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<math>\int_{-N}^{N} e^x\, dx</math>
<math>\int_{-N}^{N} e^x\, dx</math>


<biblio>
<biblio>
#exemple2 isbn=076374722X
#Barash2010 pmid=20445623
#exemple1 pmid=11333547 //el mejor artículo de la historia
#MultipleFluors pmid=15558047
#exemple3 autor ''Titol''. Ciutat, any. O el que sigui.
#SmolkeNAR2010 pmid=20385591
</biblio>
#IntronSizeDist pmid=16980575
 
#Kangueane2004 pmid=15217358
<biblio>
#SmithReview2005 pmid=15956978
#aha pmid=16908781
#SplicingNomenclature pmid=18688268
#prodigy ''Atrial Fibrilation''. Prodigy guidance. Última revisió Abril 2003.
#MetaHart pmid=10507957
#NICE National Collaborating Centre for Chronich Conditions. ''NICE Cinical Guideline 36: Atrial fibrilation (The management of atrial fibrilation)''. Issue date: June 2006.
#CocAAS pmid=16235290
#AFP pmid=15999873
#MetaTesta pmid=15872032
</biblio>
</biblio>

Revisió del 09:11, 12 ago 2011

Probando

<R output="html" iframe="width:100%;height:250px;"> prob=0.15; nmin=1; nmax=15; x=6 m <-pbinom(rep(0:x, each = nmax-nmin+1), rep(nmin:nmax,x), prob) dim(m) <- c(nmax-nmin+1,x+1) m <- t(m) colnames(m) <- format(nmin:nmax) rownames(m) <- format(0:x) outHTML(rhtml, m, title="x\n", format="f", digits=4) </R>

<R output="display" iframe="width:400px;height:400px"> pdf(rpdf, width=5, height=5) n <- 10 prob <- 0.2 x <- seq(0, n, 1) p <- dbinom(x, n, prob) param <- list(n, prob) main <- c("Binomialverteilung - Wahrscheinlichkeitsfunktion", paste (c("Stichprobenumfang n", "Wahrscheinlichkeit p"), param, sep="=")) plot(x,p, type="h", main=main) </R>

  1. Barash Y, Calarco JA, Gao W, Pan Q, Wang X, Shai O, Blencowe BJ, and Frey BJ. Deciphering the splicing code. Nature. 2010 May 6;465(7294):53-9. DOI:10.1038/nature09000 | PubMed ID:20445623 | HubMed [Barash2010]
  2. Shaner NC, Campbell RE, Steinbach PA, Giepmans BN, Palmer AE, and Tsien RY. Improved monomeric red, orange and yellow fluorescent proteins derived from Discosoma sp. red fluorescent protein. Nat Biotechnol. 2004 Dec;22(12):1567-72. DOI:10.1038/nbt1037 | PubMed ID:15558047 | HubMed [MultipleFluors]
  3. Culler SJ, Hoff KG, Voelker RB, Berglund JA, and Smolke CD. Functional selection and systematic analysis of intronic splicing elements identify active sequence motifs and associated splicing factors. Nucleic Acids Res. 2010 Aug;38(15):5152-65. DOI:10.1093/nar/gkq248 | PubMed ID:20385591 | HubMed [SmolkeNAR2010]
  4. Hong X, Scofield DG, and Lynch M. Intron size, abundance, and distribution within untranslated regions of genes. Mol Biol Evol. 2006 Dec;23(12):2392-404. DOI:10.1093/molbev/msl111 | PubMed ID:16980575 | HubMed [IntronSizeDist]
  5. Sakharkar MK, Chow VT, and Kangueane P. Distributions of exons and introns in the human genome. In Silico Biol. 2004;4(4):387-93. PubMed ID:15217358 | HubMed [Kangueane2004]
  6. Matlin AJ, Clark F, and Smith CW. Understanding alternative splicing: towards a cellular code. Nat Rev Mol Cell Biol. 2005 May;6(5):386-98. DOI:10.1038/nrm1645 | PubMed ID:15956978 | HubMed [SmithReview2005]
  7. Sammeth M, Foissac S, and Guigó R. A general definition and nomenclature for alternative splicing events. PLoS Comput Biol. 2008 Aug 8;4(8):e1000147. DOI:10.1371/journal.pcbi.1000147 | PubMed ID:18688268 | HubMed [SplicingNomenclature]

Totes los resumits de Medline : PubMed | HubMed