Supplementary Website Research Articles

Book Review of Disciplinary Literacy and Gamified Learning in Elementary Classrooms: Questing Through Time and Space

Disciplinary Literacy and Gamified Learning in Elementary Classrooms: Questing Through Time and Space is a handbook for launching quest-based learning activities in the elementary classroom. The work collates resources that support content area learning and multi-modal literacy. Students are centered in the learning activities as creators and players, thus making learning an active and engaging experience. Each unit articulates the learning standards, lesson objectives, and evaluation methods, effectively serving as a paradigm of best practices in teaching. This resource is complemented by an online resource hub for each unit of study, which includes a supplementary website, videos, and printable lesson plans.

Supercapacitor auto analyser: An automated data analysis software for supercapacitor characterization

High-performance supercapacitors (SCs) with high power, energy, and long-life cycles, are essential for innovating wearable and portable electronics as extensively reported in literature. The Web of Science shows more than 23,000 papers published since 2018 with the topic ‘Supercapacitor’, number that keep growing, from 732 papers per year in 2012 to an average of 4651 papers per year since 2018. However, the establishment of performance metrics on the reported values should be achieved to reduce inconsistencies in their real performances. For that reason, we developed the Supercapacitors Auto Analyser (SCAA) program for SCs data analysis to support the community to establish performance metrics for SC devices, with standard terms, equations, and units. The SCAA generates important graphs with the SCs key properties and electrochemical performance such as capacitance, energy, power, coulombic efficiency (CE), equivalent series resistance (ESR), drop potential (Vdrop), cycling stability, and time constant. These results are calculated from common data generated by potentiostat on SCs characterization such as cyclic voltammetry (CV), galvanostatic charge–discharge (GCD), and electrochemical impedance spectroscopy (EIS). With appropriate inputs, the SCAA provides as many as 50 graphs with accurate normalizations by mass, area, or volume in a few minutes. This automation of data analysis is packed in a software made available to the community in the supplementary materials and website www.scaasoftware.com.

The Development of EFL Lexical Competence through the Use of Computer Assisted Language Learning in Qassim University

The current study aimed to investigate the effectiveness of Computer Assisted Language Learning (CALL) on vocabulary learning and its perceived benefits and challenges among Saudi learners of English as a foreign language (EFL). 64 homogeneous male and female participants were selected and assigned to experimental and control groups with equal numbers. The experimental group was taught vocabulary using the Blackboard Collaborate Ultra and a supplementary online website, while the control group was taught using the traditional face-to-face (FTF) approach. The treatment lasted for 8 weeks. Both groups of learners took pre- and post-tests for vocabulary achievement. Based on the descriptive statistics, independents samples t-test, and paired samples t-test, the experimental group outperformed the control group. However, there was no significant difference in the vocabulary test performance between male and female learners allocated in the experimental group. The follow-up interview revealed several benefits of this approach for their English vocabulary development though a few students pointed at some challenges that hinder them from making a good use of technology in enhancing their vocabulary.

Dynamical Properties and Conceptual Interpretation of Latent Change Score Models.

Latent Change Score models (LCS) are a popular tool for the study of dynamics in longitudinal research. They represent processes in which the short-term dynamics have direct and indirect consequences on the long-term behavior of the system. However, this dual interpretation of the model parameters is usually overlooked in the literature, and researchers often find it difficult to see the connection between parameters and specific patterns of change. The goal of this paper is to provide a comprehensive examination of the meaning and interpretation of the parameters in LCS models. Importantly, we focus on their relation to the shape of the trajectories and explain how different specifications of the LCS model involve particular assumptions about the mechanisms of change. On a supplementary website, we present an interactive Shiny App that allows users to explore different sets of parameter values and examine their effects on the predicted trajectories. We also include fully explained code to estimate some of the most relevant specifications of the LCS model with the R-packages lavaan and OpenMx.

OP89 Conference Abstract Searching In National Institute For Health And Care Excellence Health Technology Appraisals

IntroductionThe National Institute for Health and Care Excellence (NICE) guidelines manual recommend that MEDLINE, Embase and Cochrane Central Register of Controlled Trials should be prioritized for searching for reviews of the effectiveness of pharmacological interventions. Additionally, searching trial registries and conference abstracts are recommended to identify ongoing or unpublished research. However, the approaches to searching conference abstracts have not been previously studied. The aim is to analyze searches of conference abstracts reported in NICE Technology Appraisal (TA) company submissions for cancer interventions from 2013 until September 2018.MethodsThe company submissions were searched and obtained via the NICE technology appraisal guidance website. The sources used to find conference abstracts were identified from the company clinical effectiveness review search methods and appendices. Conference abstract searching in both database and website sources were compared.ResultsOf all 394 TAs, 124 (31 percent) were cancer TAs. Between 2013 and 2018, 91 TAs were completed or updated, which covered 18 cancer categories and 52 different named technologies. Technologies to treat non-small-cell lung cancer was the most frequently appraised in the last five years. Nivolumab was the most frequently appraised technology. Searches for conference abstracts were reported in 70 (77 percent) out of 91 company submissions. Supplementary searching was reported in 59 (84 percent), compared with 11 (16 percent) searching either/both Embase and the Web of Science Conference Proceeding Index (WoS-CPCI). A total of 54 supplementary website sources were searched which ranged from one to 11 per TA (average four sources). The American Society of Clinical Oncology (ASCO) and the European Society of Medical Oncology were the most frequently searched sources.ConclusionsWhilst the WoS-CPCI has better coverage of cancer conference abstracts than Embase, searching databases alone are inadequate. Supplementary conference websites should be searched for reasons such as access to the most recent abstracts and incomplete indexing of titles within databases. A wide range of cancer specific sites exists although the impact of broad (e.g. ASCO) versus condition specific sites is unclear.

Ambient Media: Japanese Atmospheres of Self by Paul Roquet

Reviewed by: Ambient Media: Japanese Atmospheres of Self by Paul Roquet Fabian Schäfer (bio) Ambient Media: Japanese Atmospheres of Self. By Paul Roquet. University of Minnesota Press, Minneapolis, 2016. 245pages. $94.50, cloth; $27.50, paper. Writing about a matter such as “ambient media” could be considered a challenge. Not because of the subject per se, but because of the fact that writing about the state of ambience—a very subjective and affective experience of visual and/or auditory media, such as video, music, or literature—necessarily requires us to “squeeze” the spatio-ephemeral and tangible experience of ambience into the two-dimensional and “cold” textual form. Not very surprisingly, while reading Paul Roquet’s book, I was often reminded of a famous quote by Victor Hugo: “music expresses that which cannot be said and on which it is impossible to be silent.” This aptly describes not only my own reading experience but also the potential limits of writing about nontextual, sometimes not even visual, media—about something that functions best not when one is contemplatively looking at it but when one experiences and senses it as something that surrounds or even absorbs the individual. While Hugo’s words refer particularly to music, I am sure Roquet must have felt the same frustration from time to time, given that his book includes auto ethnographical descriptions of his own subjective exposure to ambient media. Nevertheless, readers of Roquet’s book should count themselves lucky that the author apparently adhered to the second part of Hugo’s observation and produced this well-researched and wonderfully written book about the yet [End Page 121] neglected subject of ambient media in Japan, thereby masterfully conquering the paradox described by Hugo. On that note, it might be important to remark that, unlike Victor Hugo in his times, we are nowadays living in the age of a ubiquitous internet connection. I was distracted from reading the book on numerous occasions by watching clips of video installations and listening to the tunes discussed in the book, at one point even reaching a state which might be described as “ambient multimedia reading.” This significantly slowed the process of reading the book and writing this review but was definitely worthwhile. These distractions aside, one wishes the author (or the publisher?) had dared to be more experimental by advancing into the possibilities of digital publishing, or at least into the various possibilities available for integrating the nontextual works discussed in the book into the printed publication in some other way (such as via a supplementary website). One might speculate, however, that the traditional format might be based on the restrictions of what could be called the “academico-commercial complex” among young scholars—driven by their need to publish their dissertations in the traditional medium of the book to get hired or tenured—combined with the growing commercialization of the scholarly book. Despite these apparently unavoidable restrictions, Roquet’s book takes the reader on a fantastic journey through and across the different forms of what the author calls “ambient media”: ambient music, ambient video/film, and ambient literature. It does so by looking into the subject from at least three different angles. Roquet discusses the specific materiality of each of the different media technologies and looks into their creatively artistic or blatantly commercial content. He also does not neglect discussion of the “effect” of ambient media on what media studies has for a long time expressed through concepts such as “recipient” and “audience.” Accordingly, the book discusses not only different media technologies, their histories, and the kind of environment (“atmosphere”) they create, but also how these media technologies, their contents, and the readers and viewers interlock in a media environment, something Roquet describes as “ambient subjectivation” (p. 3). Put differently, the book successfully manages to be simultaneously a history and an epistemology and ontology of ambient media. Thereby, it productively contributes to the fields of media history and media philosophy/theory alike. Roquet—quoting Nikolas Rose—describes the aim of creating as well as being receptive to this state of ambient subjectivation as that of “personal mood regulation,” namely, the effect of ambient media aligning “political, social, and institutional goals...

Current Directions in Ecomusicology: Music, Culture, Nature eds. by Aaron S. Allen and Kevin Dawe

Current Directions in Music, Culture, Nature. Edited by Aaron S. Allen and Kevin Dawe. (Routledge Research in Music, no. 13.) New York: Routledge, 2016. [vii, 314 p. ISBN 9781138804586 (hardback), $148; ISBN 9781138062498 (paperback), $49.95; ISBN 9781315752938 (e-book), varies.] Music examples, photographs, glossary, index, supplementary website. What is ecomusicology? In a colloquy dedicated to the subject in the Journal of the American MusicoLogical Society, Aaron S. Allen began to answer this question, admitting he was reluctant to define an emerging subfield as yet lacking in consensus, but we must start somewhere (Aaron S. Allen, Ecomusicology: Ecocriticism and Musicology, Journal of the American Musicologicat Society 64, no. 2 [Summer 2011]: 392). In the years since, scholarly and public interest in intersections between music, place, and the environment has blossomed, with vibrant ecomusicology groups in both the American Musicological Society and the Society for Ethnomusicology and a series of successful interdisciplinary Ecomusicologies conferences. From the fruits of these labors, Allen and Kevin Dawe have collected nineteen essays in the volume Current Directions in providing a much clearer answer to the question. In their introductory essay, Ecomusicologies, Allen and Dawe maintain that there is no one ecomusicology but many ecomusicologies constituting a dynamic field (p. 1), and the essays that follow certainly support this assertion. book is divided into four directions: ecological, fieldwork, critical, and textual. Allen and Dawe provide an additional introduction to each of these major sections, summarizing but also connecting the essays to each other and to a wider literature. These divisions are relatively arbitrary; all of the essays involve theoretical criticism in some way, and all are concerned with interpreting specific musics or sounds as texts, for example. Yet the four directions impose additional framing mechanisms that give the volume cohesion, moving from a focus on ecological sciences, to ethnography, to social theory, and finally to exegesis. terms in the book's subtitle--music, culture, and nature--unite all of the chapters, yet they also engage in various degrees with binaries of music/sound, culture/ society, and nature/environment. Often, authors advocate a blurring or complete breakdown of these binaries. Jeff Todd Titon, in his chapter Why Thoreau?, argues for an ecomusicological re-framing of the Walden author in part because of how Thoreau described natural sounds in explicitly musical language. For Thoreau, place is experienced as an embodied encounter with sound. musicalization of natural sounds is the subject of multiple essays, including but not limited to W. Alice Boyle and Ellen Waterman's The Ecology of Musical Performance: Towards a Robust Methodology, and Helena Simonett's Of Human and Non-Human Birds: Indigenous Music Making in Sentient Ecology in Northwestern Simonett's essay also contests the nature/ environment binary as she applies the concept of sentient ecology, which extends the concept of personhood to animals, and ultimately, to all life in an ecosystem (p. 99), to her analysis of indigenous Yoreme musicians in Mexico. This false binary is explored even further in the essay by Margaret Q. Guyette and Jennifer C. Post, Ecomusicology, Ethnomusicology, and Soundscape Ecology: Scientific and Musical Responses to Sound Study. Here the authors argue that traditional notions of nature as a space untouched by humanity, and the environment as merely built or constructed, are problematic for anthropocentric scholarship because they limit or blind researchers from seeing how humans and the natural world are inextricable from one another. In studying the acoustic properties of landscape, Guyette and Post encourage ecologists to be aware of human noise as integral, rather than detrimental, to the soundscape, and implore ethnomusicologists to focus on non-human sound as integral to the performance practices of musical cultures. …

Learning distributed discrete Bayesian Network Classifiers under MapReduce with Apache Spark

The challenge of scalability has always been a focus on Machine Learning research, where improved algorithms and new techniques are proposed in a constant basis to deal with more complex problems. With the advent of Big Data, this challenge has been intensified, in which new large scale datasets overwhelm the majority of available techniques. The community has resorted to Cloud Computing and distributed programming paradigms as the most immediate solution where Apache Spark has proven to be the most promising framework. In this paper we focus on the problem of supervised classification, exploring the family of the so called Bayesian Network Classifiers by studying their adaptability to the MapReduce and Apache Spark frameworks. We will analyse a range of algorithms and propose distributed versions of them. Our approach is based on a general framework for learning this probabilistic models from large scale and high dimensional data, the latter being a problem with less support in the literature. We also present an extensive experimental evaluation of our proposal over a wide set of problems and different elastic configurations of a computing cluster to show the full extent of the scalability properties of our framework. Additional material and the software to reproduce our experiments can be found on the supplementary website http://simd.albacete.org/supplements/distributed_bncs.html.

Pathways on demand: automated reconstruction of human signaling networks.

Signaling pathways are a cornerstone of systems biology. Several databases store high-quality representations of these pathways that are amenable for automated analyses. Despite painstaking and manual curation, these databases remain incomplete. We present PATHLINKER, a new computational method to reconstruct the interactions in a signaling pathway of interest. PATHLINKER efficiently computes multiple short paths from the receptors to transcriptional regulators (TRs) in a pathway within a background protein interaction network. We use PATHLINKER to accurately reconstruct a comprehensive set of signaling pathways from the NetPath and KEGG databases. We show that PATHLINKER has higher precision and recall than several state-of-the-art algorithms, while also ensuring that the resulting network connects receptor proteins to TRs. PATHLINKER’s reconstruction of the Wnt pathway identified CFTR, an ABC class chloride ion channel transporter, as a novel intermediary that facilitates the signaling of Ryk to Dab2, which are known components of Wnt/β-catenin signaling. In HEK293 cells, we show that the Ryk–CFTR–Dab2 path is a novel amplifier of β-catenin signaling specifically in response to Wnt 1, 2, 3, and 3a of the 11 Wnts tested. PATHLINKER captures the structure of signaling pathways as represented in pathway databases better than existing methods. PATHLINKER’s success in reconstructing pathways from NetPath and KEGG databases point to its applicability for complementing manual curation of these databases. PATHLINKER may serve as a promising approach for prioritizing proteins and interactions for experimental study, as illustrated by its discovery of a novel pathway in Wnt/β-catenin signaling. Our supplementary website at http://bioinformatics.cs.vt.edu/~murali/supplements/2016-sys-bio-applications-pathlinker/ provides links to the PATHLINKER software, input datasets, PATHLINKER reconstructions of NetPath pathways, and links to interactive visualizations of these reconstructions on GraphSpace.

Discretization of Expression Quantitative Trait Loci in Association Analysis Between Genotypes and Expression Data<sup>§</sup>

Expression quantitative trait loci are used as a tool to identify genetic causes of natural variation in gene expression. Only in a few cases the expression of a gene is controlled by a variant on a single genetic marker. There is a plethora of different complexity levels of interaction effects within markers, within genes and between marker and genes. This complexity challenges biostatisticians and bioinformatitians every day and makes findings difficult to appear. As a way to simplify analysis and better control confounders, we tried a new approach for association analysis between genotypes and expression data. We pursued to understand whether discretization of expression data can be useful in genome-transcriptome association analyses. By discretizing the dependent variable, algorithms for learning classifiers from data as well as performing block selection were used to help understanding the relationship between the expression of a gene and genetic markers. We present the results of using this approach to detect new possible causes of expression variation of DRB5, a gene playing an important role within the immune system. Together with expression of gene DRB5 obtained from the classical microarray technology, we have also measured DRB5 expression by using the more recent next-generation sequencing technology. A supplementary website including a link to the software with the method implemented can be found at http: //bios.ugr.es/DRB5. Keywords: eQTL, gene expression microarray, machine learning, RNA-seq, SNP.

ValWorkBench: An open source Java library for cluster validation, with applications to microarray data analysis

The prediction of the number of clusters in a dataset, in particular microarrays, is a fundamental task in biological data analysis, usually performed via validation measures. Unfortunately, it has received very little attention and in fact there is a growing need for software tools/libraries dedicated to it. Here we present ValWorkBench, a software library consisting of eleven well known validation measures, together with novel heuristic approximations for some of them. The main objective of this paper is to provide the interested researcher with the full software documentation of an open source cluster validation platform having the main features of being easily extendible in a homogeneous way and of offering software components that can be readily re-used. Consequently, the focus of the presentation is on the architecture of the library, since it provides an essential map that can be used to access the full software documentation, which is available at the supplementary material website [1]. The mentioned main features of ValWorkBench are also discussed and exemplified, with emphasis on software abstraction design and re-usability. A comparison with existing cluster validation software libraries, mainly in terms of the mentioned features, is also offered. It suggests that ValWorkBench is a much needed contribution to the microarray software development/algorithm engineering community. For completeness, it is important to mention that previous accurate algorithmic experimental analysis of the relative merits of each of the implemented measures [19,23,25], carried out specifically on microarray data, gives useful insights on the effectiveness of ValWorkBench for cluster validation to researchers in the microarray community interested in its use for the mentioned task.

Computational approaches for discovery of common immunomodulators in fungal infections: towards broad-spectrum immunotherapeutic interventions

BackgroundFungi are the second most abundant type of human pathogens. Invasive fungal pathogens are leading causes of life-threatening infections in clinical settings. Toxicity to the host and drug-resistance are two major deleterious issues associated with existing antifungal agents. Increasing a host’s tolerance and/or immunity to fungal pathogens has potential to alleviate these problems. A host’s tolerance may be improved by modulating the immune system such that it responds more rapidly and robustly in all facets, ranging from the recognition of pathogens to their clearance from the host. An understanding of biological processes and genes that are perturbed during attempted fungal exposure, colonization, and/or invasion will help guide the identification of endogenous immunomodulators and/or small molecules that activate host-immune responses such as specialized adjuvants.ResultsIn this study, we present computational techniques and approaches using publicly available transcriptional data sets, to predict immunomodulators that may act against multiple fungal pathogens. Our study analyzed data sets derived from host cells exposed to five fungal pathogens, namely, Alternaria alternata, Aspergillus fumigatus, Candida albicans, Pneumocystis jirovecii, and Stachybotrys chartarum. We observed statistically significant associations between host responses to A. fumigatus and C. albicans. Our analysis identified biological processes that were consistently perturbed by these two pathogens. These processes contained both immune response-inducing genes such as MALT1, SERPINE1, ICAM1, and IL8, and immune response-repressing genes such as DUSP8, DUSP6, and SPRED2. We hypothesize that these genes belong to a pool of common immunomodulators that can potentially be activated or suppressed (agonized or antagonized) in order to render the host more tolerant to infections caused by A. fumigatus and C. albicans.ConclusionsOur computational approaches and methodologies described here can now be applied to newly generated or expanded data sets for further elucidation of additional drug targets. Moreover, identified immunomodulators may be used to generate experimentally testable hypotheses that could help in the discovery of broad-spectrum immunotherapeutic interventions. All of our results are available at the following supplementary website: http://bioinformatics.cs.vt.edu/~murali/supplements/2013-kidane-bmc

The landscape of host transcriptional response programs commonly perturbed by bacterial pathogens: towards host-oriented broad-spectrum drug targets.

BackgroundThe emergence of drug-resistant pathogen strains and new infectious agents pose major challenges to public health. A promising approach to combat these problems is to target the host’s genes or proteins, especially to discover targets that are effective against multiple pathogens, i.e., host-oriented broad-spectrum (HOBS) drug targets. An important first step in the discovery of such drug targets is the identification of host responses that are commonly perturbed by multiple pathogens.ResultsIn this paper, we present a methodology to identify common host responses elicited by multiple pathogens. First, we identified host responses perturbed by each pathogen using a gene set enrichment analysis of publicly available genome-wide transcriptional datasets. Then, we used biclustering to identify groups of host pathways and biological processes that were perturbed only by a subset of the analyzed pathogens. Finally, we tested the enrichment of each bicluster in human genes that are known drug targets, on the basis of which we elicited putative HOBS targets for specific groups of bacterial pathogens. We identified 84 up-regulated and three down-regulated statistically significant biclusters. Each bicluster contained a group of pathogens that commonly dysregulated a group of biological processes. We validated our approach by checking whether these biclusters correspond to known hallmarks of bacterial infection. Indeed, these biclusters contained biological process such as inflammation, activation of dendritic cells, pro- and anti- apoptotic responses and other innate immune responses. Next, we identified biclusters containing pathogens that infected the same tissue. After a literature-based analysis of the drug targets contained in these biclusters, we suggested new uses of the drugs Anakinra, Etanercept, and Infliximab for gastrointestinal pathogens Yersinia enterocolitica, Helicobacter pylori kx2 strain, and enterohemorrhagic Escherichia coli and the drug Simvastatin for hematopoietic pathogen Ehrlichia chaffeensis.ConclusionsUsing a combination of automated analysis of host-response gene expression data and manual study of the literature, we have been able to suggest host-oriented treatments for specific bacterial infections. The analyses and suggestions made in this study may be utilized to generate concrete hypothesis on which gene sets to probe further in the quest for HOBS drug targets for bacterial infections. All our results are available at the following supplementary website: http://bioinformatics.cs.vt.edu/ murali/supplements/2013-kidane-plos-one

Relating drug–protein interaction network with drug side effects

Motivation: Identifying the emergence and underlying mechanisms of drug side effects is a challenging task in the drug development process. This underscores the importance of system–wide approaches for linking different scales of drug actions; namely drug-protein interactions (molecular scale) and side effects (phenotypic scale) toward side effect prediction for uncharacterized drugs.Results: We performed a large-scale analysis to extract correlated sets of targeted proteins and side effects, based on the co-occurrence of drugs in protein-binding profiles and side effect profiles, using sparse canonical correlation analysis. The analysis of 658 drugs with the two profiles for 1368 proteins and 1339 side effects led to the extraction of 80 correlated sets. Enrichment analyses using KEGG and Gene Ontology showed that most of the correlated sets were significantly enriched with proteins that are involved in the same biological pathways, even if their molecular functions are different. This allowed for a biologically relevant interpretation regarding the relationship between drug–targeted proteins and side effects. The extracted side effects can be regarded as possible phenotypic outcomes by drugs targeting the proteins that appear in the same correlated set. The proposed method is expected to be useful for predicting potential side effects of new drug candidate compounds based on their protein-binding profiles.Supplementary information: Datasets and all results are available at http://web.kuicr.kyoto-u.ac.jp/supp/smizutan/target-effect/.Availability: Software is available at the above supplementary website.Contact: yamanishi@bioreg.kyushu-u.ac.jp, or goto@kuicr.kyoto-u.ac.jp

Slim-Filter: an interactive windows-based application for illumina genome analyzer data assessment and manipulation

BackgroundThe emergence of Next Generation Sequencing technologies has made it possible for individual investigators to generate gigabases of sequencing data per week. Effective analysis and manipulation of these data is limited due to large file sizes, so even simple tasks such as data filtration and quality assessment have to be performed in several steps. This requires (potentially problematic) interaction between the investigator and a bioinformatics/computational service provider. Furthermore, such services are often performed using specialized computational facilities.ResultsWe present a Windows-based application, Slim-Filter designed to interactively examine the statistical properties of sequencing reads produced by Illumina Genome Analyzer and to perform a broad spectrum of data manipulation tasks including: filtration of low quality and low complexity reads; filtration of reads containing undesired subsequences (such as parts of adapters and PCR primers used during the sample and sequencing libraries preparation steps); excluding duplicated reads (while keeping each read’s copy number information in a specialized data format); and sorting reads by copy numbers allowing for easy access and manual editing of the resulting files. Slim-Filter is organized as a sequence of windows summarizing the statistical properties of the reads. Each data manipulation step has roll-back abilities, allowing for return to previous steps of the data analysis process. Slim-Filter is written in C++ and is compatible with fasta, fastq, and specialized AS file formats presented in this manuscript. Setup files and a user’s manual are available for download at the supplementary web site ( https://www.bioinfo.uh.edu/Slim_Filter/).ConclusionThe presented Windows-based application has been developed with the goal of providing individual investigators with integrated sequencing reads analysis, curation, and manipulation capabilities.

Surrogate variable analysis using partial least squares (SVA-PLS) in gene expression studies

In a typical gene expression profiling study, our prime objective is to identify the genes that are differentially expressed between the samples from two different tissue types. Commonly, standard analysis of variance (ANOVA)/regression is implemented to identify the relative effects of these genes over the two types of samples from their respective arrays of expression levels. But, this technique becomes fundamentally flawed when there are unaccounted sources of variability in these arrays (latent variables attributable to different biological, environmental or other factors relevant in the context). These factors distort the true picture of differential gene expression between the two tissue types and introduce spurious signals of expression heterogeneity. As a result, many genes which are actually differentially expressed are not detected, whereas many others are falsely identified as positives. Moreover, these distortions can be different for different genes. Thus, it is also not possible to get rid of these variations by simple array normalizations. This both-way error can lead to a serious loss in sensitivity and specificity, thereby causing a severe inefficiency in the underlying multiple testing problem. In this work, we attempt to identify the hidden effects of the underlying latent factors in a gene expression profiling study by partial least squares (PLS) and apply ANCOVA technique with the PLS-identified signatures of these hidden effects as covariates, in order to identify the genes that are truly differentially expressed between the two concerned tissue types. We compare the performance of our method SVA-PLS with standard ANOVA and a relatively recent technique of surrogate variable analysis (SVA), on a wide variety of simulation settings (incorporating different effects of the hidden variable, under situations with varying signal intensities and gene groupings). In all settings, our method yields the highest sensitivity while maintaining relatively reasonable values for the specificity, false discovery rate and false non-discovery rate. Application of our method to gene expression profiling for acute megakaryoblastic leukemia shows that our method detects an additional six genes, that are missed by both the standard ANOVA method as well as SVA, but may be relevant to this disease, as can be seen from mining the existing literature.

Network-based functional enrichment

BackgroundMany methods have been developed to infer and reason about molecular interaction networks. These approaches often yield networks with hundreds or thousands of nodes and up to an order of magnitude more edges. It is often desirable to summarize the biological information in such networks. A very common approach is to use gene function enrichment analysis for this task. A major drawback of this method is that it ignores information about the edges in the network being analyzed, i.e., it treats the network simply as a set of genes. In this paper, we introduce a novel method for functional enrichment that explicitly takes network interactions into account.ResultsOur approach naturally generalizes Fisher’s exact test, a gene set-based technique. Given a function of interest, we compute the subgraph of the network induced by genes annotated to this function. We use the sequence of sizes of the connected components of this sub-network to estimate its connectivity. We estimate the statistical significance of the connectivity empirically by a permutation test. We present three applications of our method: i) determine which functions are enriched in a given network, ii) given a network and an interesting sub-network of genes within that network, determine which functions are enriched in the sub-network, and iii) given two networks, determine the functions for which the connectivity improves when we merge the second network into the first. Through these applications, we show that our approach is a natural alternative to network clustering algorithms.ConclusionsWe presented a novel approach to functional enrichment that takes into account the pairwise relationships among genes annotated by a particular function. Each of the three applications discovers highly relevant functions. We used our methods to study biological data from three different organisms. Our results demonstrate the wide applicability of our methods. Our algorithms are implemented in C++ and are freely available under the GNU General Public License at our supplementary website. Additionally, all our input data and results are available at http://bioinformatics.cs.vt.edu/~murali/supplements/2011-incob-nbe/.

Preface

Preface Sarah Banet-Weiser “Sound Clash: Listening to American Studies” is my first special issue since coming on board as editor of American Quarterly (AQ), and it certainly exceeded all my expectations. As the guest editors, Kara Keeling and Josh Kun, point out in their introduction, the call for an AQ issue devoted to sound studies generated almost ninety submissions—a record for a special issue for this journal by a long stretch. The seventeen essays that were subsequently selected for this volume represent a wide range of scholarly thinking on sound—from nineteenth century noise ordinances to the abstract beauty of sound to the relation of Johnny Cash to Native American soundscape—and signal to the readers of AQ of the critical role of sound in the broad field of American studies. The idea for this special issue came about because both Keeling and Kun are on the AQ Managing Board, and had noticed an increase in submissions that had to do with a broad notion of sound. Music studies have long been fundamental to American studies, but sound—and the sensuous acts of listening and hearing—have just recently been attracting a wide range of scholarly attention. The ability to generate sonic matter—to listen, to hear some sounds and not others—involve practices and forms of labor, as the editors note in their introduction, that engage in and revolve around relations of power. These power relations enforce certain kinds of inclusions and exclusions, involving gender, race, class, sexualities, and other formulations of identity, points of contact, and instances of conflict. Sound is understood in this issue as a cultural form with a material force and the studies here occasion examinations into the sonic and aurality as processes of economic, social, and political negotiations. For instance, the cover image for this issue is from an installation by sound artist Stephen Vitiello, titled “Fear of High Places and Natural Things.” Vitiello works with recording as well as installation, and his method involves the altering of everyday noises into visual installations that consciously forge soundscapes. In his art, Vitiello explores the relationship between sound and motion, using these installations as a means to both sonically generate and aurally record movement. This is a transformation that is intended to shift and change our perception of the quotidian; for us to re-imagine the environment in which we exist when we listen or hear creatively and critically. From a vastly different perspective, the back cover image, a nineteenth century anti-noise ordinance flyer, also asks us to take a moment to listen. The image of George Washington, with a finger to his lips, and the words “Quiet Please” may have been a call for [End Page v] citizens of New York City to dim the chime and clatter of nineteenth century urban life, but the production of, and value placed on, proper forms of sound emission and reception still strikes as important to life as experienced in the twenty-first century. This is what the essays in this volume do as well; they transform our perception of what we have understood to be sound: listening, hearing, and imagining. The work in the following pages of this issue represents important contributions to a uniquely American studies conversation about sound. But while the words on the pages hold political, social, and cultural meaning, when we read, we do not always hear, or are not invited to actively engage aural perception. We wanted to create a volume on sound that also involves the acts of hearing and listening. As part of this issue, then, we have established a supplementary website with audio, film clips, images, and other media files that accompany several of the essays included in the issue. While reading, then, one can also listen and watch a 1920s telephone training film, or listen to “Back Door Man” while reading an analysis of the song. You can access this site at http://www.press.jhu.edu/journals/american_quarterly/special_issue.html and later on our website at www.americanquarterly.org. Putting together this special issue required a great many people to labor together. With the record number of submissions, the guest editors quickly found themselves...

Abstract No. 378: A high-yield tutorial on latest diagnostic and therapeutic paradigms in pulmonary thromboembolic disease with supplementary interactive website

Abstract No. 378: A high-yield tutorial on latest diagnostic and therapeutic paradigms in pulmonary thromboembolic disease with supplementary interactive website

Prediction of a gene regulatory network linked to prostate cancer from gene expression, microRNA and clinical data

Motivation: Cancer is a complex disease, triggered by mutations in multiple genes and pathways. There is a growing interest in the application of systems biology approaches to analyze various types of cancer-related data to understand the overwhelming complexity of changes induced by the disease.Results: We reconstructed a regulatory module network using gene expression, microRNA expression and a clinical parameter, all measured in lymphoblastoid cell lines derived from patients having aggressive or non-aggressive forms of prostate cancer. Our analysis identified several modules enriched in cell cycle-related genes as well as novel functional categories that might be linked to prostate cancer. Almost one-third of the regulators predicted to control the expression levels of the modules are microRNAs. Several of them have already been characterized as causal in various diseases, including cancer. We also predicted novel microRNAs that have never been associated to this type of tumor. Furthermore, the condition-dependent expression of several modules could be linked to the value of a clinical parameter characterizing the aggressiveness of the prostate cancer. Taken together, our results help to shed light on the consequences of aggressive and non-aggressive forms of prostate cancer.Availability: The complete regulatory network is available as an interactive supplementary web site at the following URL: http://bioinformatics.psb.ugent.be/webtools/pronet/Contact: yves.vandepeer@psb.vib-ugent.be