Yaron Orenstein
Yaron Orenstein
School of Electrical and Computer Engineering
Verified email at bgu.ac.il - Homepage
Cited by
Cited by
Evaluation of methods for modeling transcription factor sequence specificity
MT Weirauch, A Cote, R Norel, M Annala, Y Zhao, TR Riley, ...
Nature biotechnology 31 (2), 126-134, 2013
A comparative analysis of transcription factor binding models learned from PBM, HT-SELEX and ChIP data
Y Orenstein, R Shamir
Nucleic acids research 42 (8), e63-e63, 2014
Transcription factor family‐specific DNA shape readout revealed by quantitative specificity models
L Yang, Y Orenstein, A Jolma, Y Yin, J Taipale, R Shamir, R Rohs
Molecular systems biology 13 (2), 910, 2017
ElemeNT: a computational tool for detecting core promoter elements
A Sloutskin, YM Danino, Y Orenstein, Y Zehavi, T Doniger, R Shamir, ...
Transcription 6 (3), 41-50, 2015
Drosophila TRF2 is a preferential core promoter regulator
A Kedmi, Y Zehavi, Y Glick, Y Orenstein, D Ideses, C Wachtel, T Doniger, ...
Genes & development 28 (19), 2163-2174, 2014
RCK: accurate and efficient inference of sequence-and structure-based protein–RNA binding models from RNAcompete data
Y Orenstein, Y Wang, B Berger
Bioinformatics 32 (12), i351-i359, 2016
Comprehensive, high-resolution binding energy landscapes reveal context dependencies of transcription factor binding
DD Le, TC Shimko, AK Aditham, AM Keys, SA Longwell, Y Orenstein, ...
Proceedings of the National Academy of Sciences 115 (16), E3702-E3711, 2018
A deep neural network approach for learning intrinsic protein-RNA binding preferences
I Ben-Bassat, B Chor, Y Orenstein
Bioinformatics 34 (17), i638-i646, 2018
Improving the performance of minimizers and winnowing schemes
G Marçais, D Pellow, D Bork, Y Orenstein, R Shamir, C Kingsford
Bioinformatics 33 (14), i110-i117, 2017
Assessment of algorithms for inferring positional weight matrix motifs of transcription factor binding sites using protein binding microarray data
Y Orenstein, C Linhart, R Shamir
Public Library of Science 7 (9), e46145, 2012
RAP: accurate and fast motif finding based on protein-binding microarray data
Y Orenstein, E Mick, R Shamir
Journal of computational biology 20 (5), 375-382, 2013
Designing small universal k-mer hitting sets for improved analysis of high-throughput sequencing
Y Orenstein, D Pellow, G Marçais, R Shamir, C Kingsford
PLoS computational biology 13 (10), e1005777, 2017
Modeling protein–DNA binding via high-throughput in vitro technologies
Y Orenstein, R Shamir
Briefings in functional genomics 16 (3), 171-180, 2017
Custom DNA microarrays reveal diverse binding preferences of proteins and small molecules to thousands of G-quadruplexes
S Ray, D Tillo, RE Boer, N Assad, M Barshai, G Wu, Y Orenstein, D Yang, ...
ACS chemical biology 15 (4), 925-935, 2020
Compact universal k-mer hitting sets
Y Orenstein, D Pellow, G Marçais, R Shamir, C Kingsford
International Workshop on Algorithms in Bioinformatics, 257-268, 2016
Integrated microfluidic approach for quantitative high-throughput measurements of transcription factor binding affinities
Y Glick, Y Orenstein, D Chen, D Avrahami, T Zor, R Shamir, D Gerber
Nucleic acids research 44 (6), e51-e51, 2016
SELMAP-SELEX affinity landscape MAPping of transcription factor binding sites using integrated microfluidics
D Chen, Y Orenstein, R Golodnitsky, M Pellach, D Avrahami, C Wachtel, ...
Scientific reports 6 (1), 1-13, 2016
Design of shortest double-stranded DNA sequences covering all k-mers with applications to protein-binding microarrays and synthetic enhancers
Y Orenstein, R Shamir
Bioinformatics 29 (13), i71-i79, 2013
Testing eulerianity and connectivity in directed sparse graphs
Y Orenstein, D Ron
Theoretical Computer Science 412 (45), 6390-6408, 2011
A randomized parallel algorithm for efficiently finding near-optimal universal hitting sets
B Ekim, B Berger, Y Orenstein
bioRxiv, 2020
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