Volume 10 Supplement 14
Biodiversity Informatics
Research
Edited by Indra Neil Sarkar
Publication of this supplement was made possible thanks to sponsorship from the Encyclopedia of Life and the Consortium for the Barcode of Life.
-
Citation: BMC Bioinformatics 2009 10(Suppl 14):S1
-
Towards a data publishing framework for primary biodiversity data: challenges and potentials for the biodiversity informatics community
Currently primary scientific data, especially that dealing with biodiversity, is neither easily discoverable nor accessible. Amongst several impediments, one is a lack of professional recognition of scientific...
Citation: BMC Bioinformatics 2009 10(Suppl 14):S2 -
Location, location, location: utilizing pipelines and services to more effectively georeference the world's biodiversity data
Increasing the quantity and quality of data is a key goal of biodiversity informatics, leading to increased fitness for use in scientific research and beyond. This goal is impeded by a legacy of geographic loc...
Citation: BMC Bioinformatics 2009 10(Suppl 14):S3 -
Googling DNA sequences on the World Wide Web
New web-based technologies provide an excellent opportunity for sharing and accessing information and using web as a platform for interaction and collaboration. Although several specialized tools are available...
Citation: BMC Bioinformatics 2009 10(Suppl 14):S4 -
bioGUID: resolving, discovering, and minting identifiers for biodiversity informatics
Linking together the data of interest to biodiversity researchers (including specimen records, images, taxonomic names, and DNA sequences) requires services that can mint, resolve, and discover globally unique...
Citation: BMC Bioinformatics 2009 10(Suppl 14):S5 -
Scratchpads: a data-publishing framework to build, share and manage information on the diversity of life
Natural History science is characterised by a single immense goal (to document, describe and synthesise all facets pertaining to the diversity of life) that can only be addressed through a seemingly infinite s...
Citation: BMC Bioinformatics 2009 10(Suppl 14):S6 -
Learning to classify species with barcodes
According to many field experts, specimens classification based on morphological keys needs to be supported with automated techniques based on the analysis of DNA fragments. The most successful results in this...
Citation: BMC Bioinformatics 2009 10(Suppl 14):S7 -
Rapid DNA barcoding analysis of large datasets using the composition vector method
Sequence alignment is the rate-limiting step in constructing profile trees for DNA barcoding purposes. We recently demonstrated the feasibility of using unaligned rRNA sequences as barcodes based on a composit...
Citation: BMC Bioinformatics 2009 10(Suppl 14):S8 -
Efficient alignment-free DNA barcode analytics
In this work we consider barcode DNA analysis problems and address them using alternative, alignment-free methods and representations which model sequences as collections of short sequence fragments (features). T...
Citation: BMC Bioinformatics 2009 10(Suppl 14):S9 -
DNA barcode analysis: a comparison of phylogenetic and statistical classification methods
DNA barcoding aims to assign individuals to given species according to their sequence at a small locus, generally part of the CO1 mitochondrial gene. Amongst other issues, this raises the question of how to de...
Citation: BMC Bioinformatics 2009 10(Suppl 14):S10
Annual Journal Metrics
-
2022 Citation Impact
3.0 - 2-year Impact Factor
4.3 - 5-year Impact Factor
0.938 - SNIP (Source Normalized Impact per Paper)
1.100 - SJR (SCImago Journal Rank)2022 Speed
12 days submission to first editorial decision for all manuscripts (Median)
135 days submission to accept (Median)2022 Usage
6,060,124 downloads
14,511 Altmetric mentions