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Elenie Godzaridis

Researcher at Bentley Systems

Publications -  9
Citations -  1887

Elenie Godzaridis is an academic researcher from Bentley Systems. The author has contributed to research in topics: Clipping (computer graphics) & Genome. The author has an hindex of 4, co-authored 9 publications receiving 1749 citations. Previous affiliations of Elenie Godzaridis include Laval University.

Papers
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Journal ArticleDOI

Assemblathon 2: evaluating de novo methods of genome assembly in three vertebrate species

Keith Bradnam, +95 more
- 23 Jan 2013 - 
TL;DR: The Assemblathon 2 as mentioned in this paper presented a variety of sequence data to be assembled for three vertebrate species (a bird, a fish, and a snake) from 21 participating teams.
Journal ArticleDOI

Assemblathon 2: evaluating de novo methods of genome assembly in three vertebrate species

Keith Bradnam, +98 more
- 22 Jul 2013 - 
TL;DR: The Assemblathon 2 as discussed by the authors presented a variety of sequence data to be assembled for three vertebrate species (a bird, a fish, and a snake) from 21 participating teams.
Journal ArticleDOI

Ray Meta: scalable de novo metagenome assembly and profiling

TL;DR: Voluminous parallel sequencing datasets, especially metagenomic experiments, require distributed computing for de novo assembly and taxonomic profiling, and Ray Meta is a massively distributed metagenome assembler that is coupled with Ray Communities, which profiles microbiomes based on uniquely-colored k-mers.
Journal ArticleDOI

Human Analysts at Superhuman Scales: What Has Friendly Software To Do?

TL;DR: Ray, the group's usable, scalable genome assembler, addresses big data problems by using optimal resources and producing one, correct and conservative, timely solution, and RayPlatform, a parallel message-passing software framework that runs on clouds, supercomputers, and desktops alike.
Patent

Hybrid mesh from 2.5D and 3D point data

TL;DR: In this article, a hybrid spatial index is proposed for reconstructing and analyzing a mesh surface based on a combination of 2.5D and 3D point data, whose branching is adapted to specific types of data.