Recently, using artificial intelligence (AI) in drug discovery has received much attention
since it significantly shortens the time and cost of developing new drugs. Deep learning (DL) …

As a data-driven science, genomics largely utilizes machine learning to capture
dependencies in data and derive novel biological hypotheses. However, the ability to extract …

Deep learning describes a class of machine learning algorithms that are capable of
combining raw inputs into layers of intermediate features. These algorithms have recently …

In the era of big data, transformation of biomedical big data into valuable knowledge has
been one of the most important challenges in bioinformatics. Deep learning has advanced …

Over the past decade, polypharmacy instances have been common in multi-diseases
treatment. However, unwanted drug-drug interactions (DDIs) that might cause unexpected …

Increases in throughput and installed base of biomedical research equipment led to a
massive accumulation of-omics data known to be highly variable, high-dimensional, and …

It is critical, but difficult, to catch the small variation in genomic or other kinds of data that
differentiates phenotypes or categories. A plethora of data is available, but the information …

Over the past decade we have witnessed the increasing sophistication of machine learning
algorithms applied in daily use from internet searches, voice recognition, social network …

Omics, such as genomics, transcriptome and proteomics, has been affected by the era of big
data. A huge amount of high dimensional and complex structured data has made it no …

12. Assisted Human Reproduction Act, SC 2004. http://laws-lois. justice. gc. ca/PDF/A-13.4.
pdf (2018) 13. CNN. Rael defends claims of cloned baby. http://www. cnn. com/2003 …