search for: toxins

...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 many taxa. And there are many taxon_toxin_citations linking a given taxon with a given toxin. (If anyone is interested in project, it is currently hosted at http://code.google.com/p/habevent/ ) If you w...

In this real example (below), all four of the replicates in one treatment combination had zero failures, and this produced a very high standard error in the summary.lm. =20 Just adding one failure to one of the replicates produced a well-behaved standard error. =20 I don't know if this is a bug, but it is certainly hard for users to understand. =20 I would value your comments=20 =20 Thanks =20

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

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(0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17...

...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 intr...

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. >

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