Aly Azeem Khan

Aly Khan

Contact Information

University of Chicago
Knapp Center for Biomedical Discovery (KCBD)
900 E. 57th St., Office 6118
Chicago, IL 60637

email: aakhan@uchicago.edu
phone: 773.834.5905

Aly Khan

Research Overview

My research program is at the interface between computer science and immunology. The primary focus of my lab is on developing novel computational methods to enhance our understanding of the complex interactions between immune cells, their environment, and the microbiome. Our goal is to uncover clinically relevant insights and pave the way for new diagnostics and therapies that can improve human health. While my lab tackles a diverse range of scientific problems, we specifically select those of a distinct nature. We are interested in problems that are clinically relevant, can be addressed using computational methods, and allow for experimentally verifiable predictions. A key theme in our research is the use of biology to guide the development of our computational methods. In this way, we incorporate biology from the outset to steer our computational work, rather than treating it as an afterthought. As a result, our research has had a broad and significant impact, 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. Between 2014 to 2019, I was a member of the research faculty at the Toyota Technological Institute at Chicago (TTIC), where I established a research program in computational immunology. In 2019, I moved to the Department of Pathology at the University of Chicago, and then joined the Department of Family Medicine and the College in 2022.

In addition to my academic research (disclosures), I have worked at Merck on computational methods to improve drug target discovery [1⇗] and collaborated with Genentech on modeling immune regulatory networks ([2⇗], [3⇗], [4⇗] and [5⇗]). Between 2016 to 2022, I founded and oversaw the immunology program at Tempus Labs ([6⇗], [7⇗], [8⇗] and [9⇗]), which included clinical diagnostics and biomarker discovery. Since 2022, I have been advising and overseeing efforts in machine learning and computational biology at 23andMe. In a past life, I took time off during my Ph.D. to work at Bank of America under Robert Almgren to study market impact and microstructure.

Selected Publications

B cell genomics at single cell resolution

  • 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.

  • BASIC: BCR assembly from single cells
    Canzar S, Neu KE, Tang Q, Wilson PC, Khan AA.
    Bioinformatics, 2017 Feb 1;33(3):425-427.

  • 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.

Precision cancer immunotherapy

  • Integration of tumor extrinsic and intrinsic features associates with immunotherapy response in non-small cell lung cancer
    Lau D, Khare S, Stein MM, Jain P, Gao Y, Ben-Taib A, Rand TA, Salahudeen A, Khan AA.
    Nature Communications, 2022 Jul 13;13(1):4053.

  • Integrating RNA expression and visual features for immune infiltrate prediction
    Reiman D, Sha L, Ho I, Tan T, Lau D, Khan AA.
    PSB 2019, 2019;24:284-295.

  • RNA Sequencing of the Tumor Microenvironment in Precision Cancer Immunotherapy
    Lau D, Bobe AM, Khan AA.
    Trends in Cancer, 2019 Mar;5(3):149-156.

Humoral immune response

  • 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.

  • Neutralizing Antibody Responses to Viral Infections Are Linked to the Non-classical MHC Class II Gene H2-Ob
    Denzin LK, Khan AA, Virdis F, Wilks J, Kane M, Beilinson HA, Dikiy S, Case LK, Roopenian D, Witkowski M, Chervonsky AV, Golovkina TV.
    Immunity, 2017 Aug 15;47(2):310-322.e7.

Immune-microbe interactions

  • 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.

Protein-protein interactions

  • Deploying synthetic coevolution and machine learning to engineer protein-protein interactions
    Yang A, Jude KM, Lai B, Minot M, Kocyla AM, Glassman CR, Nishimiya D, Kim YS, Reddy ST, Khan AA, Garcia KC.
    Science, 2023 Jul 28;381(6656):eadh1720.

  • Predicting protein-protein interactions through sequence-based deep learning
    Hashemifar S, Neyshabur B, Khan AA, Xu J.
    Bioinformatics, 2018 Sep 1;34(17):i802-i810.

Machine learning

For more recent publications, check Google Scholar.

Laboratory for Computational Immunology

Our lab combines genomics, machine learning, and computational biology to investigate the immune system. Our long-term goal is to uncover clinically relevant insights and pave the way for new diagnostics and therapies to enhance human health. Key areas of interest include: (1) Single-Cell and Spatial Immunology: How can we utilize single-cell and spatial technologies to better understand B and T cell functions? (2) Precision Immunotherapy: What factors influence variable responses to cancer immunotherapies and the appearance of immune-related adverse events? (3) Drug and Therapeutic Development: How can we design immune-modulatory drugs better? (4) Systems Immunology: How can we improve the accuracy and interpretability of predictive models through the integration of existing immune knowledge?

Group and Affiliated Members

  • Derek Reiman, PhD - (Research Assistant Professor, TTIC)
  • Phillip Lo - (PhD candidate, Applied Mathematics)
  • Renyu Zhang - (PhD candidate, Computer Science)
  • Hugh Yeh - (MD/PhD candidate, Molecular Engineering)
  • Steven Song - (MD/PhD candidate, Computer Science)
Alumni
  • TBD

Dissertation committees

  • Xiao Luo - (PhD candidate, TTIC)
  • Ziwei Xie - (PhD candidate, TTIC)
  • Randy Melanson - (MD/PhD candidate, Immunology)
  • Ben Lai - (PhD candidate, TTIC)
  • Sudarshan Babu - (PhD candidate, TTIC)
  • Veronica Locher - (PhD candidate, Immunology)
Alumni
  • Augusta Broughton, PhD - (Immunology)
  • Xuan Hui, PhD - (Public Health)
  • Emily Higgs, PhD - (MD/PhD candidate)
  • Linda Lan, PhD - (Immunology)
  • Yuta Asano, PhD - (Immunology)
  • Karlynn Neu, PhD - (Immunology)

Joining the lab

Current graduate students who are interested in computational biology and immunology are highly encouraged to reach out. Our lab is associated with the following graduate training programs: Genomics, Genetics, and Systems Biology; Immunology; and Cancer Biology. We're also affiliated with the UChicago Comprehensive Cancer Center and Toyota Technological Institute at Chicago. We are particularly interested in students who wish to be co-mentored with another lab, especially if their interests involve developing and applying novel machine learning methods to immunology or pursuing complementary wet-lab experiments. I am also happy to work with students as a member of their disseration committee, especially if the research aligns with our lab's interests and may benefit from new computational methods.

Prospective graduate students should consider applying to any of the aforementioned programs, making sure to mention our lab in their applications. Postdoctoral candidates with strong interest in computational biology and immunology are also highly encouraged to reach out.

Teaching

  • Principles of Precision Health (MSPH 34000)†, University of Chicago, Winter 2024.

  • Computational Systems Biology (MSPH 44000)‡, University of Chicago, Spring 2023.

  • BSD Quantitative Biology Bootcamp (Immunology Section)‡, University of Chicago, Summer 2022.

  • BSD Quantitative Biology Bootcamp (Immunology Section)‡, University of Chicago, Summer 2021.

  • 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 Khan Aly Khan