Abstract Background The Critical Assessment of Genome Interpretation (CAGI) aims to
advance the state-of-the-art for computational prediction of genetic variant impact …

The digital world is generating data at a staggering and still increasing rate. While these “big
data” have unlocked novel opportunities to understand public health, they hold still greater …

Summary Recommendations from the American College of Medical Genetics and Genomics
and the Association for Molecular Pathology (ACMG/AMP) for interpreting sequence variants …

The assessment of variant effect predictor (VEP) performance is fraught with biases
introduced by benchmarking against clinical observations. In this study, building on our …

Inversions are structural mutations that reverse the sequence of a chromosome segment
and reduce the effective rate of recombination in the heterozygous state. They play a major …

Multiple computational approaches have been developed to improve our understanding of
genetic variants. However, their ability to identify rare pathogenic variants from rare benign …

Advances in high‐throughput omics technologies are leading plant biology research into the
era of big data. Machine learning (ML) performs an important role in plant systems biology …

Molecular biology is currently a fast-advancing science. Sequencing techniques are getting
cheaper, but the interpretation of genetic variants requires expertise and computational …

Estimating the effects of variants found in disease driver genes opens the door to
personalized therapeutic opportunities. Clinical associations and laboratory experiments …

Conventional supervised binary classification algorithms have been widely applied to
address significant research questions using biological and biomedical data. This …