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ScienceOpen Author Interview Series – Carol Perez-Iratxeta

Today’s author interview comes from Carol Perez-Iratxeta ( http://goo.gl/fwloa7 ), a bioinformatics researcher based at the Ottawa Hospital Research Institute (OHRI) in Ottawa, Canada. Her research concerns data mining and computational genomic analysis applied to human disease.

Together with fellow OHRI researcher Caroline Louis-Jeune, as well as Dr. Miguel Andrade, based at the Max Delbrück Center for Molecular Medicine in Berlin, Germany, she has just published an article entitled, „FASTA Herder: a web application to trim protein sequence sets“ on ScienceOpen (http://goo.gl/4qa7Ez ).

-First of all, what prompted you to publish your work with ScienceOpen? Why do you believe in the idea of Open Access publishing platforms for the sciences?

We have always preferred Open Access publishing when possible. More recently, we are receiving the important support of the University of Ottawa library Open Access program: (http://scholarlycommunication.uottawa.ca/open-access ).
They cover OA publication costs through an Author Fund. That makes a difference for us and will translate into institutional savings when open access will be broadly adopted. Universities cannot afford anymore the burden of increasing cost of the traditional publication model.
We thought that your model of open review of SO is very interesting, and we wanted to submit an article.

–Can you describe the research you‘ve published with us?

This is a software tool to help dealing with high redundancy in protein data sets. Protein sequences that share similarities (homologs) are often collected and analyzed together to formulate hypothesis about the proteins’ structures and functions. As more and more genomes are sequenced, this is getting complicated due to the presence of many sequences that are quite similar to others and don’t contribute with much information. Our tool helps to identify and trim these sequences out. As the main difference from other methods that rely just on a high similarity percentage, our method looks for full length homologs, allowing to safely use lower values of similarity percentages.

–What would you say to emerging and junior scholars who are contemplating the publishing landscape for their work?

We are all still too preoccupied about publishing in traditional big journals and their impact factors. This is especially true for junior authors trying to establish themselves, but eventually things have to change and become fairer. It is up to all us to be the agents of that change.