search for: toxin

Getting the through items from a has_many :through :uniq relationship In a nutshell, I have been using the has_many :through :uniq relationship, and I want a DRY way to list the join model objects. Currently, my objects include taxon objects, toxin objects, data_object objects, and taxon_toxin_citation objects ("citation" is another word for data_object). A taxon has many data objects, has many taxon_toxin_citations, and has many toxins through taxon_toxin_citations. As well as a taxon causing many toxins, a toxin can be caused by m...

...would value your comments=20 =20 Thanks =20 Best wishes, =20 Mick =20 Prof M.J. Crawley =20 Imperial College London Silwood Park Ascot Berks SL5 7PY UK =20 Phone (0) 207 5942 216 Fax (0) 207 5942 339 =20 The data are from a bioassay in which a factorial experiment with two factors (antibio and toxin) each with three levels was replicated four times. The response is "mi" and "n-mi" =20 Note that lines 17 to 20 in the dataframe have no failures (24 dead out of 24 individuals) data<-read.table("c:\\temp\\ab1.txt",header=3DT) attach(data) names(data) =20 [1] &quot...

Hi everyone, I would like to fit a predictive model to my data in order to compare absorbance readings to a toxin standard. This data was obtained by exposing red blood cells to different toxin concentrations, which lead to the lysis of the red blood cells, increasing the absorbance (hemoglobin is freed). The data has a sigmoid shape (see below), so I thought about fitting a logistic model to the data so that...

I have 11 vectors representing insect survival probabilities in response to different levels of toxins at 10 concentrations lx100=c(1,1,1,.8,.5,.4,.2,0) day100=c(0,1,2,3,4,5,6,7,8) lx90=c(1,1,1,1,.9,.8,.6,.4,.2,.1,0) day90=c(0,1,2,3,4,5,6,7,8,9,10) #...and so on10% and a zero (control) series lx0=c(1,1,1,1,1,1,.9,.9,.8,.8,.6,.5,.4,.3,.2,.1,.1,0) day0=c(0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,1...

...C1q ? lymphocyte Antibody-secreting (plasma) cell Ant..." My approach generates this snippet for the same search string (not included in the example): "mechanisms of humoral immunity the elimination of <b>extracellular</b> <b>microbes</b> and toxins 143 9 immunologic tolerance ... for example antibodies function to eliminate <b>microbes</b> in extra <b>extracellular</b> fluids and activated t lymphocytes ... and are designed to provide defense against <b>extracellular</b> <b>microbes</b> and int...

Hi i would like to use some graphs or tables to explore the data and make some sensible guesses of what to expect to see in a glm model to assess if toxin concentration and sex have a relationship with the kill rate of rats. But i cant seem to work it out as i have two predictor variables~help?Thanks.:) Here's my data. > rat.toxic<-read.table(file="Rats.csv",header=T,row.names=NULL,sep=",") > attach(rat.toxic) >...

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