Journal Article

Biodiversity informatics: automated approaches for documenting global biodiversity patterns and processes

Robert Guralnick and Andrew Hill

in Bioinformatics

Volume 25, issue 4, pages 421-428
Published in print February 2009 | ISSN: 1367-4803
Published online January 2009 | e-ISSN: 1460-2059 | DOI:
Biodiversity informatics: automated approaches for documenting global biodiversity patterns and processes

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Motivation: Data about biodiversity have been scattered in different formats in natural history collections, survey reports and the literature. A central challenge for the biodiversity informatics community is to provide the means to share and rapidly synthesize these data and the knowledge they provide us to build an easily accessible, unified global map of biodiversity. Such a map would provide raw and summary data and information on biodiversity and its change across the world at multiple scales.

Results: We discuss a series of steps required to create a unified global map of biodiversity. These steps include: building biodiversity repositories; creating scalable species distribution maps; creating flexible, user-programmable pipelines which enable biodiversity assessment; and integrating phylogenetic approaches into biodiversity assessment. We show two case studies that combine phyloinformatic and biodiversity informatic approaches to document large scale biodiversity patterns. The first case study uses data available from the Barcode of Life initiative in order to make species conservation assessment of North American birds taking into account evolutionary uniqueness. The second case study uses full genomes of influenza A available from Genbank to provide an auto-updating documentation of the evolution and geographic spread of these viruses.

Availability: Both the website for tracking evolution and spread of influenza A and the website for applying phyloinformatics analysis to Barcode of Life data are available as outcomes of case studies (


Journal Article.  6627 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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