Fast Spectral Clustering Using Autoencoders and Landmarks

In this paper, we introduce an algorithm for performing spectral clustering efficiently. Spectral clustering is a powerful clustering algorithm that suffers from high computational complexity, due to eigen decomposition. In this work, we first build the adjacency matrix of the corresponding graph of the dataset. To build this matrix, we only consider a limited number of points, called landmarks, and compute the similarity of all data points with the landmarks. Then, we present a definition of the Laplacian matrix of the graph that enable us to perform eigen decomposition efficiently, using a deep autoencoder. The overall complexity of the algorithm for eigen decomposition is $O(np)$, where $n$ is the number of data points and $p$ is the number of landmarks. At last, we evaluate the performance of the algorithm in different experiments.Comment: 8 Pages- Accepted in 14th International Conference on Image Analysis and Recognitio

An Exploratory Analysis on Drug Target Locality

Abstract—From a network medicine perspective, diseases are caused by perturbations in the dynamics of multiple interacting genes - a disease module. A drug that is a suitable candidate for re-purposing, should affect perturbed disease modules other than the one for which it was designed. In other words, it must act on various disease modules. A systematic analysis of re purposing suitability requires deeper understanding of drug target modularity. In this paper, we present a large-scale analysis of drug-target relationships, evaluating the locality of drug targets in protein-protein interaction networks. We show that the various drugs in each category affect different regions in biological networks, and present modular features. Additionally, multiple targets associated to the same drug appear close in the interactome. Our statistical analysis of the functions of the known drug targets reveals that peripheral functions of disease modules, such as signalling, are common targets for many drugs.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Mining the biomedical literature to predict shared drug targets in drugbank

The current drug development pipelines are characterised by long processes with high attrition rates and elevated costs. More than 80% of new compounds fail in the later stages of testing due to severe side-effects caused by unknown biomolecular targets of the compounds. In this work, we present a measure that can predict shared targets for drugs in DrugBank through large scale analysis of the biomedical literature. We show that using MeSH ontology terms can accurately describe the drugs and that appropriate use of the MeSH ontological structure can determine pairwise drug similarity.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Mining the biomedical literature to predict shared drug targets in drugbank

The current drug development pipelines are characterised by long processes with high attrition rates and elevated costs. More than 80% of new compounds fail in the later stages of testing due to severe side-effects caused by unknown biomolecular targets of the compounds. In this work, we present a measure that can predict shared targets for drugs in DrugBank through large scale analysis of the biomedical literature. We show that using MeSH ontology terms can accurately describe the drugs and that appropriate use of the MeSH ontological structure can determine pairwise drug similarity.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Combining Interactomes from Multiple Organisms: a Case Study on Human-Mouse

The amount and quality of available data on different organisms varies greatly. While model organisms benefit from extensive experimental studies, there is often a lack of detailed experimental data for more specific organisms. Additionally, even among model organisms there are noticeable differences in the amount and type of data available, due to the different suitability of experiments in different organisms. The combination of interactomes for closely related species, represents a viable tool to increase the amount of protein- protein interaction data for a given organism. The Human-Mouse case of study is particularly relevant, as many experiments cannot be carried out on humans. This paper describes a general method to construct a combined interactome from different organisms.CONACYT – Consejo Nacional de Ciencia y TecnologíaPROCIENCI

Updated Meta-Analysis of Randomized Trials Comparing Safety and Efficacy of Intraoperative Defibrillation Testing with No Defibrillation Testing On Implantable Cardioverter-Defibrillator Implantation

Introduction: There is an ongoing debate regarding the need to conduct intraoperative defibrillation testing (DFT) at the time of implantable cardioverter-defibrillator (ICD) implantation. To provide sufficiently strong evidence for the feasibility of omitting intraoperative DFT in clinical practice, we conducted a meta-analysis of randomized controlled trials (RCT) comparing patients with DFT and no-DFT.Methods: We systematically searched Medline (via PubMed), ClinicalTrial.gov, the Cochrane Central Register of Controlled Trials, and Embase for studies evaluating DFT vs. no-DFT on ICD implantation with regard to total mortality and arrhythmic death, efficacy of first and any appropriate shock in interrupting ventricular tachycardia (VT)/ventricular fibrillation (VF), and procedural adverse events. Effect estimates [risk ratio (RR) with 95% confidence intervals (CI)] were pooled using the random-effects model.Results: Our meta-analysis included 4 RCTs comprising 3770 patients (1896 with DFT and 1874 without DFT). Total mortality (RR = 1.00, 95% CI 0.86–1.17; P = 0.98) and arrhythmic death (RR = 1.60, 95% CI 0.46-5.59: P = 0.46) were not statistically different. Both first (RR = 0.94, 95% CI 0.89–0.98; P = 0.004) and any appropriate ICD shock (RR = 0.97, 95% CI 0.95–1.00; P = 0.02) significantly increased the rate of VT/VF interruption in the group with no-DFT in comparison with DFT. Finally, the incidence of adverse events was lower in no-DFT patients (RR = 1.23; 95% CI 1.00–1.51; P = 0.05).Conclusions: The practice of DFT (as opposed to no-DFT) did not yield benefits in mortality or the overall rate of conversion of VT/VT. Moreover, a slightly higher incidence of perioperative adverse events was observed in the DFT group

Fungal cell wall degrading enzymes and plant inhibitors: role during plant infection and strategies to increase plant resistance

During the infection process pathogens produce high amounts of cell wall-degrading enzymes (CWDE) such as endo-xylanases and polygalacturonases (PGs), in order to overcome the barrier constituted by the plant cell wall and obtain nutrients. The first class of enzymes hydrolyzes xylan, a polysaccharide particularly abundant in monocot plants, and some of them have been shown to cause necrosis and hypersensitive response (HR) in the host tissue. The PGs are secreted by pathogenic microorganisms at the early stage of the infection process and are involved in the degradation of the pectin polymer. Fungal PGs and xylanases have been shown to play an important role during pathogenesis of some fungal pathogens, but little is known about their contribution to the virulence of the fungal pathogen Fusarium graminearum, the causal agent of the Fusarium Head Blight disease. Therefore we focused our attention on the F. graminearum xyr1 and pg1 genes (encoding the major regulator of xylanase genes expression and the main PG isoform of the fungus, respectively) by producing single gene disruption mutants (∆xyr and ∆pg). Targeted disruption of the pg1 gene produced a mutant with a PG activity nearly abolished and a reduced virulence on soybean but not on wheat spikes; besides, the ∆xyr mutant, although dramatically impaired in xylanase activity, showed a virulence comparable with wild type on both soybean and wheat. In order to establish a possible synergistic effect between the F. graminearum xylanase and PG activities, a ΔΔxyr/pg double mutant was produced by transforming protoplasts of a ∆pg mutant strain. As expected, when grown on xylan and pectin as carbon sources, the xylanase and PG activities of the double mutant strains were dramatically reduced compared to the wild type strain, while the growth of the double mutant was affected only on xylan containing medium. Infection experiments on soybean seedlings and wheat spikes showed that the virulence of the double mutant strains was significantly reduced compared to the single mutants. The synergistic effect of PG and xylanase activities was confirmed incubating the F. graminearum PG1 and two main purified fungal xylanases in presence of wheat cell walls. Since one of these xylanases (FGSG_03624) has been previously shown to cause HR in wheat tissues, we also evaluated the ability of this xylanase to induce defence responses in Arabidopsis. Exogenous treatments with this protein induced the expression of PDF1.2 defense gene, marker of the jasmonate/ethylene pathways. Treatment of xylanase leaves reduced symptoms of the bacterium Pseudomonas syringae pv. maculicola but not those of the fungus Botrytis cinerea. A site-directed mutagenesis of the FGSG_03624 catalytic site abolished the xylanase activity. This mutagenized protein was transiently expressed in tobacco leaves and also constitutively expressed in Arabidopsis plants. Transformed tobacco and Arabidopsis plants were as susceptible as the untransformed plants to B. cinerea infections. Differently from what observed with exogenous treatments, transgenic Arabidopsis plants were not more resistance to P. syringae infection. As a defense mechanism to counteract pathogens infection, plants have evolved specific inhibitors, usually localized in the plant cell wall, able to reduce or completely block the fungal CWDE. A Triticum aestivum family of xylanase inhibitor proteins (TAXI) have been shown to inhibit the B. cinerea Xyn11A xylanase, a well-known virulence factor of this fungus. TAXI encoding genes were expressed in tobacco leaves and Arabidopsis plants and these plants were infected with B. cinerea. While tobacco leaves transiently expressing TAXIs showed increased resistance against the fungus compared to control leaves, transgenic Arabidopsis plants resulted as susceptible as the untransformed plants

Progressive promoter element combinations classify conserved orthogonal plant circadian gene expression modules

We aimed to test the proposal that progressive combinations of multiple promoter elements acting in concert may be responsible for the full range of phases observed in plant circadian output genes. In order to allow reliable selection of informative phase groupings of genes for our purpose, intrinsic cyclic patterns of expression were identified using a novel, non-biased method for the identification of circadian genes. Our non-biased approach identified two dominant, inherent orthogonal circadian trends underlying publicly available microarray data from plants maintained under constant conditions. Furthermore, these trends were highly conserved across several plant species. Four phase-specific modules of circadian genes were generated by projection onto these trends and, in order to identify potential combinatorial promoter elements that might classify genes into these groups, we used a Random Forest pipeline which merged data from multiple decision trees to look for the presence of element combinations. We identified a number of regulatory motifs which aggregated into coherent clusters capable of predicting the inclusion of genes within each phase module with very high fidelity and these motif combinations changed in a consistent, progressive manner from one phase module group to the next, providing strong support for our hypothesis