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...: int 27481 17013 24751 27498 27486 30984 17293 28329 27459 27482 ... $ NAME : Factor w/ 4040 levels "||*AA037178|Hs.179661|FK506 binding protein 1A (12kD)",..: 3444 3445 3446 3444 3445 657 1788 3121 3119 3119 ... $ MLC94.46_LYM009_de.novo.untreated : num 0.234 0.452 0.405 0.115 0.249 ... $ MLC96.45_LYM186_de.novo.untreated : num -0.1725 -0.0387 -0.0413 -0.0242 -0.1028 ... $ MLC91.27_LYM427_de.novo.untreated : num 0.200 0.175 0.195 0.223 0.179 ... $ MLC96.84_LYM225_transformed : num -0.213 -0....

...Age of adults (days)", limits=c(0,16), expand=c(0,0), breaks=c(5, 10, 15)) + scale_colour_discrete(name ="Group", breaks=c("ace", "ctrlAM","met"), labels=c("acetone", "untreated","methoprene"))+ theme_bw() + # maek background theme black and white opts(legend.justification=c(1,0),# legend justification needs to be in the (options) le...

Hello, r-help at r-project.orgbarplot(twcons.area, beside=T, col=c("green4", "blue", "red3", "gray"), xlab="estate", ylab="number of persons", ylim=c(0, 110), legend.text=c("treated", "mix", "untreated", "NA")) produces a barplot very fine. In addition, I'd like to get the bars' absolute values on the top of the bars. How can I produce this in an easy way? Thanks S?ren

...] + x.temp) panel.lines(x.temp,y.temp,col=2)} if (panel.number==2) { y.temp<-coef(m2.nls)[1] * x.temp/ (coef(m2.nls)[3] + x.temp) panel.lines(x.temp,y.temp,col=2)} }, ylab="Rate of reaction", xlab="Substrate concentration", main = "Puromycin---comparison bt. treated and untreated" ) thanks for any idea

...er (preterminal) half develops cardiac damage, but survives to week 7. The aim of the study was to elucidate the difference in cardiac gene expression of dTGR with THF compared to dTGR showing compensated cardiac hypertrophy, but not yet THF.Experiments were conducted in age-matched 4 week-old male untreated dTGR.Untreated dTGR were divided in two subgroups, rats with cardiac hypertrophy (n=18) and rats with THF (n=8).Rats were killed at age 7 weeks.Total RNAs (five animals per group) were isolated from the left ventricle.For all rgu34_a affymetrix chips were used. Iam using maanova package. In usin...

...er testing . if 45% of the employees have positive indications of asbestos in their lungs , find the probability that twelve employees must be tested in order to find the four positives to send for further testing ? 2. In a small scale trial five seeds are treated with fungicide and five seeds are untreated with fungicide. Seeds were then planted and the number was counted . If four plants actually sprouted what is the probability that a) all four plants emerged form the treated seeds. b)Three of few emerged from the treated seeds Regards Malcolm [[alternative HTML version deleted]]

...ys Yielding Concentration-Mortality Data particularly control - adjustment model from book Bioassay of Entomopathogenic Microbes and Nematodes chapter 7 with R. I used glm with family=binomial and link=probit, but I do not know how to implement parameter gamma (control mortality - mortality of the untreated control insect in this exaple) into model formula. Model in book: pi(x)=gamma+(1-gamma)F(alpha+beta log(x)) F....cumulative probability distribution function data: x=concentration n=number of insect at each run y=number of death among n in given batch run at given concentration Xmat<-dat...

...or 1 month with a regular light and watering regime. At this point they were randomly given 1l of one of 4 different pesticides at one of 4 different concentrations (100%, 75%, 50% or 25% in water). There were 20 pots of grass for each pesticide/concentration giving 320 pots. There were no control (untreated) pots. The response was measured after 1 week and recorded as either: B1 - grass dead B2 - grass affected but not dead B3 - no visible effect I could analyse this as lethal effect vs non-lethal effect (B1 vs B2+B3) or some effect vs no effect (B1+B2 vs B3) binomial model, but I can't see ho...

...rsion of the often used conventional fixed effects (FE) panel models. In contrast to conventional fixed effects models, data are not person ?demeaned?, but 'detrended? by the predicted individual slope of each person or group, which relaxes the assumptions of parallel trends between treated and untreated groups. We are happy about any comments or feedback! Best regards, Tobias Tobias R?ttenauer Department of Social Sciences TU Kaiserslautern Erwin-Schroedinger-Str. 57 67663 Kaiserslautern ruettenauer at sowi.uni-kl.de Tel.: +49 631 205 5785

...rsion of the often used conventional fixed effects (FE) panel models. In contrast to conventional fixed effects models, data are not person ?demeaned?, but 'detrended? by the predicted individual slope of each person or group, which relaxes the assumptions of parallel trends between treated and untreated groups. We are happy about any comments or feedback! Best regards, Tobias Tobias R?ttenauer Department of Social Sciences TU Kaiserslautern Erwin-Schroedinger-Str. 57 67663 Kaiserslautern ruettenauer at sowi.uni-kl.de Tel.: +49 631 205 5785

hi,everybody I have a *time course* data set about a CML cell line treated by two drugs and their combination.The experiment was performed on cDNA microarray platform.The green channel of all the arrays are common,the untreated cell.Here follows the experiment design: a_0hr,a_3hr,a_8hr,a_12hr,a_24hr,a_48hr,a_72hr, b_3hr,b_8hr,b_12hr,b_24hr,b_48hr,b_72hr, ab_3hr,ab_8hr,ab_12hr,ab_24hr,ab_48hr,ab_72hr. A total of 19 *cDNA microarrays*.a_0hr means* *drug *a *treament *0 hours vs. control. *And a_3hrs means drug a tre...

Dear all, I want to see if the treatment of an animal with a specific compound has an effect on the expression of certain genes. Though my question is based in biology, it really is all about how to deal with the standard deviation in normalised data. I have three groups of animals; untreated, treated with placebo, and treated with a single concentration of the compound in question. Gene expression is measured in triplicate, that is I have three values for each measurement of each animal, and normalised to a standard gene. My problem is, that there is no guarantee that one of the me...

Following an example on p 111 in 'Nonlinear Regression with R' by Ritz & Streibig, I have been fitting nls models using square brackets with the grouping variable inside. In their book is this example, in which 'state' is a factor indicating whether a treatment has been used or not: > Puromycin.m1 <- nls(rate ~ Vm[state] * + conc/(K[state] + conc), data = Puromycin,

Dan Gohman wrote: > On Sep 11, 2009, at 9:57 AM, Chris Lattner wrote: > > >> Devang's work on debug info prompted this, thoughts welcome: >> http://nondot.org/sabre/LLVMNotes/ExtensibleMetadata.txt > > The document mentions "instructions" a lot. We'll want to be able to > apply metadata to ConstantExprs as well at least, if not also Arguments >