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Comments on “Clinical drug response can be predicted using baseline gene expression levels and in vitro drug sensitivity in cell lines”. I recently co-authored a paper in Genome Biology entitled “Clinical drug response can be predicted using baseline gene expression levels and in vitro drug sensitivity in cell lines”. The paper proposes a solution to a problem that has a long and sordid history in pharmacogenomics (see “Deception at Duke” on YouTube). CHOICE OF MACHINE LEARNING ALGORITHM. First make up s...

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Bioinformatics - | bioinformaticstutorials.com Reviews
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Comments on “Clinical drug response can be predicted using baseline gene expression levels and in vitro drug sensitivity in cell lines”. I recently co-authored a paper in Genome Biology entitled “Clinical drug response can be predicted using baseline gene expression levels and in vitro drug sensitivity in cell lines”. The paper proposes a solution to a problem that has a long and sordid history in pharmacogenomics (see “Deception at Duke” on YouTube). CHOICE OF MACHINE LEARNING ALGORITHM. First make up s...
<META>
KEYWORDS
1 bioinformatics
2 background
3 the future
4 the paper
5 no comments
6 plot m pch=seq 9
7 cm cov m1
8 eigenvecs eigen cm $vectors
9 eval1 eigen cm $values 1
10 eval2 eigen cm $values 2
CONTENT
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bioinformatics,background,the future,the paper,no comments,plot m pch=seq 9,cm cov m1,eigenvecs eigen cm $vectors,eval1 eigen cm $values 1,eval2 eigen cm $values 2,rowfeatvec t eigenvecs,rowdataadj t m1,plot t finaldata pch=seq 9,bioclite writexls
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Bioinformatics - | bioinformaticstutorials.com Reviews

https://bioinformaticstutorials.com

Comments on “Clinical drug response can be predicted using baseline gene expression levels and in vitro drug sensitivity in cell lines”. I recently co-authored a paper in Genome Biology entitled “Clinical drug response can be predicted using baseline gene expression levels and in vitro drug sensitivity in cell lines”. The paper proposes a solution to a problem that has a long and sordid history in pharmacogenomics (see “Deception at Duke” on YouTube). CHOICE OF MACHINE LEARNING ALGORITHM. First make up s...

LINKS TO THIS WEBSITE

genemed.uchicago.edu genemed.uchicago.edu

Paul Geeleher Hompage - University of Chicago

http://genemed.uchicago.edu/~pgeeleher

I am a postdoc in bioinformatics in Dr. R. Stephanie Huang's lab at the University of Chicago. I split my time evenly between Dr. Huang's lab in the Section of Medicine and Prof. Nancy Cox lab in the Section of Genetic Medicine. My reseach interests are currently focused on leveraging high throughput data (i.e. microarray and next generation seuencing data) to tailor drug treatments. Email: paulgeeleher at gmail dot com. R Code and instructions for Genome Biology paper.

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Comments on “Clinical drug response can be predicted using baseline gene expression levels and in vitro drug sensitivity in cell lines”. I recently co-authored a paper in Genome Biology entitled “Clinical drug response can be predicted using baseline gene expression levels and in vitro drug sensitivity in cell lines”. The paper proposes a solution to a problem that has a long and sordid history in pharmacogenomics (see “Deception at Duke” on YouTube). CHOICE OF MACHINE LEARNING ALGORITHM. First make up s...

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