| 2024 | RECOMB | Semi-supervised Learning While Controlling the FDR with an Application to Tandem Mass Spectrometry Analysis. | Jack Freestone, Lukas Kll, William Stafford Noble, Uri Keich |
| 2022 | ISIT | Fundamental Limits of Multi-Sample Flow Graph Decomposition. | Kayvon Mazooji, Sreeram Kannan, William Stafford Noble, Ilan Shomorony |
| 2022 | RECOMB | Semi-supervised Single-Cell Cross-modality Translation Using Polarbear. | Ran Zhang, Laetitia Meng-Papaxanthos, Jean-Philippe Vert, William Stafford Noble |
| 2021 | ICML | DANCE: Enhancing saliency maps using decoys. | Yang Young Lu, Wenbo Guo, Xinyu Xing, William Stafford Noble |
| 2021 | ICML | ACE: Explaining cluster from an adversarial perspective. | Yang Young Lu, Timothy C. Yu, Giancarlo Bonora, William Stafford Noble |
| 2020 | RECOMB | Multiple Competition-Based FDR Control and Its Application to Peptide Detection. | Kristen Emery, Syamand Hasam, William Stafford Noble, Uri Keich |
| 2019 | WABI | Inferring Diploid 3D Chromatin Structures from Hi-C Data. | Alexandra Gesine Cauer, Grkan Yardimci, Jean-Philippe Vert, Nelle Varoquaux, William Stafford Noble |
| 2019 | WABI | Jointly Embedding Multiple Single-Cell Omics Measurements. | Jie Liu, Yuanhao Huang, Ritambhara Singh, Jean-Philippe Vert, William Stafford Noble |
| 2017 | RECOMB | Progressive Calibration and Averaging for Tandem Mass Spectrometry Statistical Confidence Estimation: Why Settle for a Single Decoy? | Uri Keich, William Stafford Noble |
| 2015 | ICML | Entropic Graph-based Posterior Regularization. | Maxwell W. Libbrecht, Michael M. Hoffman, Jeff A. Bilmes, William Stafford Noble |
| 2014 | UAI | Learning Peptide-Spectrum Alignment Models for Tandem Mass Spectrometry. | John T. Halloran, Jeff A. Bilmes, William Stafford Noble |
| 2013 | PSB | Session Introduction. | Alexander J. Hartemink, Manolis Kellis, William Stafford Noble, Zhiping Weng |
| 2012 | PSB | The Structure and Function of Chromatin and Chromosomes. | William Stafford Noble, C. Anthony Blau, Job Dekker, Zhi-jun Duan, Yi Mao |
| 2012 | UAI | Spectrum Identification using a Dynamic Bayesian Network Model of Tandem Mass Spectra. | Ajit P. Singh, John T. Halloran, Jeff A. Bilmes, Katrin Kirchhoff, William Stafford Noble |
| 2011 | RECOMB | A Three-Dimensional Model of the Yeast Genome. | William Stafford Noble, Zhi-jun Duan, Mirela Andronescu, Kevin Schutz, Sean McIlwain, Yoo Jung Kim, Choli Lee, Jay Shendure, Stanley Fields, C. Anthony Blau |
| 2010 | RECOMB | Predicting Nucleosome Positioning Using Multiple Evidence Tracks. | Sheila M. Reynolds, Zhiping Weng, Jeff A. Bilmes, William Stafford Noble |
| 2009 | RECOMB | On the Relationship between DNA Periodicity and Local Chromatin Structure. | Sheila M. Reynolds, Jeff A. Bilmes, William Stafford Noble |
| 2008 | ECCB | Non-parametric estimation of posterior error probabilities associated with peptides identified by tandem mass spectrometry. | Lukas Kll, John D. Storey, William Stafford Noble |
| 2008 | ECCB | Improved network-based identification of protein orthologs. | Nir Yosef, Roded Sharan, William Stafford Noble |
| 2008 | ISMB | Modeling peptide fragmentation with dynamic Bayesian networks for peptide identification. | Aaron A. Klammer, Sheila M. Reynolds, Jeff A. Bilmes, Michael J. MacCoss, William Stafford Noble |
| 2008 | PSB | Multi-Scale Correlations in Continuous Genomic Data. | Robert E. Thurman, William Stafford Noble, John A. Stamatoyannopoulos |
| 2007 | RECOMB | Peptide Retention Time Prediction Yields Improved Tandem Mass Spectrum Identification for Diverse Chromatography Conditions. | Aaron A. Klammer, Xianhua Yi, Michael J. MacCoss, William Stafford Noble |
| 2006 | ICML | Nonstationary kernel combination. | Darrin P. Lewis, Tony Jebara, William Stafford Noble |
| 2006 | ISMB | Efficient identification of DNA hybridization partners in a sequence database. | Tobias P. Mann, William Stafford Noble |
| 2005 | ICML | Multi-class protein fold recognition using adaptive codes. | Eugene Ie, Jason Weston, William Stafford Noble, Christina S. Leslie |
| 2005 | ISMB | Kernel methods for predicting protein-protein interactions. | Asa Ben-Hur, William Stafford Noble |
| 2005 | ISMB | Predicting the | William Stafford Noble, Scott Kuehn, Robert E. Thurman, Man Yu, John A. Stamatoyannopoulos |
| 2004 | ISMB | Learning kernels from biological networks by maximizing entropy. | Koji Tsuda, William Stafford Noble |
| 2004 | PSB | Kernel-Based Data Fusion and Its Application to Protein Function Prediction in Yeast. | Gert R. G. Lanckriet, Minghua Deng, Nello Cristianini, Michael I. Jordan, William Stafford Noble |
| 2003 | ECCB | Searching for statistically significant regulatory modules. | Timothy L. Bailey, William Stafford Noble |
| 2002 | PSB | The Spectrum Kernel: A String Kernel for SVM Protein Classification. | Christina S. Leslie, Eleazar Eskin, William Stafford Noble |
| 2002 | PSB | Exploring Gene Expression Data with Class Scores. | Paul Pavlidis, Darrin P. Lewis, William Stafford Noble |
| 2002 | RECOMB | Combining pairwise sequence similarity and support vector machines for remote protein homology detection. | Li Liao, William Stafford Noble |
| 2001 | KDD | Classification of genes using probabilistic models of microarray expression profiles. | Paul Pavlidis, Christopher Tang, William Stafford Noble |