Dana Pe'er

27 papers A* 5A 3B 1Journal 15Unranked 2
YearRankTypeTitle / Venue / Authors
2025 A* conf
Wasserstein Flow Matching: Generative Modeling Over Families of Distributions.
ICML
Doron Haviv, Aram-Alexandre Pooladian, Dana Pe'er, Brandon Amos
2024 J jnl
REUNION: transcription factor binding prediction and regulatory association inference from single-cell multi-omics data.
Bioinform.
Yang Yang, Dana Pe'er
2024 J jnl
Wasserstein Flow Matching: Generative modeling over families of distributions.
CoRR
Doron Haviv, Aram-Alexandre Pooladian, Dana Pe'er, Brandon Amos
2024 A* conf
Wasserstein Wormhole: Scalable Optimal Transport Distance with Transformer.
ICML
Doron Haviv, Russell Zhang Kunes, Thomas Dougherty, Cassandra Burdziak, Tal Nawy, Anna Gilbert, Dana Pe'er
2024 J jnl
Wasserstein Wormhole: Scalable Optimal Transport Distance with Transformers.
CoRR
Doron Haviv, Russell Zhang Kunes, Thomas Dougherty, Cassandra Burdziak, Tal Nawy, Anna Gilbert, Dana Pe'er
2023 A* conf
Gradient Estimation for Binary Latent Variables via Gradient Variance Clipping.
AAAI
Russell Z. Kunes, Mingzhang Yin, Max Land, Doron Haviv, Dana Pe'er, Simon Tavaré
2023 J jnl
scKINETICS: inference of regulatory velocity with single-cell transcriptomics data.
Bioinform.
Cassandra Burdziak, Chujun Julia Zhao, Doron Haviv, Direna Alonso-Curbelo, Scott W. Lowe, Dana Pe'er
2022 J jnl
Gradient Estimation for Binary Latent Variables via Gradient Variance Clipping.
CoRR
Russell Z. Kunes, Mingzhang Yin, Max Land, Doron Haviv, Dana Pe'er, Simon Tavaré
2019 J jnl
A Nonparametric Multi-view Model for Estimating Cell Type-Specific Gene Regulatory Networks.
CoRR
Cassandra Burdziak, Elham Azizi, Sandhya Prabhakaran, Dana Pe'er
2019 J jnl
The emergent landscape of the mouse gut endoderm at single-cell resolution.
Nat.
Sonja Nowotschin, Manu Setty, Ying-Yi Kuo, Vincent Liu, Vidur Garg, Roshan Sharma, Claire S. Simon, Nestor Saiz, Rui Gardner, Stéphane C. Boutet, Deanna M. Church, Pamela A. Hoodless, Anna-Katerina Hadjantonakis, Dana Pe'er
2016 A* conf
Dirichlet Process Mixture Model for Correcting Technical Variation in Single-Cell Gene Expression Data.
ICML
Sandhya Prabhakaran, Elham Azizi, Ambrose J. Carr, Dana Pe'er
2013 A* conf
Can CAD cure cancer?
DAC
Smita Krishnaswamy, Bernd Bodenmiller, Dana Pe'er
2013 J jnl
Learning Bayesian Network Structure from Massive Datasets: The "Sparse Candidate" Algorithm
CoRR
Nir Friedman, Iftach Nachman, Dana Pe'er
2012 J jnl
Learning Module Networks
CoRR
Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller, Nir Friedman
2012 J jnl
Using systems and structure biology tools to dissect cellular phenotypes.
J. Am. Medical Informatics Assoc.
Aris Floratos, Barry Honig, Dana Pe'er, Andrea Califano
2010 J jnl
JISTIC: Identification of Significant Targets in Cancer.
BMC Bioinform.
Felix Sanchez-Garcia, Uri David Akavia, Eyal Mozes, Dana Pe'er
2009 J jnl
Learning Signaling Network Structures with Sparsely Distributed Data.
J. Comput. Biol.
Karen Sachs, Solomon Itani, Jennifer Carlisle, Garry P. Nolan, Dana Pe'er, Douglas A. Lauffenburger
2006 J jnl
MinReg: A Scalable Algorithm for Learning Parsimonious Regulatory Networks in Yeast and Mammals.
J. Mach. Learn. Res.
Dana Pe'er, Amos Tanay, Aviv Regev
2005 J jnl
Learning Module Networks.
J. Mach. Learn. Res.
Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller, Nir Friedman
2004 — conf
Analysis of Signaling Pathways in Human T-Cells Using Bayesian Network Modeling of Single Cell Data.
CSB
Karen Sachs, Omar D. Perez, Dana Pe'er, Garry P. Nolan, David K. Gifford, Tommi S. Jaakkola, Douglas A. Lauffenburger
2003 — —
From gene expression to molecular pathways (מביטוי גנים למסלולים מולקולריים.).
Dana Pe'er
2003 A conf
Learning Module Networks.
UAI
Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller, Nir Friedman
2002 A conf
Minreg: Inferring an active regulator set.
ISMB
Dana Pe'er, Aviv Regev, Amos Tanay
2001 — conf
Inferring subnetworks from perturbed expression profiles.
ISMB (Supplement of Bioinformatics)
Dana Pe'er, Aviv Regev, Gal Elidan, Nir Friedman
2000 J jnl
Using Bayesian Networks to Analyze Expression Data.
J. Comput. Biol.
Nir Friedman, Michal Linial, Iftach Nachman, Dana Pe'er
2000 B conf
Using Bayesian networks to analyze expression data.
RECOMB
Nir Friedman, Michal Linial, Iftach Nachman, Dana Pe'er
1999 A conf
Learning Bayesian Network Structure from Massive Datasets: The "Sparse Candidate" Algorithm.
UAI
Nir Friedman, Iftach Nachman, Dana Pe'er