By Karen
Dr. Fragiadakis’s research focuses on analyzing immune state in diverse sets of patient cohorts using high-dimensional single-cell technologies, including single-cell sequencing and CyTOF. She uses multi-modal data integration methods to evaluate patient differences and infer broader principles of immune organization.
By Karen
We focus on understanding how the immune system coordinates responses with an emphasis on tumor immunology. We combine experimental and computational methods to understand how the immune system responds to tumors and to rationally initiate curative immune responses against cancer.
By Karen
Dr. Ushizima research focuses on computer vision algorithms for monitoring diseases progression while exploring information from multiple imaging techniques. Together with Grinberg’s lab, developed quantitative histological analysis of whole human brains using multiple instruments.
By Karen
The Abbasi Lab aims to understand functions of the brain and related disorders by leveraging principles in machine learning and statistics. The lab studies large-scale single-cell level neurophysiological datasets as well as medical images and structured and unstructured healthcare data.
By Karen
The main theme of our research is large-scale analysis of disease genomes by integrating multi-omics data, evolutionary insights, electronic health records, as well as digitized clinical traits from imaging and wearable sensor readouts. The ultimate goal is to build data-driven frameworks to detect diseases before symptoms emerge and to achieve precision health management.
By Karen
Ramani Lab invents molecular tools to study biology, e.g. devising ways to molecularly tag nucleic acids and proteins with unique genomic or proteomic identifiers, then using these to quantify biological phenomena at the level of single cells and single molecules, using high-throughput sequencing and cutting-edge mass spectrometric techniques.
By Karen
Dr Baranzini’s current research involves immunological studies using the EAE model, sequencing of whole genomes and transcriptomes from patients with multiple sclerosis and developing bioinformatics tools to integrate this information with that coming from other high throughput technologies. Dr Baranzini uses a combination of “wet lab” methods including DNA microarrays, proteomics, and laser capture microdissection, in combination with “dry lab” analytical approaches encompassing bioinformatics, complexity theory, and mathematical modeling.
By Karen
The lab seeks to discover new therapeutic approaches to target the genetic mutations and altered signaling networks that are specific to cancer cells. Using functional genomics applied to mouse and human systems, we work to understand the transcriptional networks that regulate the outcome of specific oncogenic mutations and to understand how cancers become resistant to chemotherapy. This work relies heavily on computational genomic analysis, generating and using high-throughput datasets and next-generation sequencing for gene and network discovery. Our primary disease focus is lung cancer and pediatric sarcomas.
By Karen
The Jain lab focuses on computational chemistry and computational biology. The primary research areas are in structure-based drug discovery, rational approaches for predictive pharmacology, and applications involved in cancer. Researchers at academic and non-profit institutions are encouraged to download and make use of our software.
By Karen
The Shoichet lab seeks to bring chemical reagents to biology, combining computation and experiment. In a protein-centric approach, molecular docking, they discover new ligands that complement protein structures. Using a ligand-centric approach, they discover new targets for known drugs and reagents.
By Karen
Recognizing that the elements of life are at angstrom-scale, the Douglas lab aims to create the computational building blocks for a new generation of therapies and devices.
By Karen
The Sirota lab develops incremental computational methods in the context of disease diagnostics and therapeutics – especially leveraging ‘omics and clinical data to better understand the role of the immune system.
By Karen
The Altschuler-Wu lab investigates fundamental questions about the origins and impact of cellular heterogeneity in collective cellular decision making, tissue development and homeostasis. Results from our studies are applied to investigate mechanisms of drug resistance, cancer evolution and new therapeutic strategies. A common theme is the combined use of single-cell perturbation assays, quantitative imaging, data-driven modeling and theory.
