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Michael Imelfort

dblp:36/7241 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2010
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
comparative genomics
0.112010
CMap3D: a 3D visualization tool for comparative genetic maps · Bioinform. 2010
Bioinformatics and computational biology › genomics › genome visualization
genetic map visualization
0.112010
CMap3D: a 3D visualization tool for comparative genetic maps · Bioinform. 2010

Methods — techniques the papers use, named apart from their topics

3d visualization · 0.1
YearPublicationVenuePosition
2010 CMap3D: a 3D visualization tool for comparative genetic maps
abstract
UNLABELLED: Genetic linkage mapping enables the study of genome organization and the association of heritable traits with regions of sequenced genomes. Comparative genetic mapping is particularly powerful as it allows translation of information between related genomes and gives an insight into genome evolution. A common tool for the storage, comparison and visualization of genetic maps is CMap. However, current visualization in CMap is limited to the comparison of adjacent aligned maps. To overcome this limitation, we have developed CMap3D, a tool to compare multiple genetic maps in three-dimensional space. CMap3D is based on a client/server model ensuring operability with current CMap data repositories. This tool can be applied to any species where genetic map information is available and enables rapid, direct comparison between multiple aligned maps. AVAILABILITY AND IMPLEMENTATION: The software is a stand-alone application written in Processing and Java. Binaries are available for Windows, OSX and Linux, and require Sun Microsystems Java Runtime Environment 1.6 or later. The software is freely available for non-commercial use from http://flora.acpfg.com.au/.
Chris Duran, Zoran Boskovic, Michael Imelfort, Jacqueline Batley, Nicholas A. Hamilton, David Edwards
Bioinform.3
2009 De novo sequencing of plant genomes using second-generation technologies
abstract
The ability to sequence the DNA of an organism has become one of the most important tools in modern biological research. Until recently, the sequencing of even small model genomes required substantial funds and international collaboration. The development of 'second-generation' sequencing technology has increased the throughput and reduced the cost of sequence generation by several orders of magnitude. These new methods produce vast numbers of relatively short reads, usually at the expense of read accuracy. Since the first commercial second-generation sequencing system was produced by 454 Technologies and commercialised by Roche, several other companies including Illumina, Applied Biosystems, Helicos Biosciences and Pacific Biosciences have joined the competition. Because of the relatively high error rate and lack of assembly tools, short-read sequence technology has mainly been applied to the re-sequencing of genomes. However, some recent applications have focused on the de novo assembly of these data. De novo assembly remains the greatest challenge for DNA sequencing and there are specific problems for second generation sequencing which produces short reads with a high error rate. However, a number of different approaches for short-read assembly have been proposed and some have been implemented in working software. In this review, we compare the current approaches for second-generation genome sequencing, explore the future direction of this technology and the implications for plant genome research.
Michael Imelfort, David Edwards
Briefings Bioinform.1