Výsledky vyhledávání - "Shental, Noam"

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Accurate Profiling of Microbial Communities from Massively Parallel Sequencing using Convex Optimization

Autor: Zuk, Or, Amir, Amnon, Zeisel, Amit, Shamir, Ohad, Shental, Noam

We describe the Microbial Community Reconstruction ({\bf MCR}) Problem, which is fundamental for microbiome analysis. In this problem, the goal is to reconstruct the identity and frequency of species comprising a microbial community, using short sequ

Externí odkaz: http://arxiv.org/abs/1309.6919

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Rare-Allele Detection Using Compressed Se(que)nsing

Autor: Shental, Noam, Amir, Amnon, Zuk, Or

Detection of rare variants by resequencing is important for the identification of individuals carrying disease variants. Rapid sequencing by new technologies enables low-cost resequencing of target regions, although it is still prohibitive to test mo

Externí odkaz: http://arxiv.org/abs/0909.0400

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Semi-Supervised Learning -- A Statistical Physics Approach

Autor: Getz, Gad, Shental, Noam, Domany, Eytan

We present a novel approach to semi-supervised learning which is based on statistical physics. Most of the former work in the field of semi-supervised learning classifies the points by minimizing a certain energy function, which corresponds to a mini

Externí odkaz: http://arxiv.org/abs/cs/0604011

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On the Achievable Information Rates of Finite-State Input Two-Dimensional Channels with Memory

Autor: Shental, Ori, Shental, Noam, Shamai, Shlomo

The achievable information rate of finite-state input two-dimensional (2-D) channels with memory is an open problem, which is relevant, e.g., for inter-symbol-interference (ISI) channels and cellular multiple-access channels. We propose a method for

Externí odkaz: http://arxiv.org/abs/cs/0502077

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