An inferential framework for biological network hypothesis tests

Background Networks are ubiquitous in modern cell biology and physiology. A large literature exists for inferring/proposing biological pathways/networks using statistical or machine learning algorithms. Despite these advances a formal testing procedure for analyzing network-level observations is in need of further development. Comparing the behaviour of a pharmacologically altered pathway to its canonical form is an example of a salient one-sample comparison. Locating which pathways differentiate disease from no-disease phenotype may be recast as a two-sample network inference problem. Results We outline an inferential method for performing one- and two-sample hypothesis tests where the sampling unit is a network and the hypotheses are stated via network model(s). We propose a dissimilarity measure that incorporates nearby neighbour information to contrast one or more networks in a statistical test. We demonstrate and explore the utility of our approach with both simulated and microarray data; random graphs and weighted (partial) correlation networks are used to form network models. Using both a well-known diabetes dataset and an ovarian cancer dataset, the methods outlined here could better elucidate co-regulation changes for one or more pathways between two clinically relevant phenotypes. Conclusions Formal hypothesis tests for gene- or protein-based networks are a logical progression from existing gene-based and gene-set tests for differential expression. Commensurate with the growing appreciation and development of systems biology, the dissimilarity-based testing methods presented here may allow us to improve our understanding of pathways and other complex regulatory systems. The benefit of our method was illustrated under select scenarios

RCMAT: a regularized covariance matrix approach to testing gene sets

<p>Abstract</p> <p>Background</p> <p>Gene sets are widely used to interpret genome-scale data. Analysis techniques that make better use of the correlation structure of microarray data while addressing practical "n<p" concerns could provide a real increase in power. However correlation structure is hard to estimate with typical genomics sample sizes. In this paper we present an extension of a classical multivariate procedure that confronts this challenge by the use of a regularized covariance matrix.</p> <p>Results</p> <p>We evaluated our testing procedure using both simulated data and a widely analyzed diabetes data set. We compared our approach to another popular multivariate test for both sets of data. Our results suggest an increase in power for detecting gene set differences can be obtained using our approach relative to the popular multivariate test with no increase in the false positive rate.</p> <p>Conclusion</p> <p>Our regularized covariance matrix multivariate approach to gene set testing showed promise in both real and simulated data comparisons. Our findings are consistent with the recent literature in gene set methodology.</p

Product Binding Enforces the Genomic Specificity of a Yeast Polycomb Repressive Complex

We characterize the Polycomb system that assembles repressive subtelomeric domains of H3K27 methylation (H3K27me) in the yeast Cryptococcus neoformans. Purification of this PRC2-like protein complex reveals orthologs of animal PRC2 components as well as a chromodomain-containing subunit, Ccc1, which recognizes H3K27me. Whereas removal of either the EZH or EED ortholog eliminates H3K27me, disruption of mark recognition by Ccc1 causes H3K27me to redistribute. Strikingly, the resulting pattern of H3K27me coincides with domains of heterochromatin marked by H3K9me. Indeed, additional removal of the C. neoformans H3K9 methyltransferase Clr4 results in loss of both H3K9me and the redistributed H3K27me marks. These findings indicate that the anchoring of a chromatin-modifying complex to its product suppresses its attraction to a different chromatin type, explaining how enzymes that act on histones, which often harbor product recognition modules, may deposit distinct chromatin domains despite sharing a highly abundant and largely identical substrate—the nucleosome

Product Binding Enforces the Genomic Specificity of a Yeast Polycomb Repressive Complex

We characterize the Polycomb system that assembles repressive subtelomeric domains of H3K27 methylation (H3K27me) in the yeast Cryptococcus neoformans. Purification of this PRC2-like protein complex reveals orthologs of animal PRC2 components as well as a chromodomain-containing subunit, Ccc1, which recognizes H3K27me. Whereas removal of either the EZH or EED ortholog eliminates H3K27me, disruption of mark recognition by Ccc1 causes H3K27me to redistribute. Strikingly, the resulting pattern of H3K27me coincides with domains of heterochromatin marked by H3K9me. Indeed, additional removal of the C. neoformans H3K9 methyltransferase Clr4 results in loss of both H3K9me and the redistributed H3K27me marks. These findings indicate that the anchoring of a chromatin-modifying complex to its product suppresses its attraction to a different chromatin type, explaining how enzymes that act on histones, which often harbor product recognition modules, may deposit distinct chromatin domains despite sharing a highly abundant and largely identical substrate—the nucleosome

Point Mutations in Aβ Result in the Formation of Distinct Polymorphic Aggregates in the Presence of Lipid Bilayers

A hallmark of Alzheimer's disease (AD) is the rearrangement of the β-amyloid (Aβ) peptide to a non-native conformation that promotes the formation of toxic, nanoscale aggregates. Recent studies have pointed to the role of sample preparation in creating polymorphic fibrillar species. One of many potential pathways for Aβ toxicity may be modulation of lipid membrane function on cellular surfaces. There are several mutations clustered around the central hydrophobic core of Aβ near the α-secretase cleavage site (E22G Arctic mutation, E22K Italian mutation, D23N Iowa mutation, and A21G Flemish mutation). These point mutations are associated with hereditary diseases ranging from almost pure cerebral amyloid angiopathy (CAA) to typical Alzheimer's disease pathology with plaques and tangles. We investigated how these point mutations alter Aβ aggregation in the presence of supported lipid membranes comprised of total brain lipid extract. Brain lipid extract bilayers were used as a physiologically relevant model of a neuronal cell surface. Intact lipid bilayers were exposed to predominantly monomeric preparations of Wild Type or different mutant forms of Aβ, and atomic force microscopy was used to monitor aggregate formation and morphology as well as bilayer integrity over a 12 hour period. The goal of this study was to determine how point mutations in Aβ, which alter peptide charge and hydrophobic character, influence interactions between Aβ and the lipid surface. While fibril morphology did not appear to be significantly altered when mutants were prepped similarly and incubated under free solution conditions, aggregation in the lipid membranes resulted in a variety of polymorphic aggregates in a mutation dependent manner. The mutant peptides also had a variable ability to disrupt bilayer integrity

The James Webb Space Telescope Mission

Twenty-six years ago a small committee report, building on earlier studies, expounded a compelling and poetic vision for the future of astronomy, calling for an infrared-optimized space telescope with an aperture of at least $4m$. With the support of their governments in the US, Europe, and Canada, 20,000 people realized that vision as the $6.5m$ James Webb Space Telescope. A generation of astronomers will celebrate their accomplishments for the life of the mission, potentially as long as 20 years, and beyond. This report and the scientific discoveries that follow are extended thank-you notes to the 20,000 team members. The telescope is working perfectly, with much better image quality than expected. In this and accompanying papers, we give a brief history, describe the observatory, outline its objectives and current observing program, and discuss the inventions and people who made it possible. We cite detailed reports on the design and the measured performance on orbit.Comment: Accepted by PASP for the special issue on The James Webb Space Telescope Overview, 29 pages, 4 figure

The Science Performance of JWST as Characterized in Commissioning

This paper characterizes the actual science performance of the James Webb Space Telescope (JWST), as determined from the six month commissioning period. We summarize the performance of the spacecraft, telescope, science instruments, and ground system, with an emphasis on differences from pre-launch expectations. Commissioning has made clear that JWST is fully capable of achieving the discoveries for which it was built. Moreover, almost across the board, the science performance of JWST is better than expected; in most cases, JWST will go deeper faster than expected. The telescope and instrument suite have demonstrated the sensitivity, stability, image quality, and spectral range that are necessary to transform our understanding of the cosmos through observations spanning from near-earth asteroids to the most distant galaxies.Comment: 5th version as accepted to PASP; 31 pages, 18 figures; https://iopscience.iop.org/article/10.1088/1538-3873/acb29

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis