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PhyleasProg: a user-oriented web server for wide evolutionary analyses.

ABSTRACT: Evolutionary analyses of biological data are becoming a prerequisite in many fields of biology. At a time of high-throughput data analysis, phylogenetics is often a necessary complementary tool for biologists to understand, compare and identify the functions of sequences. But available bioinformatics tools are frequently not easy for non-specialists to use. We developed PhyleasProg (http://phyleasprog.inra.fr), a user-friendly web server as a turnkey tool dedicated to evolutionary analyses. PhyleasProg can help biologists with little experience in evolutionary methodologies by analysing their data in a simple and robust way, using methods corresponding to robust standards. Via a very intuitive web interface, users only need to enter a list of Ensembl protein IDs and a list of species as inputs. After dynamic computations, users have access to phylogenetic trees, positive/purifying selection data (on site and branch-site models), with a display of these results on the protein sequence and on a 3D structure model, and the synteny environment of related genes. This connection between different domains of phylogenetics opens the way to new biological analyses for the discovery of the function and structure of proteins.

SUBMITTER: Busset J

PROVIDER: S-EPMC3125726 | biostudies-literature | 2011 Jul

REPOSITORIES: biostudies-literature

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PhyleasProg: a user-oriented web server for wide evolutionary analyses.

Busset Joël J Cabau Cédric C Meslin Camille C Pascal Géraldine G

Nucleic acids research 20110429 Web Server issue

Evolutionary analyses of biological data are becoming a prerequisite in many fields of biology. At a time of high-throughput data analysis, phylogenetics is often a necessary complementary tool for biologists to understand, compare and identify the functions of sequences. But available bioinformatics tools are frequently not easy for non-specialists to use. We developed PhyleasProg (http://phyleasprog.inra.fr), a user-friendly web server as a turnkey tool dedicated to evolutionary analyses. Phyl ...[more]

PMID: 21531699

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Project description:MotivationLife stories of diseased and healthy individuals are abundantly available on the Internet. Collecting and mining such online content can offer many valuable insights into patients' physical and emotional states throughout the pre-diagnosis, diagnosis, treatment and post-treatment stages of the disease compared with those of healthy subjects. However, such content is widely dispersed across the web. Using traditional query-based search engines to manually collect relevant materials is rather labor intensive and often incomplete due to resource constraints in terms of human query composition and result parsing efforts. The alternative option, blindly crawling the whole web, has proven inefficient and unaffordable for e-health researchers.ResultsWe propose a user-oriented web crawler that adaptively acquires user-desired content on the Internet to meet the specific online data source acquisition needs of e-health researchers. Experimental results on two cancer-related case studies show that the new crawler can substantially accelerate the acquisition of highly relevant online content compared with the existing state-of-the-art adaptive web crawling technology. For the breast cancer case study using the full training set, the new method achieves a cumulative precision between 74.7 and 79.4% after 5 h of execution till the end of the 20-h long crawling session as compared with the cumulative precision between 32.8 and 37.0% using the peer method for the same time period. For the lung cancer case study using the full training set, the new method achieves a cumulative precision between 56.7 and 61.2% after 5 h of execution till the end of the 20-h long crawling session as compared with the cumulative precision between 29.3 and 32.4% using the peer method. Using the reduced training set in the breast cancer case study, the cumulative precision of our method is between 44.6 and 54.9%, whereas the cumulative precision of the peer method is between 24.3 and 26.3%; for the lung cancer case study using the reduced training set, the cumulative precisions of our method and the peer method are, respectively, between 35.7 and 46.7% versus between 24.1 and 29.6%. These numbers clearly show a consistently superior accuracy of our method in discovering and acquiring user-desired online content for e-health research.Availability and implementationThe implementation of our user-oriented web crawler is freely available to non-commercial users via the following Web site: http://bsec.ornl.gov/AdaptiveCrawler.shtml. The Web site provides a step-by-step guide on how to execute the web crawler implementation. In addition, the Web site provides the two study datasets including manually labeled ground truth, initial seeds and the crawling results reported in this article.

Dataset Information

PhyleasProg: a user-oriented web server for wide evolutionary analyses.

Publications

PhyleasProg: a user-oriented web server for wide evolutionary analyses.

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