Independent Principal Component Analysis for biologically meaningful dimension reduction of large biological data sets

Overview of attention for article published in BMC Bioinformatics, February 2012

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In the top 25% of all research outputs scored by Altmetric
High Attention Score compared to outputs of the same age (83rd percentile)
Good Attention Score compared to outputs of the same age and source (73rd percentile)

So far, Altmetric has seen 13 X posts from 13 X users, with an upper bound of 41,803 followers.

Enrico Ferrero on Twitter: "Independent Principal Component Analysis combines the best of PCA and ICA: https://t.co/FcoNIT6xjR #bioinformatics" / Twitter https://t.co/F6JPKVjRx9

RT @enricoferrero: Independent Principal Component Analysis combines the best of PCA and ICA: https://t.co/O1I2teRtoN #bioinformatics

RT @enricoferrero: Independent Principal Component Analysis combines the best of PCA and ICA: https://t.co/O1I2teRtoN #bioinformatics

RT @enricoferrero: Independent Principal Component Analysis combines the best of PCA and ICA: https://t.co/O1I2teRtoN #bioinformatics

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