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Omer Berkman

Bio: Omer Berkman is an academic researcher from King's College London. The author has contributed to research in topics: Parallel algorithm & All nearest smaller values. The author has an hindex of 16, co-authored 32 publications receiving 1479 citations. Previous affiliations of Omer Berkman include Google & Tel Aviv University.

Papers
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Journal ArticleDOI
TL;DR: ROOM is shown to accurately predict steady-state metabolic fluxes that maintain flux linearity, in agreement with experimental flux measurements, and to correctly identify short alternative pathways used for rerouting metabolic flux in response to gene knockouts.
Abstract: Predicting the metabolic state of an organism after a gene knockout is a challenging task, because the regulatory system governs a series of transient metabolic changes that converge to a steady-state condition. Regulatory on/off minimization (ROOM) is a constraint-based algorithm for predicting the metabolic steady state after gene knockouts. It aims to minimize the number of significant flux changes (hence on/off) with respect to the wild type. ROOM is shown to accurately predict steady-state metabolic fluxes that maintain flux linearity, in agreement with experimental flux measurements, and to correctly identify short alternative pathways used for rerouting metabolic flux in response to gene knockouts. ROOM's growth rate and flux predictions are compared with previously suggested algorithms, minimization of metabolic adjustment, and flux balance analysis (FBA). We find that minimization of metabolic adjustment provides accurate predictions for the initial transient growth rates observed during the early postperturbation state, whereas ROOM and FBA more successfully predict final higher steady-state growth rates. Although FBA explicitly maximizes the growth rate, ROOM does not, and only implicitly favors flux distributions having high growth rates. This indicates that, even though the cell has not evolved to cope with specific mutations, regulatory mechanisms aiming to minimize flux changes after genetic perturbations may indeed work to this effect. Further work is needed to identify metrics that characterize the complete trajectory from the initial to the final metabolic steady states after genetic perturbations.

487 citations

Journal ArticleDOI
TL;DR: This paper introduces a novel parallel data structure called the recursive star-tree, derived by using recursion in the spirit of the inverse Ackermann function, which allows for extremely fast parallel computations, specifically, $O(\alpha (n)$ time.
Abstract: This paper introduces a novel parallel data structure called the recursive star-tree (denoted “${}^ * $-tree”). For its definition a generalization of the $ * $ functional is used (where for a function $f * f(n) = \min \{ {i|f^{(i)} (n) \leqslant 1} \}$ and $f^{(i)} $ is the ith iterate of f). Recursive ${}^ * $-trees are derived by using recursion in the spirit of the inverse Ackermann function.The recursive ${}^ * $-tree data structure leads to a new design paradigm for parallel algorithms. This paradigm allows for extremely fast parallel computations, specifically, $O(\alpha (n))$ time (where $\alpha (n)$ is the inverse of the Ackermann function), using an optimal number of processors on the (weakest) concurrent-read, concurrent-write parallel random-access machine (CRCW PRAM).These computations need only constant time, and use an optimal number of processors if the following nonstandard assumption about the model of parallel computation is added to the CRCW PRAM: an extremely small number of processor...

221 citations

Proceedings ArticleDOI
01 Feb 1989
TL;DR: It is established that several problems are highly parallelizable and for each of these problems, an optimal 0 (loglogn ) time parallel algorithm on the Common CRCW PRAM model which is the weakest among the CRCWPRAM models is designed.
Abstract: of Results. We establish that several problems are highly parallelizable. For each of these problems, we design an optimal 0 (loglogn ) time parallel algorithm on the Common CRCW PRAM model which is the weakest among the CRCW PRAM models. These problems include: 0 all nearest smaller values, l preprocessing for answering range maxima queries, l several problems in Computational Geometry, l string matching. Until recently, such algorithms were known only for finding the maximum and merging.

126 citations

Journal ArticleDOI
TL;DR: The level-ancestor problem is considered and the Euler tour of the tree and the level of each vertex are given and the only change in result (1) above is that preprocessing time increases to O (log n ).

125 citations

Journal ArticleDOI
TL;DR: An O (log log n ) time optimal parallel algorithm is given for the all nearest smaller values problem and it is shown that any optimal CRCW PRAM algorithm for the triangulation problem requires Ω( log log n) time.

125 citations


Cited by
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Journal ArticleDOI
TL;DR: This primer covers the theoretical basis of the approach, several practical examples and a software toolbox for performing the calculations.
Abstract: Flux balance analysis is a mathematical approach for analyzing the flow of metabolites through a metabolic network. This primer covers the theoretical basis of the approach, several practical examples and a software toolbox for performing the calculations.

3,229 citations

Journal Article
TL;DR: In this survey I have collected everything I could find on graph labelings techniques that have appeared in journals that are not widely available.
Abstract: A graph labeling is an assignment of integers to the vertices or edges, or both, subject to certain conditions. Graph labelings were first introduced in the late 1960s. In the intervening years dozens of graph labelings techniques have been studied in over 1000 papers. Finding out what has been done for any particular kind of labeling and keeping up with new discoveries is difficult because of the sheer number of papers and because many of the papers have appeared in journals that are not widely available. In this survey I have collected everything I could find on graph labeling. For the convenience of the reader the survey includes a detailed table of contents and index.

2,367 citations

Journal ArticleDOI
TL;DR: This protocol provides a helpful manual for all stages of the reconstruction process and presents a comprehensive protocol describing each step necessary to build a high-quality genome-scale metabolic reconstruction.
Abstract: Network reconstructions are a common denominator in systems biology. Bottom–up metabolic network reconstructions have been developed over the last 10 years. These reconstructions represent structured knowledge bases that abstract pertinent information on the biochemical transformations taking place within specific target organisms. The conversion of a reconstruction into a mathematical format facilitates a myriad of computational biological studies, including evaluation of network content, hypothesis testing and generation, analysis of phenotypic characteristics and metabolic engineering. To date, genome-scale metabolic reconstructions for more than 30 organisms have been published and this number is expected to increase rapidly. However, these reconstructions differ in quality and coverage that may minimize their predictive potential and use as knowledge bases. Here we present a comprehensive protocol describing each step necessary to build a high-quality genome-scale metabolic reconstruction, as well as the common trials and tribulations. Therefore, this protocol provides a helpful manual for all stages of the reconstruction process.

1,574 citations

Book ChapterDOI
19 Aug 2001
TL;DR: In this paper, the Subset-Cover framework is proposed for the stateless receiver case, where the users do not (necessarily) update their state from session to session, and sufficient conditions that guarantee the security of a revocation algorithm in this class are provided.
Abstract: We deal with the problem of a center sending a message to a group of users such that some subset of the users is considered revoked and should not be able to obtain the content of the message. We concentrate on the stateless receiver case, where the users do not (necessarily) update their state from session to session. We present a framework called the Subset-Cover framework, which abstracts a variety of revocation schemes including some previously known ones. We provide sufficient conditions that guarantees the security of a revocation algorithm in this class. We describe two explicit Subset-Cover revocation algorithms; these algorithms are very flexible and work for any number of revoked users. The schemes require storage at the receiver of log N and 1/2 log2 N keys respectively (N is the total number of users), and in order to revoke r users the required message lengths are of r log N and 2r keys respectively. We also provide a general traitor tracing mechanism that can be integrated with any Subset-Cover revocation scheme that satisfies a "bifurcation property". This mechanism does not need an a priori bound on the number of traitors and does not expand the message length by much compared to the revocation of the same set of traitors. The main improvements of these methods over previously suggested methods, when adopted to the stateless scenario, are: (1) reducing the message length to O(r) regardless of the coalition size while maintaining a single decryption at the user's end (2) provide a seamless integration between the revocation and tracing so that the tracing mechanisms does not require any change to the revocation algorithm.

1,277 citations

Book ChapterDOI
10 Apr 2000
TL;DR: A very simple algorithm for the Least Common Ancestors problem is presented, dispelling the frequently held notion that optimal LCA computation is unwieldy and unimplementable.
Abstract: We present a very simple algorithm for the Least Common Ancestors problem. We thus dispel the frequently held notion that optimal LCA computation is unwieldy and unimplementable. Interestingly, this algorithm is a sequentialization of a previously known PRAM algorithm.

898 citations