle (termed a "chromatophore"; i.e., plastid) <it>via </it>an independent primary endosymbiosis involving a <it>Prochlorococcus </it>or <it>Synechococcus</it>-like cyanobacterium. All data regarding <it>P. chromatophora </it>stem from a single isolate from Germany (strain M0880/a). Here we brought into culture a novel photosynthetic <it>Paulinella </it>strain (FK01) and generated molecular sequence data from these cells and from four different cell samples, all isolated from freshwater habitats in Japan. Our study had two aims. The first was to compare and contrast cell ultrastructure of the M0880/a and FK01 strains using scanning electron microscopy. The second was to assess the phylogenetic diversity of photosynthetic <it>Paulinella </it>to test the hypothesis they share a vertically inherited plastid that originated in their common ancestor.</p> <p>Results</p> <p>Comparative morphological analyses show that <it>Paulinella </it>FK01 cells are smaller than M0880/a and differ with respect to the number of scales per column. There are more distinctive, multiple fine pores on the external surface of FK01 than in M0880/a. Molecular phylogenetic analyses using multiple gene markers demonstrate these strains are genetically distinct and likely comprise separate species. The well-supported monophyly of the <it>Paulinella chromatophora </it>strains analyzed here using plastid-encoded 16S rRNA suggests strongly that they all share a common photosynthetic ancestor. The strain M0880/a is most closely related to Japanese isolates (Kanazawa-1, -2, and Kaga), whereas FK01 groups closely with a Kawaguchi isolate.</p> <p>Conclusion</p> <p>Our results indicate that <it>Paulinella chromatophora </it>comprises at least two distinct evolutionary lineages and likely encompasses a broader taxonomic diversity than previously thought. The finding of a single plastid origin for both lineages shows these taxa to be valuable models for studying post-endosymbiotic cell and genome evolution.</p

Harmonic Pulse Testing for Well Monitoring: application to a fractured geothermal reservoir

Harmonic Pulse Testing (HPT) has been developed as a type of well testing applicable during ongoing field operations because a pulsed signal is superimposed on background pressure trend. Its purpose is to determine well and formation parameters such as wellbore storage, skin, permeability and boundaries within the investigated volume. Compared to conventional well testing, HPT requires more time to investigate the same reservoir volume. The advantage is that it does not require the interruption of well and reservoir injection/production before and/or during the test because it allows the extraction of an interpretable periodic signal from measured pressure potentially affected by interference. This makes it an ideal monitoring tool. Interpretation is streamlined through diagnostic plots mimicking conventional well test interpretation methods. To this end, analytical solutions in the frequency domain are available. The methodology was applied to monitor stimulation operations performed at an Enhanced Geothermal System (EGS) site in Pohang, Korea. The activities were divided into two steps: first a preliminary sequence of tests, injection/fall‐off and two HPTs, characterized by low injection rates and dedicated to estimate permeability prior to stimulation operations; then stimulation sequence characterized by higher injection rate. During the stimulation operations other HPTs were performed to monitor formation properties behavior. The interpretation of HPT data through the derivative approach implemented in the frequency domain provided reliable results in agreement with the injection test. Moreover, it provided an estimation of hydraulic properties without cessation of stimulation operations, thus confirming the effectiveness of HPT application for monitoring purposes

Primary Biliary Lymphoma Mimicking Cholangiocarcinoma: A Characteristic Feature of Discrepant CT and Direct Cholangiography Findings

Primary non-Hodgkin's lymphoma arising from the bile duct is extremely rare and the reported imaging features do not differ from those of cholangiocarcinoma of the bile duct. We report a case of a patient with extranodal marginal zone B-cell lymphoma of mucosa associated lymphoid tissue (MALT), who presented with obstructive jaundice and describe the distinctive radiologic features that may suggest the correct preoperative diagnosis of primary lymphoma of the bile duct. Primary MALT lymphoma of the extrahepatic bile duct should be considered in the differential diagnosis when there is a mismatch in imaging findings on computed tomography or magnetic resonance imaging and cholangiography

Early Science with the Large Millimeter Telescope: COOL BUDHIES I - a pilot study of molecular and atomic gas at z~0.2

An understanding of the mass build-up in galaxies over time necessitates tracing the evolution of cold gas (molecular and atomic) in galaxies. To that end, we have conducted a pilot study called CO Observations with the LMT of the Blind Ultra-Deep H I Environment Survey (COOL BUDHIES). We have observed 23 galaxies in and around the two clusters Abell 2192 (z = 0.188) and Abell 963 (z = 0.206), where 12 are cluster members and 11 are slightly in the foreground or background, using about 28 total hours on the Redshift Search Receiver (RSR) on the Large Millimeter Telescope (LMT) to measure the $^{12}$CO J = 1 --> 0 emission line and obtain molecular gas masses. These new observations provide a unique opportunity to probe both the molecular and atomic components of galaxies as a function of environment beyond the local Universe. For our sample of 23 galaxies, nine have reliable detections (S/N$\geq$3.6) of the $^{12}$CO line, and another six have marginal detections (2.0 < S/N < 3.6). For the remaining eight targets we can place upper limits on molecular gas masses roughly between $10^9$ and $10^{10} M_\odot$. Comparing our results to other studies of molecular gas, we find that our sample is significantly more abundant in molecular gas overall, when compared to the stellar and the atomic gas component, and our median molecular gas fraction lies about $1\sigma$ above the upper limits of proposed redshift evolution in earlier studies. We discuss possible reasons for this discrepancy, with the most likely conclusion being target selection and Eddington bias.Comment: MNRAS, submitte

Broadly Sampled Multigene Trees of Eukaryotes

Background. Our understanding of the eukaryotic tree of life and the tremendous diversity of microbial eukaryotes is in flux as additional genes and diverse taxa are sampled for molecular analyses. Despite instability in many analyses, there is an increasing trend to classify eukaryotic diversity into six major supergroups: the \u27Amoebozoa\u27, \u27Chromalveolata\u27, \u27Excavata\u27, \u27Opisthokonta\u27, \u27Plantae\u27, and \u27Rhizaria\u27. Previous molecular analyses have often suffered from either a broad taxon sampling using only single-gene data or have used multigene data with a limited sample of taxa. This study has two major aims: (1) to place taxa represented by 72 sequences, 61 of which have not been characterized previously, onto a well-sampled multigene genealogy, and (2) to evaluate the support for the six putative supergroups using two taxon-rich data sets and a variety of phylogenetic approaches. Results. The inferred trees reveal strong support for many clades that also have defining ultrastructural or molecular characters. In contrast, we find limited to no support for most of the putative supergroups as only the \u27Opisthokonta\u27 receive strong support in our analyses. The supergroup \u27Amoebozoa\u27 has only moderate support, whereas the \u27Chromalveolata\u27, \u27Excavata\u27, \u27Plantae\u27, and \u27Rhizaria\u27 receive very limited or no support. Conclusion. Our analytical approach substantiates the power of increased taxon sampling in placing diverse eukaryotic lineages within well-supported clades. At the same time, this study indicates that the six supergroup hypothesis of higher-level eukaryotic classification is likely premature. The use of a taxon-rich data set with 105 lineages, which still includes only a small fraction of the diversity of microbial eukaryotes, fails to resolve deeper phylogenetic relationships and reveals no support for four of the six proposed supergroups. Our analyses provide a point of departure for future taxon- and gene-rich analyses of the eukaryotic tree of life, which will be critical for resolving their phylogenetic interrelationships