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Genome, Human

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Prediction of inherited genomic susceptibility to 20 common cancer types by a supervised machine-learning method.

Proceedings of the National Academy of Sciences of the United States of America
Prevention and early intervention are the most effective ways of avoiding or minimizing psychological, physical, and financial suffering from cancer. However, such proactive action requires the ability to predict the individual's susceptibility to ca...

Supervised Machine Learning for Population Genetics: A New Paradigm.

Trends in genetics : TIG
As population genomic datasets grow in size, researchers are faced with the daunting task of making sense of a flood of information. To keep pace with this explosion of data, computational methodologies for population genetic inference are rapidly be...

Classifying cancer genome aberrations by their mutually exclusive effects on transcription.

BMC medical genomics
BACKGROUND: Malignant tumors are typically caused by a conglomeration of genomic aberrations-including point mutations, small insertions, small deletions, and large copy-number variations. In some cases, specific chemotherapies and targeted drug trea...

Predicting human splicing branchpoints by combining sequence-derived features and multi-label learning methods.

BMC bioinformatics
BACKGROUND: Alternative splicing is the critical process in a single gene coding, which removes introns and joins exons, and splicing branchpoints are indicators for the alternative splicing. Wet experiments have identified a great number of human sp...

Predicting enhancers with deep convolutional neural networks.

BMC bioinformatics
BACKGROUND: With the rapid development of deep sequencing techniques in the recent years, enhancers have been systematically identified in such projects as FANTOM and ENCODE, forming genome-wide landscapes in a series of human cell lines. Nevertheles...

Network-based analysis of diagnosis progression patterns using claims data.

Scientific reports
In recent years, several network models have been introduced to elucidate the relationships between diseases. However, important risk factors that contribute to many human diseases, such as age, gender and prior diagnoses, have not been considered in...

Machine learning model for sequence-driven DNA G-quadruplex formation.

Scientific reports
We describe a sequence-based computational model to predict DNA G-quadruplex (G4) formation. The model was developed using large-scale machine learning from an extensive experimental G4-formation dataset, recently obtained for the human genome via G4...

De novo prediction of human chromosome structures: Epigenetic marking patterns encode genome architecture.

Proceedings of the National Academy of Sciences of the United States of America
Inside the cell nucleus, genomes fold into organized structures that are characteristic of cell type. Here, we show that this chromatin architecture can be predicted de novo using epigenetic data derived from chromatin immunoprecipitation-sequencing ...

Who's Who? Detecting and Resolving Sample Anomalies in Human DNA Sequencing Studies with Peddy.

American journal of human genetics
The potential for genetic discovery in human DNA sequencing studies is greatly diminished if DNA samples from a cohort are mislabeled, swapped, or contaminated or if they include unintended individuals. Unfortunately, the potential for such errors is...