What Can Networks Do for You

This chapter aims at demonstrating the utility of network approaches in classification and outlier detection tasks in the context of stem cell biology and related fields. With modern high-through-put methods it has now become easier and cheaper to accurately measure thousands of features on a genome-wide scale than to define a low number of markers that can be tested, for example with low throughput RT-PCR assays. Typically the number of potential markers exceeds the number of experiments by several orders of magnitude. Therefore the significance – let alone mechanistic involvement – of each possible feature cannot be guaranteed from the data alone. Fortunately, easy-to-use implementations of many powerful network based algorithms have been made freely available so one can readily employ these advanced algorithms on new high-content datasets.

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