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Cholera- and Anthrax-Like Toxins

issuu.com/rfieldhouse/docs/journal.pcbi.1001029...
Computer tools helped us uncover and understand potent protein toxins that empower bacterial pathogens against plants, animals and man. These toxins are potential drug targets and researchers can use them to make vaccines. New toxin knowledge aids the long-term goal of finding alternatives to antibiotics, to which pathogens are becoming more resistant. The toxins share similar structure despite low sequence identity, so our search links sequence and structure features. We present a ranked list and computational characterization of six new toxins combined with cell-based tests.
Uploaded by rfieldhouse on 01/05/2011
Digital publication details: 19 pages.

3D cities and numerical weather prediction models: an overview of the methods used in the LUCID

issuu.com/3figs/docs/lucid_met_office_methods_sde...
Transferring spatial data between different types of spatial models is often a much trickier process than GIS professionals would like to admit. This is further complicated if the models were generated for very different purposes and at different levels of spatial granularity and using different spatial projections...
Uploaded by 3figs on 05/12/2010
Digital publication details: 19 pages.

A Noncausal Linear Prediction Based SwitchingMedian Filter for the Removal of Salt and PepperNoise

issuu.com/ideseditor/docs/aceee_ijsip_3_1_1...
In this paper, we propose a switching based median filter for the removal of impulse noise, namely, the salt and pepper noise in gray scale images. The filter is based on the concept of substitution of noisy pixels prior to estimation. It effectively suppresses the impulse noise in two stages. First, the noisy pixels are detected by using the signal dependent rank-ordered mean (SD-ROM) filter. In the second stage, the noisy pixels are first substituted by the first order 2D noncausal linear prediction technique and subsequently replaced by the median value. Extensive simulations are carried out to validate the proposed method. Experimental results show improvements both visually and quantitatively compared to other switching based median filters for the removal of salt-and-pepper noise at different densities.
Uploaded by ideseditor on 01/13/2013
Digital publication details: 7 pages.

IDC Prediction 2013

issuu.com/miriamcampos1/docs/presentaci_n-latin-ameri...
IDC Latin America Prediction 2013
Uploaded by miriamcampos1 on 01/30/2013
Digital publication details: 16 pages.

Climate Prediction S&T Digest, December 2009

issuu.com/climatesti/docs/climate_prediction_digest_1...
34th NOAA Climate Diagnostics and Prediction Workshop special issue
Uploaded by climatesti on 12/22/2009
Digital publication details: 21 pages.
Tags: prediction · noaa · nws · climate

Regarding Influences of Production Processes on Material Parameters in Fatigue Life Prediction

issuu.com/simulia/docs/regarding-influences-productio...
Fatigue life prediction has reached a high level in respect to practical handling and accuracy in the last decades. As a result of insecure or lacking input data deviations between numerical results and test results in terms of cycles till crack initiation are possible. On the one hand, the accuracy of Finite Element results gets better and better because of greatly increasing computer power and mesh density. Whereas on the other hand, the situation is much more critical regarding load data and especially regarding local material properties of the components. In the last few years also the possibilities of process simulation have improved in such, that at least a few local material properties or quality indicators can be predicted with sufficient reliability.
Uploaded by simulia on 05/02/2011
Digital publication details: 1 pages.

Prediction of Atmospheric Pressure at Ground Level using Artificial Neural Network

issuu.com/14110/docs/vol3-issue-1-02-prediction-of-at...
Prediction of Atmospheric Pressure is one important and challenging task that needs lot of attention and study for analyzing atmospheric conditions. Advent of digital computers and development of data driven artificial intelligence approaches like Artificial Neural Networks (ANN) have helped in numerical prediction of pressure. However, very few works have been done till now in this area. The present study developed an ANN model based on the past observations of several meteorological parameters like temperature, humidity, air pressure and vapour pressure as an input for training the model. The novel architecture of the proposed model contains several multilayer perceptron network (MLP) to realize better performance. The model is enriched by analysis of alternative hybrid model of k-means clustering and MLP. The improvement of the performance in the prediction accuracy has been demonstrated by the automatic selection of the appropriate cluster.
Uploaded by 14110 on 01/10/2013
Digital publication details: 8 pages.

Svjetlana Ivanovic Natal Chart + 30 day-by-day prediction

issuu.com/samonetaana/docs/complete_natal_chart_and_3...
Gift from the www.facebook.com/madamastrology- Free Premium Natal Chart Report plus 30 days- day-by-day guide prediction.
Uploaded by samonetaana on 12/20/2012
Digital publication details: 41 pages.

Trend Report

issuu.com/surbhishukla/docs/trends...
A/w 2012/13 Trend prediction
Uploaded by surbhishukla on 05/01/2012
Digital publication details: 27 pages.

Needle in the haystack: structure-based toxin discovery

issuu.com/rfieldhouse/docs/needleinthehaystack...
In the current data-rich era, making the leap from sequence data to knowledge is a task that requires an elegant bioinformatics toolset to pinpoint pressing research questions. Therefore, a strategy to expand important protein-family knowledge is required, particularly in cases in which primary sequence identity is low but structural conservation is high. For example, the mono-ADP-ribosylating toxins fit these criteria and several approaches have been used to accelerate the discovery of new family members. The strategy evolved from conduction of PSIā€“BLAST searches through to the combination of secondary-structure prediction with pattern-based searches. However, a newly developed tactic, in which fold recognition dominates, reduces reliance on sequence similarity and advances scientists toward a true structure-based protein-family expansion methodology.
Uploaded by rfieldhouse on 09/24/2008
Digital publication details: 11 pages.
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