Zohar Yakhini
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Zohar Yakhini has a total of 177 co-authors. Here are the top co-authors by number of shared publications:
- Alexander Golberg
Tel Aviv University
8 shared publications - Leon Anavy
School of Computer Science, Reichman University, Herzliya, Israel
8 shared publications - Edward Vitkin
Porter School of Environment and Earth Sciences Tel Aviv University Tel Aviv Israel
7 shared publications Amrita Singh
Department of Environmental Studies, Porter School of Environment and Earth Sciences, Tel Aviv University, Tel Aviv, Israel
4 shared publications- Ben Galili
Department of Computer Science, Technion – Israel Institute of Technology , Haifa 320003
4 shared publications - Hadas Biran
Computer Science Department, Technion - Israel Institute of Technology, Haifa, Israel
4 shared publications
Latest Publications
- Open Access
- 2 September 2026
- Published by Association for Computing Machinery (ACM)
- p. 167
Quantum-Inspired Feature Engineering For Logistic Regression
- 2 September 2026
- Published by Association for Computing Machinery (ACM)
- p. 167
Open AccessQuantum-Inspired Feature Engineering For Logistic Regression
- Open Access
NinjaSeq: programmable restriction enzyme-based sequencing library preparation with random access for DNA data storage
DNA data storage allows sequences to be defined without biological constraints, yet readout workflows still depend on generic end-repair/dA-tailing chemistry. We developed NinjaSeq, a type IIS restriction endonuclease library-preparation strategy that incorporates recognition sites into primer flanks, enabling digestion to generate adapter-compatible overhangs and eliminating the need for conventional end preparation. By combining this chemistry with constrained coding that excludes internal recognition motifs, NinjaSeq produced sequencing quality and decoding performance consistent with standard protocols while reducing reagent burden and simplifying processing, including compatibility with one-pot restriction-ligation. The same sequence-directed design also enables physical random access during library preparation: targeting file-specific flanking sites enriched a desired file from a mixed pool by about sixteen-fold in a proof-of-concept experiment. These results position NinjaSeq as a practical ONT readout approach for DNA data storage.
Open AccessNinjaSeq: programmable restriction enzyme-based sequencing library preparation with random access for DNA data storage
DNA data storage allows sequences to be defined without biological constraints, yet readout workflows still depend on generic end-repair/dA-tailing chemistry. We developed NinjaSeq, a type IIS restriction endonuclease library-preparation strategy that incorporates recognition sites into primer flanks, enabling digestion to generate adapter-compatible overhangs and eliminating the need for conventional end preparation. By combining this chemistry with constrained coding that excludes internal recognition motifs, NinjaSeq produced sequencing quality and decoding performance consistent with standard protocols while reducing reagent burden and simplifying processing, including compatibility with one-pot restriction-ligation. The same sequence-directed design also enables physical random access during library preparation: targeting file-specific flanking sites enriched a desired file from a mixed pool by about sixteen-fold in a proof-of-concept experiment. These results position NinjaSeq as a practical ONT readout approach for DNA data storage.
- Open Access
- 22 March 2026
- Published by MDPI AG in Remote Sensing
- Vol. 18 (6) , 954
High-Resolution Air Temperature Estimation Using the Full Landsat Spectral Range and Information-Based Machine Learning
Accurate mapping of near-surface air temperature () at the fine spatial resolution is required for city-scale monitoring and remains a critical challenge in Earth Observation (EO). Reliance on ground-based measurements is constrained by their sparse spatial coverage and high operational costs. We present a novel, scalable machine learning framework designed to overcome this limitation. Our method utilizes interpretable Convolutional Neural Networks (CNNs) to fuse high-resolution Landsat data, integrating both thermal and reflective spectral bands, with contextual spatiotemporal metadata. This approach allows for inference, at 30 m resolution, of fields without relying on dense, localized ground monitoring networks. Our hybrid CNN architecture is optimized for spatial generalization, maintaining strong and transferable performance (station-wise ) across diverse environments from humid coasts () to arid interiors (). Although focused on a specific geographical region, our results suggest a robust and reproducible pathway for generating spatially consistent temperature fields from globally available EO archives, directly supporting urban heat island mitigation, climate policy development, and high-resolution public health assessment worldwide.- 22 March 2026
- Published by MDPI AG in Remote Sensing
- Vol. 18 (6) , 954
Open AccessHigh-Resolution Air Temperature Estimation Using the Full Landsat Spectral Range and Information-Based Machine Learning
Accurate mapping of near-surface air temperature () at the fine spatial resolution is required for city-scale monitoring and remains a critical challenge in Earth Observation (EO). Reliance on ground-based measurements is constrained by their sparse spatial coverage and high operational costs. We present a novel, scalable machine learning framework designed to overcome this limitation. Our method utilizes interpretable Convolutional Neural Networks (CNNs) to fuse high-resolution Landsat data, integrating both thermal and reflective spectral bands, with contextual spatiotemporal metadata. This approach allows for inference, at 30 m resolution, of fields without relying on dense, localized ground monitoring networks. Our hybrid CNN architecture is optimized for spatial generalization, maintaining strong and transferable performance (station-wise ) across diverse environments from humid coasts () to arid interiors (). Although focused on a specific geographical region, our results suggest a robust and reproducible pathway for generating spatially consistent temperature fields from globally available EO archives, directly supporting urban heat island mitigation, climate policy development, and high-resolution public health assessment worldwide. - Open Access
- 1 January 2026
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Molecular, Biological, and Multi-Scale Communications
- Vol. 12, 1217-1235
A Security Framework for Chemical Functions
- 1 January 2026
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Molecular, Biological, and Multi-Scale Communications
- Vol. 12, 1217-1235
Open AccessA Security Framework for Chemical Functions
- Open Access
- 1 January 2026
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Molecular, Biological, and Multi-Scale Communications
- Vol. 12, 937-946
A Stochastic Performance Analysis Framework for DNA-Based Authentication Protocols
- 1 January 2026
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Molecular, Biological, and Multi-Scale Communications
- Vol. 12, 937-946
Open AccessA Stochastic Performance Analysis Framework for DNA-Based Authentication Protocols
- Open Access
- 31 October 2025
- Published by Oxford University Press (OUP) in Biometrika
- Vol. 113 (1)
Higher criticism for rare and weak non-proportional hazard deviations in survival analysis
We propose a method for comparing survival data based on higher criticism of $ p $-values obtained from many exact hypergeometric tests. The method accommodates noninformative right-censorship and is sensitive to hazard differences in unknown and relatively rare time intervals. It attains much better power against such differences than the log-rank test and its variants. We demonstrate the usefulness of our method in detecting rare and weak non-proportional hazard differences compared to existing tests using simulations and gene expression data. Additionally, we analyse the asymptotic power of our method and other tests under a theoretical framework describing two groups experiencing failure rates that are usually identical over time, except in a few unknown instances where one group’s failure rate is higher. Our test’s power experiences a phase transition across the plane of rarity and intensity parameters that mirrors the phase transition of higher criticism in two-sample rare and weak normal and Poisson means settings. The region of the plane in which our method has asymptotically full power is larger than the corresponding region for the log-rank test.
- 31 October 2025
- Published by Oxford University Press (OUP) in Biometrika
- Vol. 113 (1)
Open AccessHigher criticism for rare and weak non-proportional hazard deviations in survival analysis
We propose a method for comparing survival data based on higher criticism of $ p $-values obtained from many exact hypergeometric tests. The method accommodates noninformative right-censorship and is sensitive to hazard differences in unknown and relatively rare time intervals. It attains much better power against such differences than the log-rank test and its variants. We demonstrate the usefulness of our method in detecting rare and weak non-proportional hazard differences compared to existing tests using simulations and gene expression data. Additionally, we analyse the asymptotic power of our method and other tests under a theoretical framework describing two groups experiencing failure rates that are usually identical over time, except in a few unknown instances where one group’s failure rate is higher. Our test’s power experiences a phase transition across the plane of rarity and intensity parameters that mirrors the phase transition of higher criticism in two-sample rare and weak normal and Poisson means settings. The region of the plane in which our method has asymptotically full power is larger than the corresponding region for the log-rank test.
- 13 August 2025
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 1-9
An Interpretation of Spearman Correlation via k-Subset Permutations
Developed by Charles Spearman in the beginning of the 20 th century, Spearman correlation is a popular method of quantifying rank correlation in many data driven studies and projects. We suggest a new interpretation of Spearman correlation using $k$-subset permutations. We characterize the distribution of the Spearman correlation of a permutation obtained when starting with some initial permutation and then uniformly shuffling a random subset of $k$ indices in that permutation, leaving all other entries unchanged. In this paper, we present some key aspects of the resulting distribution, including its expected value and variance. Specifically, we characterize the dependence on $k, n$, as well as, in some cases, on the initial permutation itself. Our results can potentially be useful in developing a stable statistics framework for Spearman correlation.- 13 August 2025
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 1-9
An Interpretation of Spearman Correlation via k-Subset Permutations
Developed by Charles Spearman in the beginning of the 20 th century, Spearman correlation is a popular method of quantifying rank correlation in many data driven studies and projects. We suggest a new interpretation of Spearman correlation using $k$-subset permutations. We characterize the distribution of the Spearman correlation of a permutation obtained when starting with some initial permutation and then uniformly shuffling a random subset of $k$ indices in that permutation, leaving all other entries unchanged. In this paper, we present some key aspects of the resulting distribution, including its expected value and variance. Specifically, we characterize the dependence on $k, n$, as well as, in some cases, on the initial permutation itself. Our results can potentially be useful in developing a stable statistics framework for Spearman correlation.- Open Access
The Labeled Coupon Collector Problem
We generalize the well-known Coupon Collector Problem (CCP) in combinatorics. Our problem is to find the minimum and expected number of draws, with replacement, required to recover $n$ distinctly labeled coupons, with each draw consisting of a random subset of $k$ different coupons and a random ordering of their associated labels. We specify two variations of the problem, Type-I in which the set of labels is known at the start, and Type-II in which the set of labels is unknown at the start. We show that our problem can be viewed as an extension of the separating system problem introduced by Rényi and Katona, provide a full characterization of the minimum, and provide a numerical approach to finding the expectation using a Markov chain model, with special attention given to the case where two coupons are drawn at a time.Open AccessThe Labeled Coupon Collector Problem
We generalize the well-known Coupon Collector Problem (CCP) in combinatorics. Our problem is to find the minimum and expected number of draws, with replacement, required to recover $n$ distinctly labeled coupons, with each draw consisting of a random subset of $k$ different coupons and a random ordering of their associated labels. We specify two variations of the problem, Type-I in which the set of labels is known at the start, and Type-II in which the set of labels is unknown at the start. We show that our problem can be viewed as an extension of the separating system problem introduced by Rényi and Katona, provide a full characterization of the minimum, and provide a numerical approach to finding the expectation using a Markov chain model, with special attention given to the case where two coupons are drawn at a time. - Open Access
- 2 July 2025
- Published by MDPI AG in Current Issues in Molecular Biology
- Vol. 47 (7) , 507
Cross-Activity Analysis of CRISPR/Cas9 Editing in Gene Families of Solanum lycopersicum Detected by Long-Read Sequencing
CRISPR/Cas9 genome editing holds promise for precise genetic modifications, yet off-target effects remain a concern—particularly in gene families with high sequence similarity. In this study, we present a computational framework for analyzing editing specificity and cross-reactivity in gene families using long-read sequencing data. The pipeline integrates multiplex PCR, NGS, and CRISPECTOR-based analysis to detect and quantify on- and off-target events with high sensitivity. As a use case, we applied this framework to Solanum lycopersicum, evaluating on-target editing in thirteen gene families and analyzing off-target cross-reactivity in five representative families. While the biological results are illustrative, the primary contribution lies in the generalizable analysis approach, which can support genome editing studies in complex plant genomes and beyond.
- 2 July 2025
- Published by MDPI AG in Current Issues in Molecular Biology
- Vol. 47 (7) , 507
Open AccessCross-Activity Analysis of CRISPR/Cas9 Editing in Gene Families of Solanum lycopersicum Detected by Long-Read Sequencing
CRISPR/Cas9 genome editing holds promise for precise genetic modifications, yet off-target effects remain a concern—particularly in gene families with high sequence similarity. In this study, we present a computational framework for analyzing editing specificity and cross-reactivity in gene families using long-read sequencing data. The pipeline integrates multiplex PCR, NGS, and CRISPECTOR-based analysis to detect and quantify on- and off-target events with high sensitivity. As a use case, we applied this framework to Solanum lycopersicum, evaluating on-target editing in thirteen gene families and analyzing off-target cross-reactivity in five representative families. While the biological results are illustrative, the primary contribution lies in the generalizable analysis approach, which can support genome editing studies in complex plant genomes and beyond.