Despite considerable progress in genome-and proteome-based high-throughput screening
methods and in rational drug design, the increase in approved drugs in the past decade did …

Drug discovery and development is a complex and costly process. Machine learning
approaches are being investigated to help improve the effectiveness and speed of multiple …

This book is an impressive survey of our collective and cumulative understanding of the
evolution of digital communication systems and the Internet. Whilst the information societies …

Owning to the rapid development of computer technologies, an increasing number of
relational data have been emerging in modern biomedical research. Many network-based …

Background Recently there has been an explosion of new data sources about genes,
proteins, genetic variations, chemical compounds, diseases and drugs. Integration of these …

We are all perplexed that current medical practice often appears maladroit in curing our
individual illnesses or disease. However, as is often the case, a lack of understanding, tools …

Advances in high-throughput experimental technologies promote the accumulation of vast
number of biomedical data. Biomedical link prediction and single-cell RNA-sequencing …

Recent advances in biomedical research have generated a large volume of drug-related
data. To effectively handle this flood of data, many initiatives have been taken to help …

Integrative Biology (IB) uses experimental or computational quantitative technologies to
characterize biological systems at the molecular, cellular, tissue and population levels. IB …

During the past several decades, the understanding of cancer at the molecular level has
been primarily focused on mechanisms on how signaling molecules transform …