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Hello: I have a 4-column dataset: Crime, Education, Urbanization, Age. I want to construct a multiple linear regression to find the effect of Education, Urbanization, and Age on Crime" lm(Crime ~ Education + Urbanization + Age) If I use + in above statement, does it mean it will build a model to find the relationship between Crime and Education when Urbanization and Age are held constant?

Hi: I have clustered microarray gene expression data and trying to map between microarray probe, gene, pathway, gene ontology, and homology for a set of (affy) microarray probes. Is there any package in R which facilitates this? I am looking at bioconductor, but till now could not find a solution. A link to some worked example would be appreciated. Thanks and regards. John [[alternative HTML

Hello: I have looked at the bnlearn and deal packages for infering bayesian network. Can anyone suggest any other suitable package for constructing bayesian gene regulatory network using gene expression data? Thanks! John [[alternative HTML version deleted]]

Hi: I am trying to search PubMed abstracts which contains BOTH two terms: COL4A1 AND Ocular. I am using the following code: url= "http://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi?" search = paste(url, "db=pubmed&term=COL4A1+AND+Ocular[abstract]&retmax=300", sep="") docId <- xmlTreeParse(getURL(paste(url, search, sep="")),

Hi: I am trying to query pubmed abstracts using the following syntax: url= "http://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi?" search = paste(url, "db=pubmed&term=", queryTerm1, "+AND+", queryTerm2,"+OR+",queryTerm3, "+OR+", queryTerm4, "[abstract]&retmax=100&usehistory=y", sep="") docId <-

Hi: I have calculated the Silhouette score and Dunn score after hierarchical clustering for 3 clusters: #Distance measure d <- dist(USArrests, method = "euclidean") #Hierarchical clustering hc <- hclust(dist(USArrests), "ave") #calculating silhouette value for 3 clusters sil<- silhouette(cutree(hc, k=3), d) #calculating Dunn index for 3 clusters clus <- cutree(hc,