A visual analytics approach for understanding biclustering results from microarray data

Abstract Background Microarray analysis is an important area of bioinformatics. In the last few years, biclustering has become one of the most popular methods for classifying data from microarrays. Although biclustering can be used in any kind of classification problem, nowadays it is mostly used for microarray data classification. A large number of biclustering algorithms have been developed over the years, however little effort has been devoted to the representation of the results. Results We present an interactive framework that helps to infer differences or similarities between biclustering results, to unravel trends and to highlight robust groupings of genes and conditions. These linked representations of biclusters can complement biological analysis and reduce the time spent by specialists on interpreting the results. Within the framework, besides other standard representations, a visualization technique is presented which is based on a force-directed graph where biclusters are represented as flexible overlapped groups of genes and conditions. This microarray analysis framework (BicOverlapper), is available at http://vis.usal.es/bicoverlapper Conclusion The main visualization technique, tested with different biclustering results on a real dataset, allows researchers to extract interesting features of the biclustering results, especially the highlighting of overlapping zones that usually represent robust groups of genes and/or conditions. The visual analytics methodology will permit biology experts to study biclustering results without inspecting an overwhelming number of biclusters individually.</p

Quasiclassical trajectory calculations of the thermal rate coefficient for the oxygen atom + hydroxyl .fwdarw. oxygen + hydrogen atom reaction on realistic double many-body expansion potential energy surfaces for ground-state hydroperoxy

Quasi-classical trajectory calculations of the thermal rate coefficient for the title reaction have been carried out over the temperature range 250 5 T 5 2500 K by using two recently reported DMBE potential energy surfaces for the ground state of the hydroperoxyl radical. The results are compared with each other and with experiment. The agreement is god. Our results support previous theoretical calculations by Miller on the Melius-Blint potential energy surface in that nonstatistical ‘recrossing” effects are very important. For the DMBE I1 (DMBE 111) potential energy surface, these nonstatistical corrections are found to increase from a factor of about 1.2 (1.4) at 250 K to about 2.1 (2.5) at 2500 K. However, they are considerably smaller than the nonstatistical corrections reported by Miller (factors of about 2.2 and 3.3 at the above temperatures). Although due, of course, to topographical differences between the DMBE and Melius-Blint potential energy surfaces, such discrepancy stems also from the different definitions used for H02* complex in the simple chemical model 0 + OH e H02* -+ 0 2 + H

A realistic hydroperoxo(~X2A") potential energy surface from the double many-body expansion method

A double many-body expansion potential energy surface reported previously for H02(R2A”) and referred to here as DMBE I is modified to produce thermal rate coefficients for the reaction 0 + OH - O2 + H in good agreement with experiment. This new potential energy surface will be referred to as DMBE 11. By the further imposition that the potential function should reproduce the experimental spectroscopic force field data for the hydroperoxyl radical, another potential energy surface has been obtained, DMBE 111. Both of these improved DMBE I1 and DMBE 111 potential energy surfaces preserve the functional form used previously for DMBE I except for the long-range 0. -.OH electrostatic interaction, which is defined in the spirit of a more satisfactory adiabatic theory

Recalibration of a single-valued double many-body expansion potential energy surface for ground-state hydroperoxy and dynamics calculations for the oxygen atom + hydroxyl .fwdarw. oxygen + hydrogen atom reaction

We report a new single-valued potential energy surface for the ground state of H02 from the double many-body expansion (DMBE) method. This new surface conforms with the three-body energy of recent ab initio CAS SCF/CCI calculations semiempirically corrected by the DMBE-SEC method and reproduces the most accurate estimates of the experimental dissociation energy, equilibrium geometry, and quadratic force constants for the hydroperoxyl radical. Using this new H02 (DMBE IV) potential energy function, exploratory dynamics calculations of the 0 + OH - O2 + PI reaction have also been carried out by the quasiclassical trajectory method. Thermal rate coefficients are reported for T = 250, 1250, and 2250 K that are shown to be in good agreement with the best reported measurement

A novel role for lncRNAs in cell cycle control during stress adaptation

Eukaryotic cells have developed sophisticated systems to constantly monitor changes in the extracellular environment and to orchestrate a proper cellular response. To maximize survival, cells delay cell-cycle progression in response to environmental changes. In response to extracellular insults, stress-activated protein kinases (SAPKs) modulate cell-cycle progression and gene expression. In yeast, osmostress induces activation of the p38-related SAPK Hog1, which plays a key role in reprogramming gene expression upon osmostress. Genomic analysis has revealed the existence of a large number of long non-coding RNAs (lncRNAs) with different functions in a variety of organisms, including yeast. Upon osmostress, hundreds of lncRNAs are induced by the SAPK p38/Hog1. One gene that expresses Hog1-dependent lncRNA in an antisense orientation is the CDC28 gene, which encodes CDK1 kinase that controls the cell cycle in yeast. Cdc28 lncRNA mediates the induction of CDC28 expression and this increase in the level of Cdc28 results in more efficient re-entry of the cells into the cell cycle after stress. Thus, the control of lncRNA expression as a new mechanism for the regulation of cell-cycle progression opens new avenues to understand how stress adaptation can be accomplished in response to changing environments.The laboratory of FP and EN is supported by grants from the Spanish Government (BFU2012-33503 and FEDER to FP, BFU2011-26722 to EN), an ERC Advanced Grant Number 294294 from the EU seventh framework program (SYNCOM) and the Fundación Marcelino Botín (FMB) to FP. FP and EN are recipients of an ICREA Acadèmia (Generalitat de Catalunya). The authors declare no competing financial interes