Aly Azeem Khan

Research Assistant Professor
Principal Investigator, Laboratory for Computational Immunology
Department of Pathology, University of Chicago
Aly Khan

Contact Information

Department of Pathology
University of Chicago
Jules F. Knapp Medical Research Center (JFK)
924 E. 57th St., Office R-120
Chicago, IL 60637

email: aakhan@uchicago.edu
phone: 773.834.5905

Aly Khan

Research Overview

My research is at the interface between computer science and immunology. I am interested in developing novel computational methods to better understand how immune cells interact with each other, the surrounding tissue and organ systems, and the microbiome. While my group works on a wide range of problems in immunology, we typically choose problems with a specific kind of personality; we are interested in problems that are clinically relevant, amenable to machine learning, and allow for predictions that can be experimentally validated. Our goal is to draw out important domain insights from immunology and then harness these insights to architect new methods using information theory, optimization, and other machine learning techniques to make testable predictions about the immune system. This cross-disciplinary approach has enabled our research to have a broad and powerful impact in identifying new problems and methods in immunology that might otherwise have gone neglected.

Background

I obtained my Ph.D. from Cornell University, where I completed my graduate studies in computational biology in a joint program with Memorial Sloan Kettering Cancer Center under Christina Leslie (advisor), Alexander Rudensky and Chris Sander. I was a member of the research faculty at the Toyota Technological Institute at Chicago (TTIC) from 2014 to 2019, where I led an independent research program in computational immunology. I joined the Department of Pathology at the University of Chicago in 2019.

In addition to my academic research (disclosures), I have worked at Merck on computational algorithms to improve drug target discovery [1⇗] and collaborated with Genentech on computational methods for modeling immune regulatory networks ([2⇗], [3⇗], [4⇗] and [5⇗]). Since 2016, I have overseen the computational immunology program at Tempus Labs ([6⇗], [7⇗] and [8⇗]). In a past life, I took time off during my Ph.D. to work at Bank of America with Robert Almgren to study market impact and microstructure.

Selected Publications

B cell immunology

  • Pseudocell Tracer—A method for inferring dynamic trajectories using scRNAseq and its application to B cells undergoing immunoglobulin class switch recombination
    Reiman D, Manakkat Vijay GK, Xu H, Sonin A, Chen D, Salomonis N, Singh H, Khan AA.
    PLOS Computational Biology, 2021 May 3;17(5):e1008094.

  • Spec-seq unveils transcriptional subpopulations of antibody-secreting cells following influenza vaccination
    Neu K, Guthmiller JJ, Huang M, La J, Vieira M, Kim K, Zheng N, Cortese M, Tepora ME, Hamel NJ, Rojas KT, Henry C, Shaw DG, Dulberger CL, Pulendran B, Cobey S, Khan AA+, Wilson PC+.
    Data: GEO
    Journal of Clinical Investigation, 2019 Jan 2;129(1):93-105.

  • Single-Cell Genomics: Approaches and Utility in Immunology
    Neu KE, Tang Q, Wilson PC, Khan AA.
    Trends in Immunology, 2017 Feb;38(2):140-149.

Microbiome

  • Polymorphic immune mechanisms regulate commensal repertoire
    Khan AA, Yurkovetskiy L, O'Grady K, Pickard J, de Pooter R, Antonopoulos D, Golovkina T, Chervonsky A.
    Cell Reports, 2019 Oct 15;29(3):541-550.

  • Lactobacillus rhamnosus GG-supplemented formula expands butyrate-producing bacterial strains in food allergic infants
    Berni Canani R, Sangwan N, Stefka AT, Nocerino R, Paparo L, Aitoro R, Calignano A, Khan AA, Gilbert J, Nagler C.
    ISME, 2016 Mar;10(3):742-50.

  • Gender bias in autoimmunity is influenced by microbiota
    Yurkovetskiy L*, Burrows M*, Khan AA*, Graham L, Volchkov P, Becker L, Antonopoulos D, Umesaki Y, Chervonsky A.
    (*Equal Contribution)
    Immunity, 2013 Aug 22;39(2):400-12.

Transcriptional regulation

  • Transcriptional programming of dendritic cells for enhanced MHC class II antigen presentation
    Lugt BV, Khan AA, Hackney JA, Agrawal S, Lesch J, Zhou M, Lee WP, Park S, Xu M, DeVoss J, Spooner CJ, Chalouni C, Delamarre L, Mellman I, Singh H.
    Nature Immunology, 2014 Feb;15(2):161-7.

  • A genomic regulatory element that directs assembly and function of immune-specific AP-1-IRF complexes
    Glasmacher E, Agrawal S, Chang AB, Murphy TL, Zeng W, Vander Lugt B, Khan AA, Ciofani M, Spooner C, Rutz S, Hackney J, Nurieva R, Escalante CR, Ouyang W, Littman DR, Murphy KM, Singh H.
    Science, 2012 Nov 16;338(6109):975-80.

Post-transcriptional regulation

  • Excessive expression of miR-27 impairs Treg-mediated immunological tolerance
    Cruz LO, Hashemifar SS, Wu CJ, Cho S, Nguyen DT, Lin LL, Khan AA, Lu LF.
    Journal of Clinical Investigation, 2017 Feb 1;127(2):530-542.

  • Transcriptome-wide miR-155 binding map reveals widespread noncanonical microRNA targeting
    Loeb GB*, Khan AA*, Canner D, Hiatt JB, Shendure J, Darnell RB, Leslie CS, Rudensky AY.
    (*Equal Contribution)
    Server: CLIP-base
    Molecular Cell, 2012 Dec 14;48(5):760-70.

  • Transfection of small RNAs globally perturbs gene regulation by endogenous microRNAs
    Khan AA, Betel D, Miller ML, Sander C, Leslie CS, Marks DS.
    Nature Biotechnology, 2009 Jun;27(6):549-55.

For more recent publications, check Google Scholar.

Teaching

  • Readings: Immunobiology (IMMU 30800)‡, University of Chicago, Spring 2020.

  • Microbial 'Omics (BIOS 25420)†, University of Chicago, Spring 2020.

  • Quantitative Immunobiology (IMMU 34800)†, University of Chicago, Spring 2020.

  • Microbial 'Omics (BIOS 25420)†, University of Chicago, Spring 2019.

  • Introduction to Machine Learning†, Toyota Technological Institute, Nagoya - Japan, Spring 2018.

‡ Course Instructor; † Special Topics/Lectures

Random walk of ye olde websites


Aly Azeem Khan Aly Khan