Jennifer Listgarten

Jennifer Listgarten


  • Mailing address:
    University of California, Berkeley
    Electrical Engineering and Computer Science
    387 Soda Hall, MC 1776
    Berkeley, CA, 94720

  • Before contacting me, students please read this.
  • jennl [at] berkeley.edu

About me

I am a Professor in UC Berkeley's EECS department , Center for Computational Biology, Bioengineering, and a member of the steering committee for the Berkeley AI Research (BAIR) Lab. From 2007 to 2017 I was at Microsoft Research, through Cambridge, MA, Los Angeles and Redmond, WA. Before that I did my PhD in the machine learning group at the University of Toronto. (Feel free to use this short bio and picture for announcements.)

My expertise is in machine learning, applied statistics, computational biology. I'm interested in both methods development as well as application of methods to enable new insight into basic biology and medicine. Recently I have also started to work on computational chemistry. A recent print interview focused on my CRISPR work can be found here. If you're interested more generally in how machine learning and biology go together, check out this Talking Machines interview with me instead (alternate link to audio here). Finally, if you want to hear about my random walk in education & career space, take a look at this Berkeley Science Review profile.

Current areas of interest include: computational methods for protein design/optimization/engineering for properties such as expression, flurorescence, binding, stability, etc.; related methods for molecule design and chemical reactions; drug repositioning and discovery; machine learning methods development, and in particular at the intersection of graphical models, neural networks and variational inference, as well as optimizing black box probablistic functions with pathological regions that can't be trusted.

Previous focus areas include: machine learning methods for time series alignment and normalization; LC-MS proteomics; statistical genetics methods to correct for confounding factors in GWAS, epigenome-WAS and eQTL studies; problems in immunoinformatics such as HLA class I epitope prediction and HLA allele imputation. If you're interested in my statistical genetics work (FaST-LMM or EWASher), please go to this landing page.

Industry engagements: I also spend some of my time with companies. At the moment, these:

  • Dayzero Diagnostics (Scientific Advisory Board).
  • Deep Apple Therapeutics (Scientific Advisory Board).
  • Inscripta (Scientific Advisory Board).
  • Fable Therapeutics (Academic co-founder).

    • Research group

    Announcements

    New and upcoming papers


    Generative models for protein structures and sequences

    Chloe Hsu, Clara Fannjiang, Jennifer Listgarten
    Nature Biotechnology 2024 (link) and a freely available copy here.

    The perpetual motion machine of AI-generated data and the distraction of "ChatGPT as scientist"

    Jennifer Listgarten
    Nature Biotechnology 2024 (link) and a freely available version here, and a talk at the 2024 National Academy of Sciences annual meeting.

    Coherent Blending of Biophysics-Based Knowledge with Bayesian Neural Networks for Robust Protein Property Prediction

    Hunter Nisonoff, Yixin Wang, Jennifer Listgarten
    ACS Synth. Biol. 2023 (Editor's Choice)   (paper link)

    Optimal trade-off control in machine learning-based library design, with application to adeno-associated virus (AAV) for gene therapy

    D Zhu*, DH Brookes*, A Busia*, A Carneiro, C Fannjiang, G Popova, D Shin, KC Donohue,, LF Lin, ZM Miller, ER Williams, EF Chang, TJ Nowakowski, J Listgarten*, DV Schaffer* (*equal contributions, corresponding)
    Science Advances 2024 (paper link)

    Is novelty predictable?

    Clara Fannjiang and Jennifer Listgarten
    Cold Spring Harbor Perspectives in Biology 2023 (paper link), similar version also available on arXiv).

    MBE: model-based enrichment estimation and prediction for differential sequencing data

    Akosua Busia and Jennifer Listgarten
    Genome Research 2023   (paper link)
    Do you estimate/predict log enrichment scores from sequencing data? Do you want greater statistical power? Or do you want an easy way to combine all kinds of short and long reads? Check out our pre-print.

    CS 294-150 Machine Learning and Statistics Meet Biology (Spring 2023)


    If you have questions about enrolling in this class, or otherwise, please read the bcourses web page, noting the year in case it's out of date. This site also contains a link for those unable to automatically enroll to fill out an application to enroll---please make sure only to fill out for the correct year (and please email me if the semester is about to start and it hasn't been updated).

    Selected
    Publications

    The perpetual motion machine of AI-generated data and the distraction of "ChatGPT as scientist"

    Jennifer Listgarten
    Nature Biotechnology 2024(link) and a freely available version here, and a talk at the 2024 National Academy of Sciences annual meeting.

    Is novelty predictable?

    Clara Fannjiang and Jennifer Listgarten
    Cold Spring Harbor Perspectives in Biology 2023 (paper link), similar version also available on arXiv).

    MBE: model-based enrichment estimation and prediction for differential sequencing data

    Akosua Busia and Jennifer Listgarten
    Genome Research 2023   (paper link)

    Optimal trade-off control in machine learning-based library design, with application to adeno-associated virus (AAV) for gene therapy

    D Zhu*, DH Brookes*, A Busia*, A Carneiro, C Fannjiang, G Popova, D Shin, KC Donohue,, LF Lin, ZM Miller, ER Williams, EF Chang, TJ Nowakowski, J Listgarten*, DV Schaffer* (*equal contributions, corresponding)
    Science Advances 2024 (paper link)

    Learning protein fitness models from evolutionary and assay-labeled data

    Chloe Hsu, Hunter Nisonoff, Clara Fannjiang, Jennifer Listgarten
    Nature Biotechnology 2022   (paper)

    Rethinking drug design in the artificial intelligence era

    P Schneider, WP Walters, AT Plowright, N Sieroka, J Listgarten, RA Goodnow Jr., J Fisher, JM Jansen, JS Duca, TS Rush, M Zentgraf, JE Hill, E Krutoholow, M Kohler, J Blaney, K Funatsu, C Luebkemann and G Schneider
    in Nature Reviews Drug Discovery  2019 (paper link)

    Conditioning by adaptive sampling for robust design

    David H. Brookes, Hahnbeom Park and Jennifer Listgarten
    accepted at ICML  2019 (paper link, arXiv version is most up-to-date)
    (5% acceptance rate for 20 min. oral presentation)

    Predicting off-target effects for end-to-end CRISPR guide design

    J Listgarten, M Weinstein, B Kleinstiver, AA Sousa, JK Joung, J Crawford, K Gao, M Elibol, L Hoang, J Doench, N Fusi (equal contributions and corresponding)
    Nature Biomedical Engineering  (2018) (paper link)
    Associated tools and resources available here.

    Orthologous CRISPR-Cas9 for Combinatorial Genetic Screens

    F Najm*, C Strand*, K Donovan*, M Hegde*, KR. Sanson*, EW Vaimberg, ME Sullender, E Hartenian, N Fusi, J. Listgarten, ST Younger*, BE Bernstein**, DE Root**, JG Doench**
    Nature Biotechnology  (2018) (paper link) (*equal contributions, **corresponding)

    Optimized sgRNA design to maximize activity and minimize off-target effects for genetic screens with CRISPR-Cas9

    JG Doench*, N Fusi*, M Sullender*, M Hegde*, EW Vaimberg*, KF Donovan, I Smith, Z Tothova, C Wilen , R Orchard , HW Virgin, J Listgarten*, DE Root
    Nature Biotechnology   2016 doi:10.1038/nbt.3437
    (*equal contributions, corresponding)
    A pre-print of just the computational aspects of this paper is available on bioRxiv
    Source code and prediction server available from here: here.
    [Microsoft Research blog post]
    [Broad Institute blog post]

    Epigenome-wide association studies without the need for cell-type composition

    James Zou, C. Lippert, D. Heckerman, Martin Aryee, Jennifer Listgarten
    Nature Methods   2014 (journal link)
    Python software available from here, and R software available from here.
    Corrigendum: Supp. Figure 1 was not run with filters as described in the paper, but without any filters. We have contacted the journal to post this correction.

    FaST-LMM-Select for addressing confounding from spatial structure and rare variants

    Jennifer Listgarten, Christoph Lippert, David Heckerman (equal contributions and corresponding)
    Nature Genetics   2013 (journal link)

    Improved linear mixed models for genome-wide association studies

    Jennifer Listgarten, C. Lippert, C. Kadie, R. Davidson, E. Eskin and D. Heckerman
    (equal contributions and corresponding)
    Nature Methods   2012, doi:10.1038/nmeth.2037
    Source and executables available here.

    Statistical resolution of ambiguous HLA typing data

    Jennifer Listgarten, Z. Brumme, C. Kadie, G. Xiaojiang, B. Walker, M. Carrington, P. Goulder, D. Heckerman,
    in PLoS Computational Biology   2008, 4(2):e1000016
    (abstract, paper, coverage in the magazine BioInform, press release) For the public web server tool based on this work, go here ; for .exe and source code (training code not included), go here.

    Bayesian detection of infrequent differences in sets of time series with shared structure.

    Jennifer Listgarten, Radford M. Neal, Sam T. Roweis, Rachel Puckrin and Sean Cutler,
    NIPS   2006
    Best Student Paper, Honorable Mention. (abstract, paper)

    Statistical and computational methods for comparative proteomic profiling using liquid chromatography-tandem mass spectrometry.

    Jennifer Listgarten and Andrew Emili,
    Molecular and Cellular Proteomics   2005 4:419-434. (abstract) (paper)

    All Publications

    Generative models for protein structures and sequences

    Chloe Hsu, Clara Fannjiang, Jennifer Listgarten
    Nature Biotechnology 2024 (link) and a freely available copy here.

    The perpetual motion machine of AI-generated data and the distraction of "ChatGPT as scientist"

    Jennifer Listgarten
    Nature Biotechnology 2024 (link) and a freely available version here, and a talk at the 2024 National Academy of Sciences annual meeting.

    Is novelty predictable?

    Clara Fannjiang and Jennifer Listgarten
    Cold Spring Harbor Perspectives in Biology 2023 (paper link), similar version also available on arXiv).

    MBE: model-based enrichment estimation and prediction for differential sequencing data

    Akosua Busia and Jennifer Listgarten
    Genome Research 2023,   (paper link)

    Coherent Blending of Biophysics-Based Knowledge with Bayesian Neural Networks for Robust Protein Property Prediction

    Hunter Nisonoff, Yixin Wang, Jennifer Listgarten
    ACS Synth. Biol. 2023 (Editor's Choice)   (paper link)

    Conformal Prediction under Feedback Covariate Shift for Biomolecular Design

    Clara Fannjiang, Stephen Bates, Anastasios Angelopoulos, Jennifer Listgarten, and Michael I. Jordan
    PNAS 2022,   (paper link)

    Optimal trade-off control in machine learning-based library design, with application to adeno-associated virus (AAV) for gene therapy

    D Zhu*, DH Brookes*, A Busia*, A Carneiro, C Fannjiang, G Popova, D Shin, KC Donohue,, LF Lin, ZM Miller, ER Williams, EF Chang, TJ Nowakowski, J Listgarten*, DV Schaffer* (*equal contributions, corresponding)
    Science Advances 2024 (paper link)

    Effective training of nanopore callers for epigenetic marks with limited labelled data

    Brian Yao, Chloe Hsu, Gal Goldner, Yael Michaeli, Yuval Ebenstein, Jennifer Listgarten
    Open Biology 2024,   (paper link)

    On the sparsity of fitness functions and implications for learning

    David H Brookes, Amirali Aghazadeh, Jennifer Listgarten
    PNAS 2022,   (paper link)

    Learning protein fitness models from evolutionary and assay-labeled data

    Chloe Hsu, Hunter Nisonoff, Clara Fannjiang, Jennifer Listgarten
    Nature Biotechnology 2022   (paper)

    Epistatic Net allows the sparse spectral regularization of deep neural networks for inferring fitness functions

    Amirali Aghazadeh, Hunter Nisonoff, Ocal, Yijie Huang, O. Ozan Koyluoglu, Jennifer Listgarten, Kannan Ramchandran
    Nature Communications 2021,   (paper link)

    Autofocused oracles for model-based design

    Clara Fannjiang and Jennifer Listgarten
    NeurIPS 2020,   (paper link)

    Rethinking drug design in the artificial intelligence era

    P Schneider, WP Walters, AT Plowright, N Sieroka, J Listgarten, RA Goodnow Jr., J Fisher, JM Jansen, JS Duca, TS Rush, M Zentgraf, JE Hill, E Krutoholow, M Kohler, J Blaney, K Funatsu, C Luebkemann and G Schneider
    in Nature Reviews Drug Discovery  2019 (paper link)

    A view of Estimation of Distribution Algorithms through the lens of Expectation-Maximization

    David H. Brookes, Akosua Busia, Clara Fannjiang, Kevin Murphy and Jennifer Listgarten
    in Proceedings of GECCO 2020   (here , extended version here)

    Conditioning by adaptive sampling for robust design

    David H. Brookes, Hahnbeom Park and Jennifer Listgarten
    accepted at ICML  2019 (paper link, arXiv version is most up-to-date)
    (5% acceptance rate for 20 min. oral presentation)

    Design by adaptive sampling

    David Brookes and Jennifer Listgarten
    NeurIPS Workshop on Machine Learning for Molecules and Materials  2018 (paper link)

    Gaussian Process Prior Variational Autoencoders

    Francesco Paolo Casale, Adrian V Dalca, Luca Saglietti, Jennifer Listgarten, Nicolo Fusi
    in NeurIPS  2018 (paper link)

    Predicting off-target effects for end-to-end CRISPR guide design

    J Listgarten, M Weinstein, B Kleinstiver, AA Sousa, JK Joung, J Crawford, K Gao, M Elibol, L Hoang, J Doench, N Fusi (equal contributions and corresponding)
    Nature Biomedical Engineering  (2018) (paper link)
    Associated tools and resources available here.

    Orthologous CRISPR-Cas9 for Combinatorial Genetic Screens

    F Najm*, C Strand*, K Donovan*, M Hegde*, KR. Sanson*, EW Vaimberg, ME Sullender, E Hartenian, N Fusi, J. Listgarten, ST Younger*, BE Bernstein**, DE Root**, JG Doench**
    Nature Biotechnology  (2018) (paper link) (*equal contributions, **corresponding)

    Identifying gene expression modules that define human cell fates

    I Germanguz, J Listgarten, A Solomon, X Gaeta, WE Lowry  (equal contributions)
    Stem Cell Research  (2016,, in press)

    Leveraging Non-Linear Genetic Effects on Functional Traits for GWAS

    Nicolo Fusi and Jennifer Listgarten
    RECOMB Proceedings (in Lecture Notes in Computer Science)  2016 (pdf)

    Optimized sgRNA design to maximize activity and minimize off-target effects for genetic screens with CRISPR-Cas9

    JG Doench*, N Fusi*, M Sullender*, M Hegde*, EW Vaimberg*, KF Donovan, I Smith, Z Tothova, C Wilen , R Orchard , HW Virgin, J Listgarten*, DE Root
    Nature Biotechnology Jan 2016 doi:10.1038/nbt.3437
    (*equal contributions, corresponding)
    A pre-print of just the computational aspects of this paper is available on bioRxiv
    Source code and prediction server available from here: here.
    [Microsoft Research blog post]
    [Broad Institute blog post]

    In Silico Predictive Modeling of CRISPR/Cas9 guide efficiency

    Nicolo Fusi, Ian Smith, John Doench, Jennifer Listgarten
    bioRxiv, dx.doi.org/10.1101/021568 2015 ( preprint )
    This pre-print has been largely (though not entirely) absorbed into the Nature Biotechnology paper above.

    Further Improvements to Linear Mixed Models for Genome-Wide Association Studies

    Chris Widmer, Christoph. Lippert, Omer Weissbrod, Nicolo Fusi, Carl Kadie, Bob Davidson, Jennifer Listgarten and D. Heckerman
    Scientific Reports, Nov. 2014 (open access)

    let-7 miRNAs Can Act through Notch to Regulate Human Gliogenesis

    Patterson M, Gaeta X, Loo K, Edwards M, Smale S, Cinkornpumin J, Xie Y, Listgarten J, Azghadi S, Douglass SM, Pellegrini M, Lowry WE.
    Stem Cell Reports 2014, doi: 10.1016/j.stemcr.2014.08.015 (open access)

    Personalized Medicine: From Genotypes, Molecular Phenotypes and the Quantified Self, Toward Improved Medicine

    Joel Dudley, Jennifer Listgarten, Oliver Stegle, Steven Brenner, Leopold Parts
    Proceedings of the Pacific Symposium on Biocomputing 2015 (pdf)

    Greater power and computational efficiency for kernel-based association testing of sets of genetic variants

    C. Lippert, J. Xiang, D. Horta, C. Widmer, C. Kadie, D. Heckerman, Jennifer Listgarten
    Bioinformatics 2014, doi: 10.1093/bioinformatics/btu504 (open access)

    Epigenome-wide association studies without the need for cell-type composition

    James Zou, Christoph Lippert, David Heckerman, Martin Aryee, Jennifer Listgarten
    Nature Methods, 309-311 (2014) (journal link)
    Python software available from here, and R software available from here.
    Corrigendum: Supp. Figure 1 was not run with filters as described in the paper, but without any filters. We have contacted the journal to post this correction.

    Personalized Medicine: from genotypes and molecular phenotypes toward therapy

    Jennifer Listgarten, Oliver Stegle, Quaid Morris, Steven Brenner, Leo Parts
    Proceedings of the Pacific Symposium on Biocomputing 2014

    A genome-to-genome analysis of associations between human genetic variation, HIV-1 sequence diversity, and viral control.

    I. Bartha, J. Carlson, C. Brumme, P. McLaren, Z. Brumme, M. John, D. Haas, J. Martinez-Picado, J. Dalmau, C. López-Galíndez, C. Casado, A. Rauch, H. Günthard, E. Bernasconi, P. Vernazza, T. Klimkait, S. Yerly, S. O’Brien, Jennifer Listgarten, N. Pfeifer, C. Lippert, N. Fusi, Z. Kutalik, T. Allen, Viktor Müller, R. Harrigan, D. Heckerman, A. Telenti, J. Fellay
    eLife (2013) 2:e01123 (journal link)

    The benefits of selecting phenotype-specific variants for applications of mixed models in genomics.

    C. Lippert, G. Quon, EY Kang, C. Kadie, Jennifer Listgarten, D. Heckerman
    (equal contributions)
    Scientific Reports (2013) doi:10.1038/srep01815 (journal link)

    FaST-LMM-Select for addressing confounding from spatial structure and rare variants

    Jennifer Listgarten, Christoph Lippert, David Heckerman (equal contributions and corresponding)
    Nature Genetics, 45, 470-471 (2013) doi:10.1038/ng.2620 (journal link)

    A powerful and efficient set test for genetic markers that handles confounders

    Jennifer Listgarten, C. Lippert, EY Kang, J. Xiang, C. Kadie, D. Heckerman
    (equal contributions and corresponding)
    Bioinformatics 2013, doi: 10.1093/bioinformatics/btt177 (open access)
    Source and executables available here.

    An Exhaustive Epistatic SNP Association Analysis on Expanded Wellcome Trust Data

    C. Lippert, Jennifer Listgarten, R. Davidson, S. Baxter, H. Poon, C. Kadie, D. Heckerman,
    (equal contributions)
    Scientific Reports, 2013, doi:10.1038/srep01099

    Patterns of methylation heritability in a genome-wide analysis of four brain regions

    Gerald Quon, Christoph Lippert, David Heckerman, Jennifer Listgarten
    Nucleic Acids Research, 2013, doi: 10.1093/nar/gks1449

    The future of genome-based medicine.

    Quaid Morris, Steven Brenner, Jennifer Listgarten, Oliver Stegle
    Proceedings of the Pacific Symposium on Biocomputing 2013, 16:456-458. doi:10.1142/9789814447973_0046

    Correlates of Protective Cellular Immunity Revealed by Analysis of Population-Level Immune Escape Pathways in HIV-1

    J. Carlson, C. Brumme, E. Martin, Jennifer Listgarten, M. Brockman, AQ. Le, C. Chui, L. Cotton, D. Knapp, SA. Riddler, R. Haubrich, G. Nelson, N. Pfeifer, C. DeZiel, D. Heckerman, R. Apps, M. Carrington, S. Mallal, R. Harrigan, M. John, Z. Brumme and the International HIV Adaptation Collaborative
    Journal of Virology, Dec. 2012, 86(4)

    Co-Operative Additive Effects between HLA Alleles in Control of HIV-1

    P. Matthews, Jennifer Listgarten, J. Carlson, R. Payne, KH Huang, J Frater, D Goedhals, D Steyn, D van Vuuren, P Paioni, P Jooste, A Ogwu, R Shapiro, Z Mncube, T Ndung'u, B Walker, D Heckerman, P Goulder
    (equal contributions)
    PLoS One, 2012, 7(10): e47799. doi:10.1371/journal.pone.0047799

    Improved linear mixed models for genome-wide association studies

    Jennifer Listgarten, C Lippert, CM Kadie, RI Davidson, E Eskin and D Heckerman
    (equal contributions and corresponding)
    Nature Methods, 2012, doi:10.1038/nmeth.2037
    Source and executables available here.

    Learning Transcriptional Regulatory Relationships Using Sparse Graphical Models

    X Zhang, W Cheng, Jennifer Listgarten, C Kadie, S Huang, W Wang, D Heckerman
    PLoS One, 2012, doi:10.1371/journal.pone.0035762

    Widespread Impact of HLA Restriction on Immune Control and Escape Pathways in HIV-1

    J. Carlson, Jennifer Listgarten, N Pfeifer, V Tan, Carl Kadie, B Walker, T Ndung'u, R Shapiro, J Frater, Z Brumme, P Goulder and D Heckerman
    Journal of Virology, February 2012, doi:10.1128/?JVI.06728-11 (abstract,paper)

    Personalized Medicine: From Genotype and Molecular Phenotypes Towards Computed Therapy

    Oliver Stegle, Frederick P. Roth, Quaid Morris, Jennifer Listgarten
    Proceedings of the Pacific Symposium on Biocomputing 2012

    HLA-A*7401-mediated control of HIV viremia is independent of its linkage disequilibrium with HLA-B*5703.

    P. Matthews, E. Adland, J. Listgarten, A. Leslie, N. Mkhwanazi, J. Carlson, M. Harndahl, A. Stryhn, R. Payne, A. Ogwu, K. Huang, J. Frater, P. Paioni, H. Kloverpris, P.Jooste, D. Goedhals, C. van Vuuren, D. Steyn, L. Riddell, F. Chen, G. Luzzi, T. Balachandran, T. Ndung'u, S. Buus, M. Carrington, R. Shapiro, D. Heckerman, and P. Goulder
    Journal of Immunology April 2011, doi: 10.4049

    Additive contribution of HLA class I alleles in the immune control of HIV-1 infection

    Leslie A, Matthews PC, Listgarten J, Carlson JM, Kadie C, Ndung'u T, Brander C, Coovadia H, Walker BD, Heckerman D, Goulder PJ
    Journal of Virology , 2010

    Rare HLA Drive Additional HIV Evolution Compared to More Frequent Alleles

    CM Rousseau, DW Lockhart, Jennifer Listgarten, C Kadie, GH Learn, DC Nickle, D Heckerman, W Deng, C Brander, T Ndung'u, H Coovadia, P Goulder, B. Korber, B Walker, J Mullins
    AIDS Research and Human Retroviruses , 2009; 25(3):297-303

    In silico resolution of ambiguous HLA typing data

    J Listgarten, Z Brumme, C Kadie, G Xiaojiang, B Walker, M Carrington, P Goulder, D Heckerman,
    in ASHI Quarterly, Volume 32, Number 2, 2008
    For the public web server tool based on this work, go here ; for .exe and source code (training code not included), go here. (pdf)

    Statistical resolution of ambiguous HLA typing data.

    Jennifer Listgarten, Z Brumme, C Kadie, G Xiaojiang, B Walker, M Carrington, P Goulder, D Heckerman,
    in PLoS Computational Biology, 2008, 4(2):e1000016
    For the public web server tool based on this work, go here ; for .exe and source code (training code not included), go here.
    (abstract, paper, coverage in the magazine BioInform, press release)

    A statistical framework for modeling HLA-dependent T-cell response data.

    Jennifer Listgarten, Nicole Frahm, Carl Kadie, Christian Brander and David Heckerman,
    PLoS Computational Biology, 2007, 3(10):e188
    Web tool, executable and source code available here, under "HLA Assignment"
    (abstract, paper, press release)

    Extensive HLA class I allele promiscuity among viral CTL epitopes.

    N. Frahm, K. Yusim, T. Suscovich, S. Adams, J. Sidney, P. Hraber, H. Hewitt, CH. Linde, D. Kavanagh, T. Woodberry, L. Henry, K. Faircloth, J. Listgarten, C. Kadie, N. Jojic, K. Sango, N. Brown, E. Pae, M. Zaman, F. Bihl, A. Khatri, M. John, S. Mallal, F. Marincola, B. Walker, A. Sette, D. Heckerman, B. Korber, C. Brander
    European Journal of Immunology, 2007 37(9):2419-2433.
    See paper above for code/tools used in this paper. (abstract)

    Evidence that dysregulated DNA mismatch repair characterizes human non-melanoma skin cancer

    Leah C. Young, Jennifer Listgarten, Martin J. Trotter, Susan E. Andrew, Victor A. Tron
    British Journal of Dermatology, 2008 158(1):59-69. (abstract)

    Determining the number of non-spurious arcs in a learned DAG model: Investigation of a Bayesian and a frequentist approach.

    Jennifer Listgarten and David Heckerman
    Proceedings of Twenty-Third Conference on Uncertainty in Artificial Intelligence, UAI Press, July 2007 ( paper)

    Analysis of sibling time series data: alignment and difference detection

    Jennifer Listgarten,
    Ph.D. Thesis, Department of Computer Science, University of Toronto 2007.
    (abstract, thesis and code)

    Bayesian detection of infrequent differences in sets of time series with shared structure.

    Jennifer Listgarten, Radford M. Neal, Sam T. Roweis, Rachel Puckrin and Sean Cutler,
    Advances in Neural Information Processing Systems 19, MIT Press, Cambridge, MA, 2007 ( NIPS 2006).
    Best Student Paper, Honorable Mention. (abstract, paper)

    Leveraging information across HLA alleles/supertypes improves epitope prediction.

    David Heckerman, Carl Kadie, Jennifer Listgarten,
    Journal of Computational Biology, 2007 14: 736-746
    (shorter version also appears Proceedings of Research in Computational Molecular Biology. Lecture Notes in Computer Science, Volume 3909, Mar 2006, 296-308.)
    (abstract, paper)
    Web tool, executable and source code available here, under "Epitope Prediction"

    Practical proteomic biomarker discovery: taking a step back to leap forward.

    Jennifer Listgarten and Andrew Emili,
    Drug Discovery Today, 2005 10:1697-1702.
    (abstract) (paper)

    Statistical and computational methods for comparative proteomic profiling using liquid chromatography-tandem mass spectrometry.

    Jennifer Listgarten and Andrew Emili,
    Molecular and Cellular Proteomics, 2005 4:419-434.
    (abstract) (paper)

    Multiple alignment of continuous time series.

    Jennifer Listgarten, Radford M. Neal, Sam T. Roweis and Andrew Emili,
    Advances in Neural Information Processing Systems 17, MIT Press, Cambridge, MA, 2005 (NIPS 2004).
    The Continuous Profile Models (CPM) Matlab Toolbox is available here.
    (abstract, paper, slides, and audio demo)

    Predictive models for breast cancer susceptibility from multiple, single nucleotide polymorphisms.

    (abstract) (paper)
    Jennifer Listgarten, S Damaraju, B Poulin, L Cook, J Dufour, A Driga, J Mackey, D Wishart, R Greiner and B Zanke,
    Clinical Cancer Research 2004:10(8):2725-37.

    Clinically validated benchmarking of normalization techniques for two-colour oligonucleotide spotted microarray slides.

    (abstract) (paper)
    Jennifer Listgarten, K Graham, S Damaraju, C Cass, J Mackey and B Zanke, Applied Bioinformatics 2003:2(4)219-228.

    Lymphovascular invasion is associated with poor survival in gastric cancer: an application of gene-expression and tissue array techniques.

    BJ Dicken, K Graham, SM Hamilton, S Andrews, R Lai, Jennifer Listgarten, GS Jhangri, LD Saunders, S Damaraju and CE Cass,
    Annals of Surgery 2006: 243(1):64-73.

    Exploring qualitative probabilities for image understanding

    Jennifer Listgarten,
    M.Sc. Thesis, Department of Computer Science, University of Toronto, October 2000.
    (pdf 1.2MB) (ps.gz 0.6MB)

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