The influence of feature selection methods on accuracy, stability and interpretability of molecular signatures
Biomarker discovery from high-dimensional data is a crucial problem with enormous
applications in biology and medicine. It is also extremely challenging from a statistical …
applications in biology and medicine. It is also extremely challenging from a statistical …
Integrating feature selection and feature extraction methods with deep learning to predict clinical outcome of breast cancer
In many microarray studies, classifiers have been constructed based on gene signatures to
predict clinical outcomes for various cancer sufferers. However, signatures originating from …
predict clinical outcomes for various cancer sufferers. However, signatures originating from …
Network biomarkers reveal dysfunctional gene regulations during disease progression
Extensive studies have been conducted on gene biomarkers by exploring the increasingly
accumulated gene expression and sequence data generated from high‐throughput …
accumulated gene expression and sequence data generated from high‐throughput …
Knowledge boosting: a graph-based integration approach with multi-omics data and genomic knowledge for cancer clinical outcome prediction
Objective Cancer can involve gene dysregulation via multiple mechanisms, so no single
level of genomic data fully elucidates tumor behavior due to the presence of numerous …
level of genomic data fully elucidates tumor behavior due to the presence of numerous …
Mitotic spindle assembly and genomic stability in breast cancer require PI3K-C2α scaffolding function
Proper organization of the mitotic spindle is key to genetic stability, but molecular
components of inter-microtubule bridges that crosslink kinetochore fibers (K-fibers) are still …
components of inter-microtubule bridges that crosslink kinetochore fibers (K-fibers) are still …
Mitch: Multi-contrast pathway enrichment for multi-omics and single-cell profiling data
Background Inference of biological pathway activity via gene set enrichment analysis is
frequently used in the interpretation of clinical and other omics data. With the proliferation of …
frequently used in the interpretation of clinical and other omics data. With the proliferation of …
Edge biomarkers for classification and prediction of phenotypes
In general, a disease manifests not from malfunction of individual molecules but from failure
of the relevant system or network, which can be considered as a set of interactions or edges …
of the relevant system or network, which can be considered as a set of interactions or edges …
[HTML][HTML] Using hidden Markov model to predict recurrence of breast cancer based on sequential patterns in gene expression profiles
A new approach is presented to predict breast cancer recurrence through gene expression
profiles using hidden Markov models (HMM). In this regard, 322 genes were selected from …
profiles using hidden Markov models (HMM). In this regard, 322 genes were selected from …
A novel model to combine clinical and pathway-based transcriptomic information for the prognosis prediction of breast cancer
Breast cancer is the most common malignancy in women worldwide. With the increasing
awareness of heterogeneity in breast cancers, better prediction of breast cancer prognosis is …
awareness of heterogeneity in breast cancers, better prediction of breast cancer prognosis is …
Single sample expression-anchored mechanisms predict survival in head and neck cancer
Gene expression signatures that are predictive of therapeutic response or prognosis are
increasingly useful in clinical care; however, mechanistic (and intuitive) interpretation of …
increasingly useful in clinical care; however, mechanistic (and intuitive) interpretation of …