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As a beginner, I would like to learn more about gene clustering analysis, namely discovering groups of correlated genes potentially coregulated or associated to some conditions or finding patterns in gene expression data, identification of coexpressed genes from microarray data.

I was looking up for some books, but all of them are a little too much biology-heavy for me, given the fact that I have a Computer Science background. I would like to dive into algorithms such as hierarchical clustering, k-means algorithm, pattern-based clustering and other methods, so a book addressing these would be of real help.

If you have any suggestions, I would be grateful.

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    $\begingroup$ Usually, people do not ask for book recommendations on this site. Quora, Researchgate, Reddit, or maybe Biostars are the perfect choices to look for such questions. Still, to give you a clue to continue, If you've previously read some books about "Biostatistics", "Bioinformatics", "R/Python programming" and have a general understanding of what is a protein and what is DNA ("General Biochemistry"), the next step should be reading research papers, indeed. If you lack the mentioned principles, then the best strategy would be reading those first. $\endgroup$ – Sam Apr 14 at 11:36
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    $\begingroup$ Just one more thing. In the case of Bioinformatics, always, always read books that are recent and new. Do not read old books (before 2005 or even 2010) as the area has evolved pretty much in recent years and many old links and websites are not available now $\endgroup$ – Sam Apr 14 at 11:38

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