The 3rd DBCLS BioHackathon: improving life science data integration with Semantic Web technologies.

BACKGROUND: BioHackathon 2010 was the third in a series of meetings hosted by the Database Center for Life Sciences (DBCLS) in Tokyo, Japan. The overall goal of the BioHackathon series is to improve the quality and accessibility of life science research data on the Web by bringing together representatives from public databases, analytical tool providers, and cyber-infrastructure researchers to jointly tackle important challenges in the area of in silico biological research. RESULTS: The theme of BioHackathon 2010 was the 'Semantic Web', and all attendees gathered with the shared goal of producing Semantic Web data from their respective resources, and/or consuming or interacting those data using their tools and interfaces. We discussed on topics including guidelines for designing semantic data and interoperability of resources. We consequently developed tools and clients for analysis and visualization. CONCLUSION: We provide a meeting report from BioHackathon 2010, in which we describe the discussions, decisions, and breakthroughs made as we moved towards compliance with Semantic Web technologies - from source provider, through middleware, to the end-consumer.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Acknowledging contributions to online expert assistance

We present a poster which contains a sequence of a question, answers to this question and comments regarding acknowledging content on BioStar. Biostar.stackexchange.com is a website where questions about Bioinformatics can be asked and answered. Users can also comment on both the questions and the answers. The site is modelled after www.stackoverflow.com (see description from Joel Spolsky), a comparable site for programmers.
 
Users find the site valuable both for answers to questions they have and as a reference. Since the content can also be viewed without registration the site likely reaches a larger audience. For instance, BioStar questions are often referenced on Twitter and FriendFeed. This leads to the question of how contributions to such a site can be measured and how they should be cited on other websites. The site itself has some mechanisms in place, which are mainly meant to encourage users; it uses reputation points and so called badges to recognize the quality of contributions. Reputation points are given by the community, who can up- or down- vote questions and answers. Badges are automatically awarded based on predefined criteria. Users with higher reputation levels can also manage the site itself, for instance by adding tags, editing questions and answers or even closing and deleting them. The reputation mechanism is interesting since it is not automatically given based on input provided but actually decided on by fellow users based on their judgement of the quality.
 
We have used the BioStar website itself to ask “How do you acknowledge Biostar and its contributors in your research output?" (http://biostar.stackexchange.com/questions/6062/) 
Currently (April 2011) this question is still active and in the top-10 of questions with most votes, indicating clear interest by the community for ways to acknowledge content from BioStar. The poster gives some interesting viewpoints on the matter. Some examples indicate how useful BioStar was in practical cases, for instance by showing how multiple consequences from gene variations can be mined, results of which could immediately be applied to real research questions. Of course people wanted to acknowledge BioStar in such cases, and indicated how they did that in practice. Although a paper about BioStar itself was suggested as a useful reference and way to advertise the site, people seem to agree that this is not the best way to acknowledge individual contributions. As an alternative, an example of a citation standard for blogs developed by the National library of medicine is mentioned, which also keeps track of the date (and thus version) of the cited document. The use of the Document Object Identifier was discussed, as a way to get easy links to fixed versions of a question with answers. Although the answers provided are given in the context of the BioStar community, the presented content is applicable to other online resources as well and could provide valid input to other communities

Antioxidant activity of phenolic acids and esters present in red wine on human Low-Density Lipoproteins

To evaluate the antioxidant activity of different phenolic acids and their esters, three types of experiments have been used. Electron paramagnetic resonance (EPR) quantitative analysis was carried out using the acetaldehyde/xanthine oxidase system and Fenton's reaction to generate superoxide and hydroxyl radicals, respectively. In a second test, hydroperoxides generated by Cu2+-catalysed oxidation of low density lipoproteins (LDL) were quantified by a modified iodometric method. In a third assay, LDL were oxidized with Esterbauer's method and modified LDL species were quantified by HPLC. The results show that the esterified phenolic derivatives present a better antioxidant activity, on the lipoperoxidation of LDL, than the corresponding phenolic acids

BioStar: An Online Question & Answer Resource for the Bioinformatics Community

Parnell, Laurence D. et al.Although the era of big data has produced many bioinformatics tools and databases, using them effectively often requires specialized knowledge. Many groups lack bioinformatics expertise, and frequently find that software documentation is inadequate while local colleagues may be overburdened or unfamiliar with specific applications. Too often, such problems create data analysis bottlenecks that hinder the progress of biological research. In order to help address this deficiency, we present BioStar, a forum based on the Stack Exchange platform where experts and those seeking solutions to problems of computational biology exchange ideas. The main strengths of BioStar are its large and active group of knowledgeable users, rapid response times, clear organization of questions and responses that limit discussion to the topic at hand, and ranking of questions and answers that help identify their usefulness. These rankings, based on community votes, also contribute to a reputation score for each user, which serves to keep expert contributors engaged. The BioStar community has helped to answer over 2,300 questions from over 1,400 users (as of June 10, 2011), and has played a critical role in enabling and expediting many research projects. BioStar can be accessed at http://www.biostars.org/.This work was partially supported by NSF grants MCB-0618402 and CCF-0643529 (CAREER), NIH grants 1R55AI065507 – 01A2 and 1 R01 GM083113-01, NIH/NCRR grant number UL1RR033184, and FPI fellowship SAF-2007-63171/BES-2009-017731 from the Ministerio de Educación y Ciencia, Spain. These funders had no role in the design of BioStar, decision to publish, or preparation of the manuscript.Peer reviewe

Robust physical methods that enrich genomic regions identical by descent for linkage studies: confirmation of a locus for osteogenesis imperfecta

<p>Abstract</p> <p>Background</p> <p>The monogenic disease osteogenesis imperfecta (OI) is due to single mutations in either of the collagen genes ColA1 or ColA2, but within the same family a given mutation is accompanied by a wide range of disease severity. Although this phenotypic variability implies the existence of modifier gene variants, genome wide scanning of DNA from OI patients has not been reported. Promising genome wide marker-independent physical methods for identifying disease-related loci have lacked robustness for widespread applicability. Therefore we sought to improve these methods and demonstrate their performance to identify known and novel loci relevant to OI.</p> <p>Results</p> <p>We have improved methods for enriching regions of identity-by-descent (IBD) shared between related, afflicted individuals. The extent of enrichment exceeds 10- to 50-fold for some loci. The efficiency of the new process is shown by confirmation of the identification of the Col1A2 locus in osteogenesis imperfecta patients from Amish families. Moreover the analysis revealed additional candidate linkage loci that may harbour modifier genes for OI; a locus on chromosome 1q includes COX-2, a gene implicated in osteogenesis.</p> <p>Conclusion</p> <p>Technology for physical enrichment of IBD loci is now robust and applicable for finding genes for monogenic diseases and genes for complex diseases. The data support the further investigation of genetic loci other than collagen gene loci to identify genes affecting the clinical expression of osteogenesis imperfecta. The discrimination of IBD mapping will be enhanced when the IBD enrichment procedure is coupled with deep resequencing.</p

Number of downloads for each project tagged with "Bioinformatics" on code.google.com

<p>Implementation of my idea on biostar "Where/how to assess which bioinformatics tools/databases are most used/accessed?" : http://www.biostars.org/p/60334/#60341 . The script gets the projects tagged bioinformatics on google-code and get the number of downloads. Of course, that doesn't give the number of "checkout' of each project, etc...</p

GNU parallel for Bioinformatics: my notebook

<p>This tutorial follows<strong> Ole Tange</strong>’s GNU parallel tutorial ( http://www.gnu.org/software/parallel/parallel_tutorial.html ) but I tried to use some bioinformatics-related  examples (align with BWA, Samtools, etc.. ).</p> <p> </p