Although machine learning-based approaches have achieved the highest results, some rule-based and hybrid systems [22, 33] showed highly competitive results during the BioCreative Challenge.
Chemical methods such as calcium-phosphate or liposome-based approaches have achieved much success for in vitro applications in cell cultures, but have been of more limited utility in vivo due to low transfection efficiencies and toxicity issues [ 16- 18].
Although these network-based approaches have achieved promising results, most of them can only predict binary DTIs, that is, they can only determine whether a drug interacts with a target protein, but cannot tell how they interact with each other.
Although previous network-based approaches have achieved promising results for DTI prediction and drug repositioning, few of them are specifically designed for integrating and predicting different types of DTIs on a multidimensional network.
Although different genetic based approaches have led to the accumulation of massive amounts of data, however, due to differential limitations of each study, limited success has been achieved in identifying common underlying genetic markers related to AD progression and pathogenesis.
This approach has achieved impressive results in the past, but today it is failing.
The crowdsourced approach has achieved mixed results in other countries.
And the SEC's new pattern-recognition analysis approach has achieved some early success.
These machine learning based methods have achieved promising predictive performances.
We set out to use a very lyrical approach to tell the story and based upon what we have been told by audiences, we have achieved this goal.
Through prodigious efforts and expert management, both sides have achieved remarkable success with their chosen approaches.
