84 research outputs found
Behavior settings revisited: eine moderne Variation der Barker-Studie "One Boy's Day" mit Hilfe einer Videoaufzeichnung
In dieser Arbeit wird die Methode des Behavior Specimen Record, zurückgehend auf Roger G. Barker und Herbert Wright (1951, 1955), verbunden mit ihrem Konzept der Behavior Settings aufgegriffen. Nach einer kurzen Beschreibung der Konzeption Barkers folgt die Darstellung einer an der TU Berlin durchgeführten Erhebung, bei der die Mutter eines Kleinkindes einen Tag lang beobachtet wurde. Als Hilfsmittel kam dabei eine Videokamera zum Einsatz, mit Hilfe derer der Tagesverlauf vollständig aufgezeichnet wurde. Diese Videoaufzeichnung bildete die Grundlage der Auswertung, als deren Ergebnis sich neben einer genauen quantitativen Analyse hinsichtlich der Dauer aller Aktivitäten auch eine qualitative Verlaufsbeschreibung, orientiert an der Idee der Behavior Settings, ergab
The word landscape of the non-coding segments of the Arabidopsis thaliana genome
<p>Abstract</p> <p>Background</p> <p>Genome sequences can be conceptualized as arrangements of motifs or words. The frequencies and positional distributions of these words within particular non-coding genomic segments provide important insights into how the words function in processes such as mRNA stability and regulation of gene expression.</p> <p>Results</p> <p>Using an enumerative word discovery approach, we investigated the frequencies and positional distributions of all 65,536 different 8-letter words in the genome of <it>Arabidopsis thaliana</it>. Focusing on promoter regions, introns, and 3' and 5' untranslated regions (3'UTRs and 5'UTRs), we compared word frequencies in these segments to genome-wide frequencies. The statistically interesting words in each segment were clustered with similar words to generate motif logos. We investigated whether words were clustered at particular locations or were distributed randomly within each genomic segment, and we classified the words using gene expression information from public repositories. Finally, we investigated whether particular sets of words appeared together more frequently than others.</p> <p>Conclusion</p> <p>Our studies provide a detailed view of the word composition of several segments of the non-coding portion of the <it>Arabidopsis </it>genome. Each segment contains a unique word-based signature. The respective signatures consist of the sets of enriched words, 'unwords', and word pairs within a segment, as well as the preferential locations and functional classifications for the signature words. Additionally, the positional distributions of enriched words within the segments highlight possible functional elements, and the co-associations of words in promoter regions likely represent the formation of higher order regulatory modules. This work is an important step toward fully cataloguing the functional elements of the <it>Arabidopsis </it>genome.</p
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An integrative view of the regulatory and transcriptional landscapes in mouse hematopoiesis.
Thousands of epigenomic data sets have been generated in the past decade, but it is difficult for researchers to effectively use all the data relevant to their projects. Systematic integrative analysis can help meet this need, and the VISION project was established for validated systematic integration of epigenomic data in hematopoiesis. Here, we systematically integrated extensive data recording epigenetic features and transcriptomes from many sources, including individual laboratories and consortia, to produce a comprehensive view of the regulatory landscape of differentiating hematopoietic cell types in mouse. By using IDEAS as our integrative and discriminative epigenome annotation system, we identified and assigned epigenetic states simultaneously along chromosomes and across cell types, precisely and comprehensively. Combining nuclease accessibility and epigenetic states produced a set of more than 200,000 candidate cis-regulatory elements (cCREs) that efficiently capture enhancers and promoters. The transitions in epigenetic states of these cCREs across cell types provided insights into mechanisms of regulation, including decreases in numbers of active cCREs during differentiation of most lineages, transitions from poised to active or inactive states, and shifts in nuclease accessibility of CTCF-bound elements. Regression modeling of epigenetic states at cCREs and gene expression produced a versatile resource to improve selection of cCREs potentially regulating target genes. These resources are available from our VISION website to aid research in genomics and hematopoiesis.National Institute of Diabetes and Digestive and Kidney Diseases (grant number R24DK106766-01A1), the National Human Genome Research Institute (grant number U54HG006998
Large Interferometer For Exoplanets (LIFE): II. Signal simulation, signal extraction, and fundamental exoplanet parameters from single-epoch observations
peer reviewedContext. The Large Interferometer For Exoplanets (LIFE) initiative is developing the science and a technology road map for an ambitious space mission featuring a space-based mid-infrared (MIR) nulling interferometer in order to detect the thermal emission of hundreds of exoplanets and characterize their atmospheres.
Aims. In order to quantify the science potential of such a mission, in particular in the context of technical trade-offs, an instrument simulator is required. In addition, signal extraction algorithms are needed to verify that exoplanet properties (e.g., angular separation and spectral flux) contained in simulated exoplanet data sets can be accurately retrieved.
Methods. We present LIFEsim, a software tool developed for simulating observations of exoplanetary systems with an MIR space-based nulling interferometer. It includes astrophysical noise sources (i.e., stellar leakage and thermal emission from local zodiacal and exozodiacal dust) and offers the flexibility to include instrumental noise terms in the future. Here, we provide some first quantitative limits on instrumental effects that would allow the measurements to remain in the fundamental noise limited regime. We demonstrate updated signal extraction approaches to validating signal-to-noise ratio (S/N) estimates from the simulator. Monte Carlo simulations are used to generate a mock survey of nearby terrestrial exoplanets and determine to which accuracy fundamental planet properties can be retrieved.
Results. LIFEsim provides an accessible way to predict the expected S/N of future observations as a function of various key instrument and target parameters. The S/Ns of the extracted spectra are photon noise dominated, as expected from our current simulations. Signals from multi-planet systems can be reliably extracted. From single-epoch observations in our mock survey of small (R < 1.5 REarth) planets orbiting within the habitable zones of their stars, we find that typical uncertainties in the estimated effective temperature of the exoplanets are ≲10%, for the exoplanet radius ≲20%, and for the separation from the host star ≲2%. Signal-to-noise-ratio values obtained in the signal extraction process deviate by less than 10% from purely photon-counting statistics-based S/Ns.
Conclusions. LIFEsim has been sufficiently well validated so that it can be shared with a broader community interested in quantifying various exoplanet science cases that a future space-based MIR nulling interferometer could address. Reliable signal extraction algorithms exist, and our results underline the power of the MIR wavelength range for deriving fundamental exoplanet properties from single-epoch observations.Large Interferometer For Exoplanets (LIFE
Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context
Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts
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