  In an effort to overcome the data deluge in computational biology and
bioinformatics and to facilitate bioinformatics research in the era of big
data, we identify some of the most influential algorithms that have been widely
used in the bioinformatics community. These top data mining and machine
learning algorithms cover classification, clustering, regression, graphical
model-based learning, and dimensionality reduction. The goal of this study is
to guide the focus of scalable computing experts in the endeavor of applying
new storage and scalable computation designs to bioinformatics algorithms that
merit their attention most, following the engineering maxim of "optimize the
common case".
