Tuesday, October 16, 2007

Open Access publishing for Eckerd

As a participant in The Oberlin Group, a consortium of liberal arts college libraries, Eckerd College is a Supporter Level member of Biomed Central (BMC). What does this mean for our researchers? We receive a discount for publishing in any one of 182 peer-reviewed, open access journals published by BMC. As a supporting member, The Oberlin Group has its own Web page, where its researchers are featured. Functionality on the page filters articles that Oberlin Group researchers have published recently, as well as articles that have been accessed the most within a month and a year. This feature provides extra exposure to authors from Oberlin Group institutions.

According to BioMed Central, some of the reasons for publishing in a BMC open-access journal are the speed of publication, international exposure, a highly dedicated promotional process undertaken by BMC, inclusion in major bibliographic indices (e.g., PubMed), and now, and the addition of a Thomson ISI impact factors for some journals. Additional promotion is available through BioMed's "Highly accessed" designation, which can be mentioned as a measurement when authors refer to their work.

Authors for BMC retain copyright over their own work through a Creative Commons license. Work published in BMC journals are made available for free through BMC permanently. Works are archived in various locations so if BMC loses control of its works, open access articles will remain available through other venues.

Some of the recent titles from Oberlin Groups researchers include the following:

Toward the automated generation of genome-scale metabolic networks in the SEED
Matthew DeJongh1, Kevin Formsma1,2, Paul Boillot1, John Gould1, Matthew Rycenga3,4 and Aaron Best2

  1. Department of Computer Science, Hope College
  2. Department of Biology, Hope College
  3. Department of Chemistry, Hope College
  4. Department of Chemistry, University of Washington
BMC Bioinformatics 2007, 8:139 doi:10.1186/1471-2105-8-139

Analysis of the Saccharomyces cerevisiae proteome with PeptideAtlas
Nichole L King, EricWDeutsch, Jeffrey A Ranish, Alexey I Nesvizhskii, James S Eddes, Parag Mallick, Jimmy Eng, Frank Desiere, Mark Flory, Daniel B Martin, Bong Kim, Hookeun Lee, Brian Raught, and Ruedi Aebersold

Abstract: We present the Saccharomyces cerevisiae PeptideAtlas composed from 47 diverse experiments and 4.9 million tandem mass spectra. The observed peptides align to 61% of Saccharomyces Genome Database (SGD) open reading frames (ORFs), 49% of the uncharacterized SGD ORFs, 54% of S. cerevisiae ORFs with a Gene Ontology annotation of 'molecular function unknown', and 76% of ORFs with Gene names. We highlight the use of this resource for data mining, construction of high quality lists for targeted proteomics, validation of proteins, and software development.

Genome Biology 2006, 7:R106 (doi:10.1186/gb-2006-7-11-r106)

No comments: