Nir Friedman

发表

Plausibility measures and default reasoning

Joseph Y. Halpern, Nir Friedman, N. Friedman, 1996, JACM.

Learning the Structure of Dynamic Probabilistic Networks pdf

Kevin P. Murphy, Stuart J. Russell, Nir Friedman, 1998, UAI.

Uncertainty in artificial intelligence : proceedings of the Eighteenth Conference (2002) : August 1-4, 2002, University of Alberta, Edmonton

Nir Friedman, Daphne Koller, Adnan Darwiche, 2002 .

Graphical Models Inferring Cellular Networks Using Probabilistic

Nir Friedman, 2007 .

Generalized Prioritized Sweeping

David Andre, Nir Friedman, Ronald Parr, 1997, NIPS.

From promoter sequence to expression: a probabilistic framework

Nir Friedman, Daphne Koller, Eran Segal, 2002, RECOMB '02.

EEG-Based Prediction of Cognitive Load in Intelligence Tests

Oren Shriki, Nir Friedman, Tomer Fekete, 2019, bioRxiv.

Context-Specific Bayesian Clustering for Gene Expression Data

Nir Friedman, Yoseph Barash, 2002, J. Comput. Biol..

Context-specific Bayesian clustering for gene expression data

Nir Friedman, Yoseph Barash, N. Friedman, 2001, J. Comput. Biol..

Likelihood Computations Using Value Abstraction

Nir Friedman, Dan Geiger, Noam Lotner, 2000, UAI.

Multivariate Information Bottleneck

Naftali Tishby, Nir Friedman, Noam Slonim, 2001, Neural Computation.

Continuous-Time Belief Propagation

Nir Friedman, Raz Kupferman, Tal El-Hay, 2010, ICML.

5 Probabilistic Relational Models

Lise Getoor, Avi Pfeffer, Nir Friedman, 2008 .

Probabilistic Graphical Models - Principles and Techniques

Nir Friedman, Daphne Koller, D. Koller, 2009 .

Modeling Belief in Dynamic Systems, Part I: Foundations

Joseph Y. Halpern, Nir Friedman, N. Friedman, 1997, Artif. Intell..

Convexifying the Bethe Free Energy pdf

Ofer Meshi, Nir Friedman, Amir Globerson, 2009, UAI.

Towards an Integrated Protein-Protein Interaction Network

Nir Friedman, Hanah Margalit, Gal Elidan, 2005, RECOMB.

Gene expression cartography

Nir Friedman, Nikolaus Rajewsky, Mor Nitzan, 2019, Nature.

Modularity and directionality in genetic interaction maps

Nir Friedman, Hanah Margalit, Ruty Rinott, 2010, Bioinform..

Towards an Integrated Protein-Protein Interaction Network: A Relational Markov Network Approach

Nir Friedman, Hanah Margalit, Gal Elidan, 2006, J. Comput. Biol..

Structured Representation of Complex Stochastic Systems

Avi Pfeffer, Nir Friedman, Daphne Koller, 1998, AAAI/IAAI.

An integrative clustering and modeling algorithm for dynamical gene expression data

Nir Friedman, Julia Sivriver, Naomi Habib, 2011, Bioinform..

Modeling dependencies in protein-DNA binding sites

Nir Friedman, Gal Elidan, Yoseph Barash, 2003, RECOMB '03.

Nucleosome positioning from tiling microarray data

Nir Friedman, Tommy Kaplan, Ariel Jaimovich, 2008, ISMB.

Dimension Reduction in Singularly Perturbed Continuous-Time Bayesian Networks pdf

Nir Friedman, Raz Kupferman, 2006, UAI.

Learning Belief Networks in the Presence of Missing Values and Hidden Variables

Nir Friedman, N. Friedman, 1997, ICML.

Ab Initio Prediction of Transcription Factor Targets Using Structural Knowledge

Nir Friedman, Hanah Margalit, Tommy Kaplan, 2005, PLoS Comput. Biol..

Building Classifiers Using Bayesian Networks

Nir Friedman, Moisés Goldszmidt, M. Goldszmidt, 1996, AAAI/IAAI, Vol. 2.

Context-Specific Independence in Bayesian Networks pdf

Craig Boutilier, Nir Friedman, Daphne Koller, 1996, UAI.

Being Bayesian about Network Structure

Nir Friedman, Daphne Koller, D. Koller, 2000, UAI.

Sequential Update of Bayesian Network Structure pdf

Nir Friedman, Moisés Goldszmidt, M. Goldszmidt, 1997, UAI.

Nondeterministic Actions and the Frame Problem

Craig Boutilier, Nir Friedman, Craig Boutilier, 1995 .

Plausibility Measures: A User's Guide pdf

Joseph Y. Halpern, Nir Friedman, N. Friedman, 1995, UAI.

"Ideal Parent" Structure Learning for Continuous Variable Bayesian Networks

Nir Friedman, Gal Elidan, Iftach Nachman, 2007, J. Mach. Learn. Res..

A Qualitative Markov Assumption and Its Implications for Belief Change pdf

Joseph Y. Halpern, Nir Friedman, N. Friedman, 1996, UAI.

Qualitative Planning under Assumptions: A Preliminary Report

Nir Friedman, Daphne Koller, 1994 .

Comparative analysis of algorithms for signal quantitation from oligonucleotide microarrays

Nir Friedman, Naftali Kaminski, Yoseph Barash, 2004, Bioinform..

Discretizing Continuous Attributes While Learning Bayesian Networks

Nir Friedman, Moisés Goldszmidt, M. Goldszmidt, 1996, ICML.

McPAS‐TCR: a manually curated catalogue of pathology‐associated T cell receptor sequences

Jaime Prilusky, Nir Friedman, Nili Tickotsky, 2017, Bioinform..

Model based Bayesian Exploration pdf

David Andre, Nir Friedman, Richard Dearden, 1999, UAI.

Belief Revision with Unreliable Observations

Craig Boutilier, Joseph Y. Halpern, Nir Friedman, 1998, AAAI/IAAI.

Continuous Time Markov Networks pdf

Nir Friedman, Daphne Koller, Raz Kupferman, 2006, UAI.

A branch-and-bound algorithm for the inference of ancestral amino-acid sequences when the replacement rate varies among sites: Application to the evolution of five gene families

Tal Pupko, Nir Friedman, Dan Graur, 2002, Bioinform..

Learning Module Networks

Nir Friedman, Aviv Regev, Eran Segal, 2002, J. Mach. Learn. Res..

Efficient learning using constrained sufficient statistics

Lise Getoor, Nir Friedman, N. Friedman, 1999, AISTATS.

Automatic genome-wide reconstruction of phylogenetic gene trees

Avi Pfeffer, Nir Friedman, Aviv Regev, 2007, ISMB/ECCB.

A Knowledge-Based Framework for Belief Change, Part II: Revision and Update

Joseph Y. Halpern, Nir Friedman, N. Friedman, 1994, KR.

Data mining tasks and methods: Classification: Bayesian classification

Ron Kohavi, Nir Friedman, N. Friedman, 2002 .

Inferring subnetworks from perturbed expression profiles

Nir Friedman, Aviv Regev, Gal Elidan, 2001, ISMB.

Bayesian Q-Learning

Stuart J. Russell, Nir Friedman, Richard Dearden, 1998, AAAI/IAAI.

A Knowledge-Based Framework for Belief change, Part I: Foundations

Joseph Y. Halpern, Nir Friedman, N. Friedman, 1994, TARK.

Inferring quantitative models of regulatory networks from expression data

Nir Friedman, Aviv Regev, Iftach Nachman, 2004, ISMB/ECCB.

Optimal video stream multiplexing through linear programming

Ofer Hadar, Helman Stern, Nir Friedman, 2008, Signal Process. Image Commun..

Using Bayesian Networks to Analyze Expression Data

Michal Linial, Nir Friedman, Iftach Nachman, 2000, J. Comput. Biol..

On the Complexity of Conditional Logics

Joseph Y. Halpern, Nir Friedman, N. Friedman, 1994, KR.

Tracking global changes induced in the CD4 T-cell receptor repertoire by immunization with a complex antigen using short stretches of CDR3 protein sequence

John Shawe-Taylor, Nir Friedman, Niclas Thomas, 2014, bioRxiv.

A Structural EM Algorithm for Phylogenetic Inference

Tal Pupko, Nir Friedman, Itsik Pe'er, 2002, J. Comput. Biol..

A structural EM algorithm for phylogenetic inference

Tal Pupko, Nir Friedman, Itsik Pe'er, 2001, J. Comput. Biol..

Modeling Belief in Dynamic Systems, Part II: Revisions and Update

Joseph Y. Halpern, Nir Friedman, N. Friedman, 1999, J. Artif. Intell. Res..

A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science

Nir Friedman, Jenia Gutin, N. Friedman, 2014 .

Rich probabilistic models for gene expression

Ben Taskar, Nir Friedman, Daphne Koller, 2001, ISMB.

Charting a tissue from single-cell transcriptomes

Nir Friedman, Nikolaus Rajewsky, Mor Nitzan, 2018 .

Efficient Bayesian Parameter Estimation in Large Discrete Domains

Yoram Singer, Nir Friedman, Y. Singer, 1998, NIPS.

Likelihood Computations Using Value Abstractions pdf

Nir Friedman, Dan Geiger, Noam Lotner, 2013, ArXiv.

Gibbs Sampling in Factorized Continuous-Time Markov Processes

Nir Friedman, Raz Kupferman, Tal El-Hay, 2008, UAI.

Discovering the Hidden Structure of Complex Dynamic Systems

Xavier Boyen, Nir Friedman, Daphne Koller, 1999, UAI.

Probabilistic Graphical Models

Nir Friedman, Daphne Koller, D. Koller, 2009, Data-Driven Computational Neuroscience.

Predicting Transcription Factor Binding Sites Using Structural Knowledge

Nir Friedman, Hanah Margalit, Tommy Kaplan, 2005, RECOMB.

Proceedings of the Eighteenth Conference on Uncertainty in Artificial Intelligence (2002) pdf

Nir Friedman, Adnan Darwiche, 2013, ArXiv.

Belief Revision: A Critique

Joseph Y. Halpern, Nir Friedman, N. Friedman, 1996, J. Log. Lang. Inf..

Phylogeny reconstruction: increasing the accuracy of pairwise distance estimation using Bayesian inference of evolutionary rates

Tal Pupko, Nir Friedman, Matan Ninio, 2007, Bioinform..

"Ideal Parent" Structure Learning for Continuous Variable Networks

Nir Friedman, Gal Elidan, Iftach Nachman, 2004, UAI.

On the Sample Complexity of Learning Bayesian Networks

Nir Friedman, Zohar Yakhini, N. Friedman, 1996, UAI.

The Bayesian Structural EM Algorithm

Nir Friedman, N. Friedman, 1998, UAI.

A Gamma mixture model better accounts for among site rate heterogeneity

Itay Mayrose, Tal Pupko, Nir Friedman, 2005, ECCB/JBI.

A Novel Bayesian DNA Motif Comparison Method for Clustering and Retrieval

Nir Friedman, Hanah Margalit, Tommy Kaplan, 2008, PLoS Comput. Biol..

Template Based Inference in Symmetric Relational Markov Random Fields

Ofer Meshi, Nir Friedman, Ariel Jaimovich, 2007, UAI.

Conditional Logics of Belief Change

Joseph Y. Halpern, Nir Friedman, N. Friedman, 1994, AAAI.

The Information Bottleneck EM Algorithm pdf

Nir Friedman, Gal Elidan, N. Friedman, 2002, UAI.

Class discovery in gene expression data

Nir Friedman, Zohar Yakhini, Amir Ben-Dor, 2001, RECOMB.

Learning Bayesian Networks with Local Structure pdf

Nir Friedman, Moisés Goldszmidt, M. Goldszmidt, 1996, UAI.

Learning Probabilistic Models of Link Structure

Ben Taskar, Lise Getoor, Nir Friedman, 2003, J. Mach. Learn. Res..

Criticality in Neuronal Networks

Nir Friedman, Karin A. Dahmen, John M. Beggs, 2012 .

Learning Bayesian Networks from Data

Nir Friedman, Daphne Koller, D. Koller, 2001 .

Data perturbation for escaping local maxima in learning

Dale Schuurmans, Nir Friedman, Gal Elidan, 2002, AAAI/IAAI.

CIS: compound importance sampling method for protein-DNA binding site p-value estimation

Nir Friedman, Gal Elidan, Yoseph Barash, 2005, Bioinform..

Bayesian Network Classifiers

Nir Friedman, Dan Geiger, Moisés Goldszmidt, 1997, Machine Learning.

On the application of the bootstrap for computing confidence measures on features of induced Bayesian networks

Nir Friedman, Moisés Goldszmidt, Abraham J. Wyner, 1999, AISTATS.

Bayesian Network Classification with Continuous Attributes: Getting the Best of Both Discretization and Parametric Fitting

Nir Friedman, Moisés Goldszmidt, Thomas J. Lee, 1998, ICML.

Proceedings of the 15th annual conference on uncertainty in artificial intelligence (UAI)

Nir Friedman, Abraham J. Wyner, Moises Goldszmidt, 1999 .

Incorporating Expressive Graphical Models in VariationalApproximations: Chain-graphs and Hidden Variables

Nir Friedman, Tal El-Hay, 2001, UAI.

Gaussian Process Networks

Nir Friedman, Iftach Nachman, N. Friedman, 2000, UAI.

Learning Bayesian Network Structure from Massive Datasets: The "Sparse Candidate" Algorithm

Nir Friedman, Iftach Nachman, Dana Pe'er, 1999, UAI.

Using Bayesian networks to analyze expression data

Michal Linial, Nir Friedman, Iftach Nachman, 2000, RECOMB '00.

UAI '02, Proceedings of the 18th Conference in Uncertainty in Artificial Intelligence, University of Alberta, Edmonton, Alberta, Canada, August 1-4, 2002

Nir Friedman, Adnan Darwiche, Adnan Darwiche, 2002, Conference on Uncertainty in Artificial Intelligence.

First-order conditional logic for default reasoning revisited

Joseph Y. Halpern, Nir Friedman, Daphne Koller, 2000, TOCL.

Data Analysis with Bayesian Networks: A Bootstrap Approach

Nir Friedman, Moisés Goldszmidt, Abraham J. Wyner, 1999, UAI.

Probabilistic models for identifying regulation networks

Nir Friedman, N. Friedman, 2003, ECCB.

Probabilistic Graphical Models: Principles and Techniques - Adaptive Computation and Machine Learning

Nir Friedman, Daphne Koller, D. Koller, 2009 .

Image Segmentation in Video Sequences: A Probabilistic Approach

Stuart J. Russell, Nir Friedman, N. Friedman, 1997, UAI.

Agglomerative Multivariate Information Bottleneck

Naftali Tishby, Nir Friedman, Noam Slonim, 2001, NIPS.

Discovering Hidden Variables: A Structure-Based Approach

Nir Friedman, Daphne Koller, Gal Elidan, 2000, NIPS.

Balancing speed and accuracy of polyclonal T cell activation: a role for extracellular feedback

Nir Friedman, Tsvi Tlusty, Yonatan Savir, 2012, BMC Systems Biology.

Robust temporal and spectral modeling for query By melody

Shlomo Dubnov, Yoram Singer, Shai Shalev-Shwartz, 2002, SIGIR '02.

A Simple Hyper-Geometric Approach for Discovering Putative Transcription Factor Binding Sites

Nir Friedman, Gill Bejerano, Yoseph Barash, 2001, WABI.

Identifying novel constrained elements by exploiting biased substitution patterns

Xiaohui Xie, Nir Friedman, Michael C. Zody, 2009, Bioinform..

Being Bayesian About Network Structure. A Bayesian Approach to Structure Discovery in Bayesian Networks

Nir Friedman, Daphne Koller, D. Koller, 2004, Machine Learning.

Inferring geometric embeddings for single cell data

Nir Friedman, Nikolaus Rajewsky, Mor Nitzan, 2019 .

Challenge: What is the Impact of Bayesian Networks on Learning?

David Heckerman, Stuart J. Russell, Nir Friedman, 1997, IJCAI.

Tissue classification with gene expression profiles.

Nir Friedman, Zohar Yakhini, Iftach Nachman, 2000 .

First-Order Conditional Logic Revisited

Joseph Y. Halpern, Nir Friedman, Daphne Koller, 1996, AAAI/IAAI, Vol. 2.

Learning Probabilistic Models of Relational Structure

Ben Taskar, Lise Getoor, Nir Friedman, 2001, ICML.

Tissue classification with gene expression profiles

Nir Friedman, Zohar Yakhini, Amir Ben-Dor, 2000, RECOMB '00.

Plausibility measures and default reasoning: an overview

Joseph Y. Halpern, Nir Friedman, N. Friedman, 1999, Proceedings. 14th Symposium on Logic in Computer Science (Cat. No. PR00158).

Mean Field Variational Approximation for Continuous-Time Bayesian Networks pdf

Nir Friedman, Raz Kupferman, Tal El-Hay, 2009, J. Mach. Learn. Res..

Learning the Dimensionality of Hidden Variables

Nir Friedman, Gal Elidan, 2001, UAI.

Unsupervised document classification using sequential information maximization

Naftali Tishby, Nir Friedman, Noam Slonim, 2002, SIGIR '02.

Learning Probabilistic Relational Models with Structural Uncertainty

Lise Getoor, Nir Friedman, Daphne Koller, 2000 .

Physical Module Networks: an integrative approach for reconstructing transcription regulation

Nir Friedman, Aviv Regev, Noa Novershtern, 2011, Bioinform..

On Decision-Theoretic Foundations for Defaults

Ronen I. Brafman, Nir Friedman, N. Friedman, 1995, IJCAI.

Efficient Exact p-Value Computation for Small Sample, Sparse, and Surprising Categorical Data

Naftali Tishby, Nir Friedman, Gill Bejerano, 2004, J. Comput. Biol..

Learning Hidden Variable Networks: The Information Bottleneck Approach

Nir Friedman, Gal Elidan, N. Friedman, 2005, J. Mach. Learn. Res..

From Instances to Classes in Probabilistic Relational Models

Lise Getoor, Nir Friedman, Daphne Koller, 2000, ICML 2000.

Coupled IL-2–Dependent Extracellular Feedbacks Govern Two Distinct Consecutive Phases of CD4 T Cell Activation

Nir Friedman, Benjamin M. Chain, Nir Waysbort, 2013, The Journal of Immunology.

High Throughput Determination of TGFβ1/SMAD3 Targets in A549 Lung Epithelial Cells

Oliver Eickelberg, Nir Friedman, Naftali Kaminski, 2011, PloS one.

Learning BayesianNetwork Structur e fr om Massive Datasets: The “SparseCandidate” Algorithm

Nir Friedman, 2001 .

Universal Quake Statistics: From Compressed Nanocrystals to

Danijel Schorlemmer, Julia R. Greer, Nir Friedman, 2015 .

Chromatin conformation governs T-cell receptor Jβ gene segment usage

Wilfred Ndifon, Nir Friedman, Hilah Gal, 2012, Proceedings of the National Academy of Sciences.

Deciphering eukaryotic gene-regulatory logic with 100 million random promoters

Nir Friedman, Aviv Regev, Carl G. de Boer, 2019, Nature Biotechnology.

Quantitative kinetic analysis of the bacteriophage lambda genetic network.

Nir Friedman, N. Friedman, D. Court, 2005, Proceedings of the National Academy of Sciences of the United States of America.

Paternally Induced Transgenerational Environmental Reprogramming of Metabolic Gene Expression in Mammals

Zhiping Weng, Nir Friedman, Ruowang Li, 2010, Cell.

Practical approaches to analyzing results of microarray experiments.

Nir Friedman, Naftali Kaminski, N. Friedman, 2002, American journal of respiratory cell and molecular biology.

Dynamics of Replication-Independent Histone Turnover in Budding Yeast

Nir Friedman, Minkyu Kim, Tommy Kaplan, 2007, Science.

Dynamic response diversity of NFAT isoforms in individual living cells.

Nir Friedman, Ziv Porat, Eric Shifrut, 2013, Molecular cell.

A functional selection model explains evolutionary robustness despite plasticity in regulatory networks

Nir Friedman, Hanah Margalit, Aviv Regev, 2012 .

Stochasticity in Gene Expression as Observed by Single-molecule Experiments in Live Cells

Nir Friedman, Long Cai, N. Friedman, 2010 .

Scoring Genes for Relevance

Nir Friedman, Zohar Yakhini, Amir Ben-Dor, 2000 .

24 Combined analysis of antigen presentation and T cell recognition reveals restricted immune responses in melanoma

Eytan Ruppin, Nir Friedman, Dan Reshef, 2018, Cancer discovery.

High-resolution nucleosome mapping reveals transcription-dependent promoter packaging.

Nir Friedman, Moran Yassour, N. Friedman, 2010, Genome research.

Patterns and Mechanisms of Ancestral Histone Protein Inheritance in Budding Yeast

Nir Friedman, Oliver J. Rando, Tibor van Welsem, 2011, PLoS biology.

Mapping Differentiation under Mixed Culture Conditions Reveals a Tunable Continuum of T Cell Fates

Nir Friedman, Yuval Hart, Avi Mayo, 2013, PLoS biology.

De novo transcript sequence reconstruction from RNA-Seq: reference generation and analysis with Trinity

Michael Ott, Nir Friedman, Aviv Regev, 2013 .

Linking stochastic dynamics to population distribution: an analytical framework of gene expression.

Nir Friedman, Long Cai, N. Friedman, 2006, Physical review letters.

High-Resolution Chromatin Dynamics during a Yeast Stress Response

Nir Friedman, Oliver J. Rando, Ido Amit, 2015, Molecular cell.

Monitoring the dynamics of primary T cell activation and differentiation using long term live cell imaging in microwell arrays.

Nir Friedman, Guy Aidelberg, Eric Shifrut, 2012, Lab on a chip.

A high-throughput chromatin immunoprecipitation approach reveals principles of dynamic gene regulation in mammals.

Nir Friedman, Zohar Itzhaki, Aviv Regev, 2012, Molecular cell.

Quantitative kinetic analysis of the bacteriophage λ genetic network

Nir Friedman, N. Friedman, D. Court, 2005 .

Paradoxical Signaling by a Secreted Molecule Leads to Homeostasis of Cell Levels

Nir Friedman, Yuval Hart, Uri Alon, 2014, Cell.

Tracking global changes induced in the CD4 T cell receptor repertoire by immunisation with a complex antigen using local sequence features of CDR3 protein sequence

John Shawe-Taylor, Nir Friedman, Niclas Thomas, 2014 .

Epigenomics and the structure of the living genome

Nir Friedman, N. Friedman, O. Rando, 2015, Genome research.

Comparative Functional Genomics of the Fission Yeasts

Manolis Kellis, Nir Friedman, Hanah Margalit, 2011, Science.

Molecular constraints on CDR3 for thymic selection of MHC-restricted TCRs from a random pre-selection repertoire

Nir Friedman, Eric Shifrut, Peter D Sun, 2019, Nature Communications.

Induction of CD4 T cell memory by local cellular collectivity

Nir Friedman, Eyal David, Gil Stelzer, 2018, Science.

Condition-specific genetic interaction maps reveal crosstalk between the cAMP/PKA and the HOG MAPK pathways in the activation of the general stress response

Nir Friedman, Amir Aharoni, Jenia Gutin, 2015, Molecular systems biology.

A functional and regulatory map of asthma.

Nir Friedman, Zohar Itzhaki, Naftali Kaminski, 2008, American journal of respiratory cell and molecular biology.

Exploring transcription regulation through cell-to-cell variability

Nir Friedman, N. Friedman, Ruty Rinott, 2011, Proceedings of the National Academy of Sciences.

Mapping Nucleosome Resolution Chromosome Folding in Yeast by Micro-C

Nir Friedman, Bryan Lajoie, Oliver J. Rando, 2015, Cell.

Precise Temporal Modulation in the Response of the SOS DNA Repair Network in Individual Bacteria

Nir Friedman, Uri Alon, N. Friedman, 2005, PLoS biology.

Clonal expansion under the microscope: studying lymphocyte activation and differentiation using live‐cell imaging

Nir Friedman, N. Friedman, M. Polonsky, 2016, Immunology and cell biology.

Dynamic Perturbations of the T-Cell Receptor Repertoire in Chronic HIV Infection and following Antiretroviral Therapy

Nir Friedman, Mahdad Noursadeghi, Niclas Thomas, 2015, Front. Immunol..

From large-scale assays to mechanistic insights: computational analysis of interactions.

Nir Friedman, N. Friedman, A. Jaimovich, 2011, Current opinion in biotechnology.

Blood transcriptional signatures of multiple sclerosis: Unique gene expression of disease activity

Nir Friedman, Naftali Kaminski, Anat Achiron, 2004, Annals of neurology.

CD4+ T Cell-Receptor Repertoire Diversity is Compromised in the Spleen but Not in the Bone Marrow of Aged Mice Due to Private and Sporadic Clonal Expansions

Wilfred Ndifon, Nir Friedman, Hilah Gal, 2013, Front. Immunol..