Cancer cells accumulate many genetic alterations throughout their lifetime, but only a few of
them drive cancer progression, termed driver mutations. Driver mutations may vary between …

Cancers are complex diseases orchestrated by a plethora of extrinsic and intrinsic factors.
Research spanning over several decades has provided better understanding of complex …

Abstract Machine learning is revolutionising medical image analysis, and clearly the future
of the field lies in this direction. However, with increasing automation there is a danger of …

Identifying the genes and mutations that drive the emergence of tumors is a critical step to
improving our understanding of cancer and identifying new directions for disease diagnosis …

Malignant tumors exhibit rapid growth and high metabolic rates, similar to embryonic stem
cells, and depend on aerobic glycolysis, known as the “Warburg effect”. This understanding …

Microarray data analysis needs utmost care as it plays a significant role in cancer study. Due
to the excessive complexity of the data extraction process, it loses some relevant information …

The vast amount of available sequencing data allows the scientific community to explore
different genetic alterations that may drive cancer or favor cancer progression. Software …

Variant interpretation remains a central challenge for precision medicine. Missense variants
are particularly difficult to understand as they change only a single amino acid in a protein …

Breast cancer (BC) is the most common malignancy affecting Western women today. It is
estimated that as many as 10% of BC cases can be attributed to germline variants. However …

Disrupted protein phosphorylation due to genetic variation is a widespread phenomenon
that triggers oncogenic transformation of healthy cells. However, few relevant …