Liat Shenhav
Liat Shenhav
Assistant Professor New York University
Verified email at
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FEAST: fast expectation-maximization for microbial source tracking
L Shenhav, M Thompson, TA Joseph, L Briscoe, O Furman, D Bogumil, ...
Nature methods 16 (7), 627-632, 2019
Stochasticity constrained by deterministic effects of diet and age drive rumen microbiome assembly dynamics
O Furman, L Shenhav, G Sasson, F Kokou, H Honig, S Jacoby, T Hertz, ...
Nature communications 11 (1), 1904, 2020
Efficacy of corneal collagen cross-linking for the treatment of keratoconus: a systematic review and meta-analysis
Z Meiri, S Keren, A Rosenblatt, T Sarig, L Shenhav, D Varssano
Cornea 35 (3), 417-428, 2016
Genome-wide methylation data mirror ancestry information
E Rahmani, L Shenhav, R Schweiger, P Yousefi, K Huen, B Eskenazi, ...
Epigenetics & chromatin 10, 1-12, 2017
Context-aware dimensionality reduction deconvolutes gut microbial community dynamics
C Martino, L Shenhav, CA Marotz, G Armstrong, D McDonald, ...
Nature biotechnology 39 (2), 165-168, 2021
GLINT: a user-friendly toolset for the analysis of high-throughput DNA-methylation array data
E Rahmani, R Yedidim, L Shenhav, R Schweiger, O Weissbrod, N Zaitlen, ...
Bioinformatics 33 (12), 1870-1872, 2017
Compositional Lotka-Volterra describes microbial dynamics in the simplex
TA Joseph, L Shenhav, JB Xavier, E Halperin, I Pe’er
PLoS computational biology 16 (5), e1007917, 2020
Naturalization of the microbiota developmental trajectory of Cesarean-born neonates after vaginal seeding
SJ Song, J Wang, C Martino, L Jiang, WK Thompson, L Shenhav, ...
Med 2 (8), 951-964. e5, 2021
BayesCCE: a Bayesian framework for estimating cell-type composition from DNA methylation without the need for methylation reference
E Rahmani, R Schweiger, L Shenhav, T Wingert, I Hofer, E Gabel, E Eskin, ...
Genome biology 19 (1), 1-18, 2018
Modeling the temporal dynamics of the gut microbial community in adults and infants
L Shenhav, O Furman, L Briscoe, M Thompson, JD Silverman, I Mizrahi, ...
PLoS computational biology 15 (6), e1006960, 2019
Resource conservation manifests in the genetic code
L Shenhav, D Zeevi
Science 370 (6517), 683-687, 2020
Re-examining the robustness of voice features in predicting depression: Compared with baseline of confounders
W Pan, J Flint, L Shenhav, T Liu, M Liu, B Hu, T Zhu
PLoS One 14 (6), e0218172, 2019
Statistical considerations in the design and analysis of longitudinal microbiome studies
JD Silverman, L Shenhav, E Halperin, S Mukherjee, LA David
bioRxiv, 448332, 2018
Using stochastic approximation techniques to efficiently construct confidence intervals for heritability
R Schweiger, E Fisher, E Rahmani, L Shenhav, S Rosset, E Halperin
Journal of Computational Biology 25 (7), 794-808, 2018
Contamination source modeling with SCRuB improves cancer phenotype prediction from microbiome data
GI Austin, H Park, Y Meydan, D Seeram, T Sezin, YC Lou, BA Firek, ...
Nature Biotechnology, 1-9, 2023
Quantifying replicability and consistency in systematic reviews
I Jaljuli, Y Benjamini, L Shenhav, OA Panagiotou, R Heller
Statistics in Biopharmaceutical Research 15 (2), 372-385, 2023
Using community ecology theory and computational microbiome methods to study human milk as a biological system
L Shenhav, MB Azad
Msystems 7 (1), e01132-21, 2022
Microdiversity of the Vaginal Microbiome is Associated with Preterm Birth
J Liao, L Shenhav, JA Urban, M Serrano, B Zhu, GA Buck, T Korem
bioRxiv, 2023.01. 13.523991, 2023
Quantifying replicability in systematic reviews: the r-value
L Shenhav, R Heller, Y Benjamini
arXiv preprint arXiv:1502.00088, 2015
A Bayesian framework for estimating cell type composition from DNA methylation without the need for methylation reference
E Rahmani, R Schweiger, L Shenhav, E Eskin, E Halperin
Research in Computational Molecular Biology: 21st Annual International …, 2017
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