Network pharmacology is an emerging area of systematic drug research that attempts to
understand drug actions and interactions with multiple targets. Network pharmacology has …

Recent advancements in experimental high-throughput technologies have expanded the
availability and quantity of molecular data in biology. Given the importance of interactions in …

New technologies are transforming medicine, and this revolution starts with data. Health
data, clinical images, genome sequences, data on prescribed therapies and results …

Enzyme catalysts are an integral part of green chemistry strategies towards a more
sustainable and resource-efficient chemical synthesis. However, the use of biocatalysed …

Metabolic engineering encompasses several widely-used strategies, which currently hold a
high seat in the field of biotechnology when its potential is manifesting through a plethora of …

The exponential growth of biomedical data in recent years has urged the application of
numerous machine learning techniques to address emerging problems in biology and …

Physiologically based pharmacokinetic (PBPK) models are useful tools in drug development
and risk assessment of environmental chemicals. PBPK model development requires the …

Deep learning (DL), an emerging area of investigation in the fields of machine learning and
artificial intelligence, has markedly advanced over the past years. DL techniques are being …

Chemists have to a large extent gained their knowledge by doing experiments and thus
gather data. By putting various data together and then analyzing them, chemists have …

Nowadays, machine learning (ML) has attained a high level of achievement in many
contexts. Considering the significance of ML in medical and bioinformatics owing to its …