Publications

January 2019. Predicting Short-term MCI-to-AD Progression Using Imaging, CSF, Genetic Factors, Cognitive Resilience, and Demographics

October 2018. LEMNA: Explaining Deep Learning based Security Applications

August 2018. Measuring the Mappability Spectrum of Reference Genome Assemblies

March 2018. METHCOMP: A Special Purpose Compression Platform for DNA Methylation Data

January 2018. Deep Learning for Better Variant Calling for Cancer Diagnosis and Treatment

December 2017. EEG-GRAPH: A Factor-Graph-Based Model for Capturing Spatial, Temporal, and Observational Relationships in Electroencephalograms, Poster by Yogatheesan Varatharajah.

November 2017.  METHCOMP: A Special Purpose Compression Platform for DNA Methylation Data

September 2017. Integrating Multi-Omics and Clinical Data to Predict SSRI Therapeutic Response in Adults with Major Depressive Disorder: A Data-Driven Machine Learning Approach.

May 2017. Prediction of Clinical Outcomes after SSRI Therapy for Major Depressive Disorder Using Clinical and Metabolomics Data: A Data-Driven Machine Learning Approach.

April 2017.  Model-based Unsupervised Learning to Establish Drug Mechanisms: A Case Study of Metformin’s Mechanisms in Triple-Negative Breast Cancer.

April 2017.  Data-Driven Longitudinal Modeling and Prediction of Symptom Dynamics in Major Depressive Disorder: Integrating Factor Graphs and Learning Methods.

April 2017.  Model-based Unsupervised Learning Informs Metformin-induced Cell-migration Inhibition Through an AMPK-independent Mechanism in Breast Cancer.