Big data in public health: terminology, machine learning, and privacy
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 …
data” have unlocked novel opportunities to understand public health, they hold still greater …
Genome interpretation using in silico predictors of variant impact
Estimating the effects of variants found in disease driver genes opens the door to
personalized therapeutic opportunities. Clinical associations and laboratory experiments …
personalized therapeutic opportunities. Clinical associations and laboratory experiments …
Calibration of computational tools for missense variant pathogenicity classification and ClinGen recommendations for PP3/BP4 criteria
Summary Recommendations from the American College of Medical Genetics and Genomics
and the Association for Molecular Pathology (ACMG/AMP) for interpreting sequence variants …
and the Association for Molecular Pathology (ACMG/AMP) for interpreting sequence variants …
Updated benchmarking of variant effect predictors using deep mutational scanning
The assessment of variant effect predictor (VEP) performance is fraught with biases
introduced by benchmarking against clinical observations. In this study, building on our …
introduced by benchmarking against clinical observations. In this study, building on our …
Functional EPAS1/HIF2A missense variant is associated with hematocrit in Andean highlanders
Hypoxia-inducible factor pathway genes are linked to adaptation in both human and
nonhuman highland species. EPAS1, a notable target of hypoxia adaptation, is associated …
nonhuman highland species. EPAS1, a notable target of hypoxia adaptation, is associated …
Unsupervised and semi‐supervised learning: The next frontier in machine learning for plant systems biology
J Yan, X Wang - The Plant Journal, 2022 - Wiley Online Library
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 …
era of big data. Machine learning (ML) performs an important role in plant systems biology …
MetaRNN: differentiating rare pathogenic and rare benign missense SNVs and InDels using deep learning
Multiple computational approaches have been developed to improve our understanding of
genetic variants. However, their ability to identify rare pathogenic variants from rare benign …
genetic variants. However, their ability to identify rare pathogenic variants from rare benign …
How chromosomal inversions reorient the evolutionary process
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 …
and reduce the effective rate of recombination in the heterozygous state. They play a major …
Positive-unlabeled learning in bioinformatics and computational biology: a brief review
Conventional supervised binary classification algorithms have been widely applied to
address significant research questions using biological and biomedical data. This …
address significant research questions using biological and biomedical data. This …
Interpreting protein variant effects with computational predictors and deep mutational scanning
Computational predictors of genetic variant effect have advanced rapidly in recent years.
These programs provide clinical and research laboratories with a rapid and scalable method …
These programs provide clinical and research laboratories with a rapid and scalable method …