407 research outputs found
SAMNet: a network-based approach to integrate multi-dimensional high throughput datasets
The rapid development of high throughput biotechnologies has led to an onslaught of data describing genetic perturbations and changes in mRNA and protein levels in the cell. Because each assay provides a one-dimensional snapshot of active signaling pathways, it has become desirable to perform multiple assays (e.g. mRNA expression and phospho-proteomics) to measure a single condition. However, as experiments expand to accommodate various cellular conditions, proper analysis and interpretation of these data have become more challenging. Here we introduce a novel approach called SAMNet, for Simultaneous Analysis of Multiple Networks, that is able to interpret diverse assays over multiple perturbations. The algorithm uses a constrained optimization approach to integrate mRNA expression data with upstream genes, selecting edges in the proteinâprotein interaction network that best explain the changes across all perturbations. The result is a putative set of protein interactions that succinctly summarizes the results from all experiments, highlighting the network elements unique to each perturbation. We evaluated SAMNet in both yeast and human datasets. The yeast dataset measured the cellular response to seven different transition metals, and the human dataset measured cellular changes in four different lung cancer models of Epithelial-Mesenchymal Transition (EMT), a crucial process in tumor metastasis. SAMNet was able to identify canonical yeast metal-processing genes unique to each commodity in the yeast dataset, as well as human genes such as ÎČ-catenin and TCF7L2/TCF4 that are required for EMT signaling but escaped detection in the mRNA and phospho-proteomic data. Moreover, SAMNet also highlighted drugs likely to modulate EMT, identifying a series of less canonical genes known to be affected by the BCR-ABL inhibitor imatinib (Gleevec), suggesting a possible influence of this drug on EMT.National Institutes of Health (U.S.) (Grant U54CA112967)National Institutes of Health (U.S.) (Grant R01GN089903)National Science Foundation (U.S.) (Award DB1-0821391)Massachusetts Institute of Technology. Undergraduate Research Opportunities Progra
Superconductivity in two-band systems with variable charge carrier density. The case of MgB2
The theory of thermodynamic properties of two-band superconductor with
reduced density charge carriers is developed on the base of phonon
superconducting mechanism with strong electron-phonon interaction. This theory
is adapted to describe the behavior of critical temperature Tc, energy gaps
Delta1, Delta2, and the relative jump of electron specific heat (Cs - Cn)/Cn in
the point T = Tc along with the variation of charge carrier density in the
compound MgB2 when substitutional impurities with different valence are
introduced into the system. It is shown, that according to the filling
mechanism of energy bands which overlap on Fermi surface, the quantities Tc,
Delta1, Delta2 decrease when this compound is doped with electrons and remain
constant or weakly change when the system is doped with holes. The theory
qualitatively agrees with the experimental data. Also is shown that the
consideration of inter- and intraband scattering of electrons on impurity
potential improves this agreement.Comment: 19 pages, 6 figures, 1 table. to be published in JETP (first number
2007
Narrative Bytes : Data-Driven Content Production in Esports
Esports - video games played competitively that are broadcast to large audiences - are a rapidly growing new form of mainstream entertainment. Esports borrow from traditional TV, but are a qualitatively different genre, due to the high flexibility of content capture and availability of detailed gameplay data. Indeed, in esports, there is access to both real-time and historical data about any action taken in the virtual world. This aspect motivates the research presented here, the question asked being: can the information buried deep in such data, unavailable to the human eye, be unlocked and used to improve the live broadcast compilations of the events? In this paper, we present a large-scale case study of a production tool called Echo, which we developed in close collaboration with leading industry stakeholders. Echo uses live and historic match data to detect extraordinary player performances in the popular esport Dota 2, and dynamically translates interesting data points into audience-facing graphics. Echo was deployed at one of the largest yearly Dota 2 tournaments, which was watched by 25 million people. An analysis of 40 hours of video, over 46,000 live chat messages, and feedback of 98 audience members showed that Echo measurably affected the range and quality of storytelling, increased audience engagement, and invoked rich emotional response among viewers
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Mitigation of off-target toxicity in CRISPR-Cas9 screens for essential non-coding elements.
Pooled CRISPR-Cas9 screens are a powerful method for functionally characterizing regulatory elements in the non-coding genome, but off-target effects in these experiments have not been systematically evaluated. Here, we investigate Cas9, dCas9, and CRISPRi/a off-target activity in screens for essential regulatory elements. The sgRNAs with the largest effects in genome-scale screens for essential CTCF loop anchors in K562 cells were not single guide RNAs (sgRNAs) that disrupted gene expression near the on-target CTCF anchor. Rather, these sgRNAs had high off-target activity that, while only weakly correlated with absolute off-target site number, could be predicted by the recently developed GuideScan specificity score. Screens conducted in parallel with CRISPRi/a, which do not induce double-stranded DNA breaks, revealed that a distinct set of off-targets also cause strong confounding fitness effects with these epigenome-editing tools. Promisingly, filtering of CRISPRi libraries using GuideScan specificity scores removed these confounded sgRNAs and enabled identification of essential regulatory elements
What Are You Looking At? Team Fight Prediction Through Player Camera
Esport is a large and still growing industry with vast audiences. Multiplayer Online Battle Arenas (MOBAs), a sub-genre of esports, possess a very complex environment, which often leads to experts missing important coverage while broadcasting live competitions. One common game event that holds significant importance for broadcasting is referred to as a team fight engagement. Professional player's own knowledge and understanding of the game may provide a solution to this problem. This paper suggests a model that predicts and detects ongoing team fights in a live scenario. This approach outlines a novel technique of deriving representations of a complex game environment by relying on player knowledge. This is done by analysing the positions of the in-game characters and their associated cameras, utilising this data to train a neural network. The proposed model is able to both assist in the production of live esport coverage as well as provide a live, expert-derived, analysis of the game without the need of relying on outside sources
Espon-Interstrat. Espon in Integrated Territorial Strategies.
The INTERSTRAT projectâs overall aim is âto encourage and facilitate the use of ESPON 2013 Programme findings in the creation and monitoring of Integrated Territorial Development Strategies (ITDS) and to support transnational learning about the actual and potential contribution of ESPON to integrated policy-making.â We defined integrated territorial development as âthe process of shaping economic, social and environmental change through spatially sensitive policies and programmesâ
TIN-X:target importance and novelty explorer
Abstract
Motivation
The increasing amount of peer-reviewed manuscripts requires the development of specific mining tools to facilitate the visual exploration of evidence linking diseases and proteins.
Results
We developed TIN-X, the Target Importance and Novelty eXplorer, to visualize the association between proteins and diseases, based on text mining data processed from scientific literature. In the current implementation, TIN-X supports exploration of data for G-protein coupled receptors, kinases, ion channels, and nuclear receptors. TIN-X supports browsing and navigating across proteins and diseases based on ontology classes, and displays a scatter plot with two proposed new bibliometric statistics: Importance and Novelty.
Availability and Implementation
http://www.newdrugtargets.org
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