Research & Activities


We are passionate about developing new algorithms, machine learning and deep learning methods, and their applications to genomics, metagenomics and cancer research. Some of the current projects in the lab include characterizing human genomes and metagenomes using multiple sequencing platforms, quantifying cancer evolution, study of tumor heterogeneity using genomics and imaging, and AI in In Vitro Fertilization (IVF).

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Structural Variation

Developing algorithms for characterizing structural variations focused on complex and repetitive elements, rare variants and clinical relevant variants.

Tumor Heterogeneity

Quantifying cancer evolution in multiple samples and reconstruction of tumor lineage trees using novel computational methods. Also, building deep learning based classifiers to discriminate heterogeneous sample, using imaging data.

Metagenomics

Advancing computational methods in metagenomics for the purpose of deconvolving mixtures, discovering variants and de novo assembly.


Recent Publications


See Iman Hajirasouliha's Google Scholar page for an updated list.


Copyright © 2016 Iman Hajirasouliha.