scispace - formally typeset
Search or ask a question
Institution

Bar-Ilan University

EducationRamat Gan, Israel
About: Bar-Ilan University is a education organization based out in Ramat Gan, Israel. It is known for research contribution in the topics: Population & Poison control. The organization has 12835 authors who have published 34964 publications receiving 995648 citations. The organization is also known as: Bar Ilan University & BIU.


Papers
More filters
Journal ArticleDOI
J. Craig Venter1, Mark Raymond Adams1, Eugene W. Myers1, Peter W. Li1  +269 moreInstitutions (12)
16 Feb 2001-Science
TL;DR: Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function, with tissue-specific developmental regulation, and with the hemostasis and immune systems are indicated.
Abstract: A 2.91-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method. The 14.8-billion bp DNA sequence was generated over 9 months from 27,271,853 high-quality sequence reads (5.11-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals. Two assembly strategies-a whole-genome assembly and a regional chromosome assembly-were used, each combining sequence data from Celera and the publicly funded genome effort. The public data were shredded into 550-bp segments to create a 2.9-fold coverage of those genome regions that had been sequenced, without including biases inherent in the cloning and assembly procedure used by the publicly funded group. This brought the effective coverage in the assemblies to eightfold, reducing the number and size of gaps in the final assembly over what would be obtained with 5.11-fold coverage. The two assembly strategies yielded very similar results that largely agree with independent mapping data. The assemblies effectively cover the euchromatic regions of the human chromosomes. More than 90% of the genome is in scaffold assemblies of 100,000 bp or more, and 25% of the genome is in scaffolds of 10 million bp or larger. Analysis of the genome sequence revealed 26,588 protein-encoding transcripts for which there was strong corroborating evidence and an additional approximately 12,000 computationally derived genes with mouse matches or other weak supporting evidence. Although gene-dense clusters are obvious, almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence. Only 1.1% of the genome is spanned by exons, whereas 24% is in introns, with 75% of the genome being intergenic DNA. Duplications of segmental blocks, ranging in size up to chromosomal lengths, are abundant throughout the genome and reveal a complex evolutionary history. Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function, with tissue-specific developmental regulation, and with the hemostasis and immune systems. DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 2.1 million single-nucleotide polymorphisms (SNPs). A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average, but there was marked heterogeneity in the level of polymorphism across the genome. Less than 1% of all SNPs resulted in variation in proteins, but the task of determining which SNPs have functional consequences remains an open challenge.

12,098 citations

Journal ArticleDOI
TL;DR: Li-ion battery technology has become very important in recent years as these batteries show great promise as power sources that can lead us to the electric vehicle (EV) revolution as mentioned in this paper.
Abstract: Li-ion battery technology has become very important in recent years as these batteries show great promise as power sources that can lead us to the electric vehicle (EV) revolution. The development of new materials for Li-ion batteries is the focus of research in prominent groups in the field of materials science throughout the world. Li-ion batteries can be considered to be the most impressive success story of modern electrochemistry in the last two decades. They power most of today's portable devices, and seem to overcome the psychological barriers against the use of such high energy density devices on a larger scale for more demanding applications, such as EV. Since this field is advancing rapidly and attracting an increasing number of researchers, it is important to provide current and timely updates of this constantly changing technology. In this review, we describe the key aspects of Li-ion batteries: the basic science behind their operation, the most relevant components, anodes, cathodes, electrolyte solutions, as well as important future directions for R&D of advanced Li-ion batteries for demanding use, such as EV and load-leveling applications.

5,531 citations

Journal ArticleDOI
TL;DR: This work presents a simple and efficient implementation of Lloyd's k-means clustering algorithm, which it calls the filtering algorithm, and establishes the practical efficiency of the algorithm's running time.
Abstract: In k-means clustering, we are given a set of n data points in d-dimensional space R/sup d/ and an integer k and the problem is to determine a set of k points in Rd, called centers, so as to minimize the mean squared distance from each data point to its nearest center. A popular heuristic for k-means clustering is Lloyd's (1982) algorithm. We present a simple and efficient implementation of Lloyd's k-means clustering algorithm, which we call the filtering algorithm. This algorithm is easy to implement, requiring a kd-tree as the only major data structure. We establish the practical efficiency of the filtering algorithm in two ways. First, we present a data-sensitive analysis of the algorithm's running time, which shows that the algorithm runs faster as the separation between clusters increases. Second, we present a number of empirical studies both on synthetically generated data and on real data sets from applications in color quantization, data compression, and image segmentation.

5,288 citations

Proceedings ArticleDOI
23 Jun 2008
TL;DR: A new method for video classification that builds upon and extends several recent ideas including local space-time features,space-time pyramids and multi-channel non-linear SVMs is presented and shown to improve state-of-the-art results on the standard KTH action dataset.
Abstract: The aim of this paper is to address recognition of natural human actions in diverse and realistic video settings. This challenging but important subject has mostly been ignored in the past due to several problems one of which is the lack of realistic and annotated video datasets. Our first contribution is to address this limitation and to investigate the use of movie scripts for automatic annotation of human actions in videos. We evaluate alternative methods for action retrieval from scripts and show benefits of a text-based classifier. Using the retrieved action samples for visual learning, we next turn to the problem of action classification in video. We present a new method for video classification that builds upon and extends several recent ideas including local space-time features, space-time pyramids and multi-channel non-linear SVMs. The method is shown to improve state-of-the-art results on the standard KTH action dataset by achieving 91.8% accuracy. Given the inherent problem of noisy labels in automatic annotation, we particularly investigate and show high tolerance of our method to annotation errors in the training set. We finally apply the method to learning and classifying challenging action classes in movies and show promising results.

3,833 citations

Journal ArticleDOI
15 Apr 2010-Nature
TL;DR: In this paper, the authors develop a framework for understanding the robustness of interacting networks subject to cascading failures and present exact analytical solutions for the critical fraction of nodes that, on removal, will lead to a failure cascade and to a complete fragmentation of two interdependent networks.
Abstract: Complex networks have been studied intensively for a decade, but research still focuses on the limited case of a single, non-interacting network. Modern systems are coupled together and therefore should be modelled as interdependent networks. A fundamental property of interdependent networks is that failure of nodes in one network may lead to failure of dependent nodes in other networks. This may happen recursively and can lead to a cascade of failures. In fact, a failure of a very small fraction of nodes in one network may lead to the complete fragmentation of a system of several interdependent networks. A dramatic real-world example of a cascade of failures ('concurrent malfunction') is the electrical blackout that affected much of Italy on 28 September 2003: the shutdown of power stations directly led to the failure of nodes in the Internet communication network, which in turn caused further breakdown of power stations. Here we develop a framework for understanding the robustness of interacting networks subject to such cascading failures. We present exact analytical solutions for the critical fraction of nodes that, on removal, will lead to a failure cascade and to a complete fragmentation of two interdependent networks. Surprisingly, a broader degree distribution increases the vulnerability of interdependent networks to random failure, which is opposite to how a single network behaves. Our findings highlight the need to consider interdependent network properties in designing robust networks.

3,651 citations


Authors

Showing all 13037 results

NameH-indexPapersCitations
H. Eugene Stanley1541190122321
Albert-László Barabási152438200119
Shlomo Havlin131101383347
Stuart A. Aaronson12965769633
Britton Chance128111276591
Mark A. Ratner12796868132
Doron Aurbach12679769313
Jun Yu121117481186
Richard J. Wurtman11493353290
Amir Lerman11187751969
Zhu Han109140748725
Moussa B.H. Youdim10757442538
Juan Bisquert10745046267
Rachel Yehuda10646136726
Michael F. Green10648545707
Network Information
Related Institutions (5)
University of Maryland, College Park
155.9K papers, 7.2M citations

93% related

Rutgers University
159.4K papers, 6.7M citations

93% related

University of Illinois at Urbana–Champaign
225.1K papers, 10.1M citations

93% related

Boston University
119.6K papers, 6.2M citations

92% related

Pennsylvania State University
196.8K papers, 8.3M citations

92% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023117
2022330
20212,286
20202,157
20191,920
20181,768