7,669 research outputs found

    MetNetGE: interactive views of biological networks and ontologies

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    Background Linking high-throughput experimental data with biological networks is a key step for understanding complex biological systems. Currently, visualization tools for large metabolic networks often result in a dense web of connections that is difficult to interpret biologically. The MetNetGE application organizes and visualizes biological networks in a meaningful way to improve performance and biological interpretability. Results MetNetGE is an interactive visualization tool based on the Google Earth platform. MetNetGE features novel visualization techniques for pathway and ontology information display. Instead of simply showing hundreds of pathways in a complex graph, MetNetGE gives an overview of the network using the hierarchical pathway ontology using a novel layout, called the Enhanced Radial Space-Filling (ERSF) approach that allows the network to be summarized compactly. The non-tree edges in the pathway or gene ontology, which represent pathways or genes that belong to multiple categories, are linked using orbital connections in a third dimension. Biologists can easily identify highly activated pathways or gene ontology categories by mapping of summary experiment statistics such as coefficient of variation and overrepresentation values onto the visualization. After identifying such pathways, biologists can focus on the corresponding region to explore detailed pathway structure and experimental data in an aligned 3D tiered layout. In this paper, the use of MetNetGE is illustrated with pathway diagrams and data from E. coli and Arabidopsis. Conclusions MetNetGE is a visualization tool that organizes biological networks according to a hierarchical ontology structure. The ERSF technique assigns attributes in 3D space, such as color, height, and transparency, to any ontological structure. For hierarchical data, the novel ERSF layout enables the user to identify pathways or categories that are differentially regulated in particular experiments. MetNetGE also displays complex biological pathway in an aligned 3D tiered layout for exploration

    From Molecules to the Masses : Visual Exploration, Analysis, and Communication of Human Physiology

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    Det overordnede mÄlet med denne avhandlingen er tverrfaglig anvendelse av medisinske illustrasjons- og visualiseringsteknikker for Ä utforske, analysere og formidle aspekter ved fysiologi til publikum med ulik faglig nivÄ og bakgrunn. Fysiologi beskriver de biologiske prosessene som skjer i levende vesener over tid. Vitenskapen om fysiologi er kompleks, men samtidig kritisk for vÄr forstÄelse av hvordan levende organismer fungerer. Fysiologi dekker en stor bredde romlig-temporale skalaer og fordrer behovet for Ä kombinere og bygge bro mellom basalfagene (biologi, fysikk og kjemi) og medisin. De senere Ärene har det vÊrt en eksplosjon av nye, avanserte eksperimentelle metoder for Ä detektere og karakterisere fysiologiske data. Volumet og kompleksiteten til fysiologiske data krever effektive strategier for visualisering for Ä komplementere dagens standard analyser. Hvilke tilnÊrminger som benyttes i visualiseringen mÄ nÞye balanseres og tilpasses formÄlet med bruken av dataene, enten dette er for Ä utforske dataene, analysere disse eller kommunisere og presentere dem. Arbeidet i denne avhandlingen bidrar med ny kunnskap innen teori, empiri, anvendelse og reproduserbarhet av visualiseringsmetoder innen fysiologi. FÞrst i avhandlingen er en rapport som oppsummerer og utforsker dagens kunnskap om muligheter og utfordringer for visualisering innen fysiologi. Motivasjonen for arbeidet er behovet forskere innen visualiseringsfeltet, og forskere i ulike anvendelsesomrÄder, har for en sammensatt oversikt over flerskala visualiseringsoppgaver og teknikker. Ved Ä bruke sÞk over et stort spekter av metodiske tilnÊrminger, er dette den fÞrste rapporten i sitt slag som kartlegger visualiseringsmulighetene innen fysiologi. I rapporten er faglitteraturen oppsummert slik at det skal vÊre enkelt Ä gjÞre oppslag innen ulike tema i rom-og-tid-skalaen, samtidig som litteraturen er delt inn i de tre hÞynivÄ visualiseringsoppgavene data utforsking, analyse og kommunikasjon. Dette danner et enkelt grunnlag for Ä navigere i litteraturen i feltet og slik danner rapporten et godt grunnlag for diskusjon og forskningsmuligheter innen feltet visualisering og fysiologi. Basert pÄ arbeidet med rapporten var det sÊrlig to omrÄder som det er Þnskelig for oss Ä fortsette Ä utforske: (1) utforskende analyse av mangefasetterte fysiologidata for ekspertbrukere, og (2) kommunikasjon av data til bÄde eksperter og ikke-eksperter. Arbeidet vÄrt av mangefasetterte fysiologidata er oppsummert i to studier i avhandlingen. Hver studie omhandler prosesser som foregÄr pÄ forskjellige romlig-temporale skalaer og inneholder konkrete eksempler pÄ anvendelse av metodene vurdert av eksperter i feltet. I den fÞrste av de to studiene undersÞkes konsentrasjonen av molekylÊre substanser (metabolitter) ut fra data innsamlet med magnetisk resonansspektroskopi (MRS), en avansert biokjemisk teknikk som brukes til Ä identifisere metabolske forbindelser i levende vev. Selv om MRS kan ha svÊrt hÞy sensitivitet og spesifisitet i medisinske anvendelser, er analyseresultatene fra denne modaliteten abstrakte og vanskelige Ä forstÄ ogsÄ for medisinskfaglige eksperter i feltet. VÄr designstudie som undersÞkte oppgavene og kravene til ekspertutforskende analyse av disse dataene fÞrte til utviklingen av SpectraMosaic. Dette er en ny applikasjon som gjÞr det mulig for domeneeksperter Ä analysere konsentrasjonen av metabolitter normalisert for en hel kohort, eller etter prÞveregion, individ, opptaksdato, eller status pÄ hjernens aktivitetsnivÄ ved undersÞkelsestidspunktet. I den andre studien foreslÄs en metode for Ä utfÞre utforskende analyser av flerdimensjonale fysiologiske data i motsatt ende av den romlig-temporale skalaen, nemlig pÄ populasjonsnivÄ. En effektiv arbeidsflyt for utforskende dataanalyse mÄ kritisk identifisere interessante mÞnstre og relasjoner, noe som blir stadig vanskeligere nÄr dimensjonaliteten til dataene Þker. Selv om dette delvis kan lÞses med eksisterende reduksjonsteknikker er det alltid en fare for at subtile mÞnstre kan gÄ tapt i reduksjonsprosessen. Isteden presenterer vi i studien DimLift, en iterativ dimensjonsreduksjonsteknikk som muliggjÞr brukeridentifikasjon av interessante mÞnstre og relasjoner som kan ligge subtilt i et datasett gjennom dimensjonale bunter. NÞkkelen til denne metoden er brukerens evne til Ä styre dimensjonalitetsreduksjonen slik at den fÞlger brukerens egne undersÞkelseslinjer. For videre Ä undersÞke kommunikasjon til eksperter og ikke-eksperter, studeres i neste arbeid utformingen av visualiseringer for kommunikasjon til publikum med ulike nivÄer av ekspertnivÄ. Det er naturlig Ä forvente at eksperter innen et emne kan ha ulike preferanser og kriterier for Ä vurdere en visuell kommunikasjon i forhold til et ikke-ekspertpublikum. Dette pÄvirker hvor effektivt et bilde kan benyttes til Ä formidle en gitt scenario. Med utgangspunkt i ulike teknikker innen biomedisinsk illustrasjon og visualisering, gjennomfÞrte vi derfor en utforskende studie av kriteriene som publikum bruker nÄr de evaluerer en biomedisinsk prosessvisualisering mÄlrettet for kommunikasjon. Fra denne studien identifiserte vi muligheter for ytterligere konvergens av biomedisinsk illustrasjon og visualiseringsteknikker for mer mÄlrettet visuell kommunikasjonsdesign. SÊrlig beskrives i stÞrre dybde utviklingen av semantisk konsistente retningslinjer for farging av molekylÊre scener. Hensikten med slike retningslinjer er Ä heve den vitenskapelige kompetansen til ikke-ekspertpublikum innen molekyler visualisering, som vil vÊre spesielt relevant for kommunikasjon til befolkningen i forbindelse med folkehelseopplysning. All kode og empiriske funn utviklet i arbeidet med denne avhandlingen er Äpen kildekode og tilgjengelig for gjenbruk av det vitenskapelige miljÞet og offentligheten. Metodene og funnene presentert i denne avhandlingen danner et grunnlag for tverrfaglig biomedisinsk illustrasjon og visualiseringsforskning, og Äpner flere muligheter for fortsatt arbeid med visualisering av fysiologiske prosesser.The overarching theme of this thesis is the cross-disciplinary application of medical illustration and visualization techniques to address challenges in exploring, analyzing, and communicating aspects of physiology to audiences with differing expertise. Describing the myriad biological processes occurring in living beings over time, the science of physiology is complex and critical to our understanding of how life works. It spans many spatio-temporal scales to combine and bridge the basic sciences (biology, physics, and chemistry) to medicine. Recent years have seen an explosion of new and finer-grained experimental and acquisition methods to characterize these data. The volume and complexity of these data necessitate effective visualizations to complement standard analysis practice. Visualization approaches must carefully consider and be adaptable to the user's main task, be it exploratory, analytical, or communication-oriented. This thesis contributes to the areas of theory, empirical findings, methods, applications, and research replicability in visualizing physiology. Our contributions open with a state-of-the-art report exploring the challenges and opportunities in visualization for physiology. This report is motivated by the need for visualization researchers, as well as researchers in various application domains, to have a centralized, multiscale overview of visualization tasks and techniques. Using a mixed-methods search approach, this is the first report of its kind to broadly survey the space of visualization for physiology. Our approach to organizing the literature in this report enables the lookup of topics of interest according to spatio-temporal scale. It further subdivides works according to any combination of three high-level visualization tasks: exploration, analysis, and communication. This provides an easily-navigable foundation for discussion and future research opportunities for audience- and task-appropriate visualization for physiology. From this report, we identify two key areas for continued research that begin narrowly and subsequently broaden in scope: (1) exploratory analysis of multifaceted physiology data for expert users, and (2) communication for experts and non-experts alike. Our investigation of multifaceted physiology data takes place over two studies. Each targets processes occurring at different spatio-temporal scales and includes a case study with experts to assess the applicability of our proposed method. At the molecular scale, we examine data from magnetic resonance spectroscopy (MRS), an advanced biochemical technique used to identify small molecules (metabolites) in living tissue that are indicative of metabolic pathway activity. Although highly sensitive and specific, the output of this modality is abstract and difficult to interpret. Our design study investigating the tasks and requirements for expert exploratory analysis of these data led to SpectraMosaic, a novel application enabling domain researchers to analyze any permutation of metabolites in ratio form for an entire cohort, or by sample region, individual, acquisition date, or brain activity status at the time of acquisition. A second approach considers the exploratory analysis of multidimensional physiological data at the opposite end of the spatio-temporal scale: population. An effective exploratory data analysis workflow critically must identify interesting patterns and relationships, which becomes increasingly difficult as data dimensionality increases. Although this can be partially addressed with existing dimensionality reduction techniques, the nature of these techniques means that subtle patterns may be lost in the process. In this approach, we describe DimLift, an iterative dimensionality reduction technique enabling user identification of interesting patterns and relationships that may lie subtly within a dataset through dimensional bundles. Key to this method is the user's ability to steer the dimensionality reduction technique to follow their own lines of inquiry. Our third question considers the crafting of visualizations for communication to audiences with different levels of expertise. It is natural to expect that experts in a topic may have different preferences and criteria to evaluate a visual communication relative to a non-expert audience. This impacts the success of an image in communicating a given scenario. Drawing from diverse techniques in biomedical illustration and visualization, we conducted an exploratory study of the criteria that audiences use when evaluating a biomedical process visualization targeted for communication. From this study, we identify opportunities for further convergence of biomedical illustration and visualization techniques for more targeted visual communication design. One opportunity that we discuss in greater depth is the development of semantically-consistent guidelines for the coloring of molecular scenes. The intent of such guidelines is to elevate the scientific literacy of non-expert audiences in the context of molecular visualization, which is particularly relevant to public health communication. All application code and empirical findings are open-sourced and available for reuse by the scientific community and public. The methods and findings presented in this thesis contribute to a foundation of cross-disciplinary biomedical illustration and visualization research, opening several opportunities for continued work in visualization for physiology.Doktorgradsavhandlin

    Single cell molecular alterations reveal target cells and pathways of concussive brain injury.

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    The complex neuropathology of traumatic brain injury (TBI) is difficult to dissect, given the convoluted cytoarchitecture of affected brain regions such as the hippocampus. Hippocampal dysfunction during TBI results in cognitive decline that may escalate to other neurological disorders, the molecular basis of which is hidden in the genomic programs of individual cells. Using the unbiased single cell sequencing method Drop-seq, we report that concussive TBI affects previously undefined cell populations, in addition to classical hippocampal cell types. TBI also impacts cell type-specific genes and pathways and alters gene co-expression across cell types, suggesting hidden pathogenic mechanisms and therapeutic target pathways. Modulating the thyroid hormone pathway as informed by the T4 transporter transthyretin Ttr mitigates TBI-associated genomic and behavioral abnormalities. Thus, single cell genomics provides unique information about how TBI impacts diverse hippocampal cell types, adding new insights into the pathogenic pathways amenable to therapeutics in TBI and related disorders

    Multidimensional annotation of the Escherichia coli K-12 genome

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    The annotation of the Escherichia coli K-12 genome in the EcoCyc database is one of the most accurate, complete and multidimensional genome annotations. Of the 4460 E. coli genes, EcoCyc assigns biochemical functions to 76%, and 66% of all genes had their functions determined experimentally. EcoCyc assigns E. coli genes to Gene Ontology and to MultiFun. Seventy-five percent of gene products contain reviews authored by the EcoCyc project that summarize the experimental literature about the gene product. EcoCyc information was derived from 15 000 publications. The database contains extensive descriptions of E. coli cellular networks, describing its metabolic, transport and transcriptional regulatory processes. A comparison to genome annotations for other model organisms shows that the E. coli genome contains the most experimentally determined gene functions in both relative and absolute terms: 2941 (66%) for E. coli, 2319 (37%) for Saccharomyces cerevisiae, 1816 (5%) for Arabidopsis thaliana, 1456 (4%) for Mus musculus and 614 (4%) for Drosophila melanogaster. Database queries to EcoCyc survey the global properties of E. coli cellular networks and illuminate the extent of information gaps for E. coli, such as dead-end metabolites. EcoCyc provides a genome browser with novel properties, and a novel interactive display of transcriptional regulatory networks

    Visualization of the distribution of autophosphorylated calcium/calmodulin-dependent protein kinase II after tetanic stimulation in the CA1 area of the hippocampus

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    Autophosphorylation of calcium/calmodulin-dependent protein kinase II (CaMKII) at threonine-286 produces Ca2+-independent kinase activity and has been proposed to be involved in induction of long-term potentiation by tetanic stimulation in the hippocampus. We have used an immunocytochemical method to visualize and quantify the pattern of autophosphorylation of CaMKII in hippocampal slices after tetanization of the Schaffer collateral pathway. Thirty minutes after tetanic stimulation, autophosphorylated CaM kinase II (P-CaMKII) is significantly increased in area CA1 both in apical dendrites and in pyramidal cell somas. In apical dendrites, this increase is accompanied by an equally significant increase in staining for nonphosphorylated CaM kinase II. Thus, the increase in P-CaMKII appears to be secondary to an increase in the total amount of CaMKII. In neuronal somas, however, the increase in P-CaMKII is not accompanied by an increase in the total amount of CaMKII. We suggest that tetanic stimulation of the Schaffer collateral pathway may induce new synthesis of CaMKII molecules in the apical dendrites, which contain mRNA encoding its alpha-subunit. In neuronal somas, however, tetanic stimulation appears to result in long-lasting increases in P-CaMKII independent of an increase in the total amount of CaMKII. Our findings are consistent with a role for autophosphorylation of CaMKII in the induction and/or maintenance of long-term potentiation, but they indicate that the effects of tetanus on the kinase and its activity are not confined to synapses and may involve induction of new synthesis of kinase in dendrites as well as increases in the level of autophosphorylated kinase

    Metabolic network visualization eliminating node redundance and preserving metabolic pathways

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    <p>Abstract</p> <p>Background</p> <p>The tools that are available to draw and to manipulate the representations of metabolism are usually restricted to metabolic pathways. This limitation becomes problematic when studying processes that span several pathways. The various attempts that have been made to draw genome-scale metabolic networks are confronted with two shortcomings: 1- they do not use contextual information which leads to dense, hard to interpret drawings, 2- they impose to fit to very constrained standards, which implies, in particular, duplicating nodes making topological analysis considerably more difficult.</p> <p>Results</p> <p>We propose a method, called MetaViz, which enables to draw a genome-scale metabolic network and that also takes into account its structuration into pathways. This method consists in two steps: a clustering step which addresses the pathway overlapping problem and a drawing step which consists in drawing the clustered graph and each cluster.</p> <p>Conclusion</p> <p>The method we propose is original and addresses new drawing issues arising from the no-duplication constraint. We do not propose a single drawing but rather several alternative ways of presenting metabolism depending on the pathway on which one wishes to focus. We believe that this provides a valuable tool to explore the pathway structure of metabolism.</p
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