The reproducibility of experiments has been a long standing impediment for further scientific
progress. Computational methods have been instrumental in drug discovery efforts owing to …

Neurodegenerative diseases, characterized by a progressive loss of brain function, affect
the lives of millions of individuals worldwide. The complexity of the brain poses a challenge …

Computational modelling has become increasingly common in life science research. To
provide a platform to support universal sharing, easy accessibility and model reproducibility …

The future development of personalized medicine depends on a vast exchange of data from
different sources, as well as harmonized integrative analysis of large-scale clinical health …

New technologies are revolutionising biological research and its applications by making it
easier and cheaper to generate ever-greater volumes and types of data. In response, the …

Recent growth in annual new therapeutic entity (NTE) approvals by the US Food and Drug
Administration (FDA) suggests a positive trend in current research and development (R&D) …

The lack of standardization in the way that quantitative and systems pharmacology (QSP)
models are developed, tested, and documented hinders their reproducibility, reusability, and …

Systems pharmacology aims to holistically understand mechanisms of drug actions to
support drug discovery and clinical practice. Systems pharmacology modeling (SPM) is data …

Objective: Only reproducible results are of significance to science. The lack of suitable
standards and appropriate support of standards in software tools has led to numerous …

Reconstructing and understanding the Human Physiome virtually is a complex mathematical
problem, and a highly demanding computational challenge. Mathematical models spanning …