The biological data science is illustrated by a massive amount of data from heterogeneous sources from different cross domains in the field of life sciences. To translate complex relationships among heterogeneous datasets related to do structure and functions of biological systems remains an urgent challenge. Although traditional model-driven approaches still play an important role in analyzing these kinds of data, it lacks capabilities to exploit the huge amount of available data or even big data to discover knowledge, predict data behaviors, and decipher complex relationships among data.
