stanford's machine learning applied in bioinformatics

[delinquentme]

2 questions:

1) Anyone on this forum also taking the ml-class offered?
2) Specific examples of machine learning used in bioinformatics

So I'm about half way through the class and I started with the specific intent of applying this to bioinformatics ...

And while I understand what I'm working on ... I'd really like more practice!

linear regression
logistic regression
neural networks
support vector machines

[prm36]

Shameless self promotion. Paper describing application of SVMs for the prediction of putative vaccine candidates from bacterial genome sequence.

Paul

[delinquentme]

I'm ok with shameless!

sounds .... amazingly spot on... !

if( published? )
" where can I find one? "
else
" WHEN!? "
end

and I've got a class full of smart and optimistic kids looking to learn some things ... do you have any leads .. or like annoying pet projects you'd like to talk about?

[prm36]

Oops,
forgot to include link!

http://www.ncbi.nlm.nih.gov/pubmed/21864619

[nkwuji]

Hi,

I am following the ml class. The techniques taught in the class are very useful in biology.

Actually until I took the class, I didnot realize that the techniques used in microarray data analysis (or RNA-seq), for example, cluster analysis, PCA, clustering, are machine learning techniques.

Plus, linear regression is used a lot in modeling gene expression and gene set analysis, e.g. limma, GSEAlm.

Moreover, Octave, the programming environment used in the course (or a free version of Matlab), is also widely used in bioinformatics.

You won't regret taking the course.

Cheers,
Jun

[delinquentme]

Paul:

http://www.sciencedirect.com/science...64410X11012990
^ Im posting this guy to reddit

Jun:
Might I ask how you came upon that fact? Where can I read more about it?

[nkwuji]

Paul:

http://www.sciencedirect.com/science...64410X11012990
^ Im posting this guy to reddit

Jun:
Might I ask how you came upon that fact? Where can I read more about it?

Just a few examples as mentioned in my post.

Multivariate analysis package for microarray (clustering, PCA, COA ...)
Culhane AC, Thioulouse J, Perriere G, Higgins DG (2005) MADE4: an R package for multivariate analysis of gene expression data. Bioinformatics 21:2789-2790.

Linear model in microarray DE gene
Smyth GK (2004) Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Stat Appl Genet Mol Biol 3:Article3.

Linear model in gene set analysis
Oron AP, Jiang Z, Gentleman R (2008) Gene set enrichment analysis using linear models and diagnostics. Bioinformatics 24:2586-2591.