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Glioblastoma

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Deep Integrative Analysis for Survival Prediction.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Survival prediction is very important in medical treatment. However, recent leading research is challenged by two factors: 1) the datasets usually come with multi-modality; and 2) sample sizes are relatively small. To solve the above challenges, we d...

MRI to MGMT: predicting methylation status in glioblastoma patients using convolutional recurrent neural networks.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Glioblastoma Multiforme (GBM), a malignant brain tumor, is among the most lethal of all cancers. Temozolomide is the primary chemotherapy treatment for patients diagnosed with GBM. The methylation status of the promoter or the enhancer regions of the...

Differentiation of Glioblastoma and Lymphoma Using Feature Extraction and Support Vector Machine.

CNS & neurological disorders drug targets
Differentiation of glioblastoma multiformes (GBMs) and lymphomas using multi-sequence magnetic resonance imaging (MRI) is an important task that is valuable for treatment planning. However, this task is a challenge because GBMs and lymphomas may have...

KNOWLEDGE-ASSISTED APPROACH TO IDENTIFY PATHWAYS WITH DIFFERENTIAL DEPENDENCIES.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
We have previously developed a statistical method to identify gene sets enriched with condition-specific genetic dependencies. The method constructs gene dependency networks from bootstrapped samples in one condition and computes the divergence betwe...