Dataset Information

Phenobook: an open source software for phenotypic data collection.

ABSTRACT: Background:Research projects often involve observation, registration, and data processing starting from information obtained in field experiments. In many cases, these tasks are carried out by several persons in different places, times, and ways, adding different levels of complexity and error in data collecting. Furthermore, data processing can be time consuming, and input errors may produce unwanted results. Results:We have developed a novel, open source software called Phenobook, an easy, flexible, and intuitive tool to organize, collect, and save experimental data for further analyses. Phenobook was conceived to collect phenotypic observations in a user-friendly, cost-effective way. It consists of a web-based software for experiment design, data input and visualization, and exportation, combined with a mobile application for remote data collecting. We provide in this article a detailed description of the developed tool. Conclusion:Phenobook is a software tool that can be easily implemented in collaborative research and development projects involving data collecting and forward analyses. Adopting Phenobook is expected to improve the involved processes by minimizing input errors, resulting in higher quality and reliability of the research outcomes.

SUBMITTER: Crescente JM

PROVIDER: S-EPMC5530315 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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Phenobook: an open source software for phenotypic data collection.

Crescente Juan M JM Guidobaldi Fabio F Demichelis Melina M Formica Maria B MB Helguera Marcelo M Vanzetti Leonardo S LS

GigaScience 20170401 4

<h4>Background</h4>Research projects often involve observation, registration, and data processing starting from information obtained in field experiments. In many cases, these tasks are carried out by several persons in different places, times, and ways, adding different levels of complexity and error in data collecting. Furthermore, data processing can be time consuming, and input errors may produce unwanted results.<h4>Results</h4>We have developed a novel, open source software called Phenoboo ...[more]

PMID: 28327910

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Project description:In order that biological meaning may be derived and testable hypotheses may be built from proteomics experiments, assignments of proteins identified by mass spectrometry or other techniques must be supplemented with additional notation, such as information on known protein functions, protein-protein interactions, or biological pathway associations. Collecting, organizing, and interpreting this data often requires the input of experts in the biological field of study, in addition to the time-consuming search for and compilation of information from online protein databases. Furthermore, visualizing this bulk of information can be challenging due to the limited availability of easy-to-use and freely available tools for this process. In response to these constraints, we have undertaken the design of software to automate annotation and visualization of proteomics data in order to accelerate the pace of research. Here we present the Software Tool for Researching Annotations of Proteins (STRAP), a user-friendly, open-source C# application. STRAP automatically obtains gene ontology (GO) terms associated with proteins in a proteomics results ID list using the freely accessible UniProtKB and EBI GOA databases. Summarized in an easy-to-navigate tabular format, STRAP results include meta-information on the protein in addition to complementary GO terminology. Additionally, this information can be edited by the user so that in-house expertise on particular proteins may be integrated into the larger data set. STRAP provides a sortable tabular view for all terms, as well as graphical representations of GO-term association data in pie charts (biological process, cellular component, and molecular function) and bar charts (cross comparison of sample sets) to aid in the interpretation of large data sets and differential analyses experiments. Furthermore, proteins of interest may be exported as a unique FASTA-formatted file to allow for customizable re-searching of mass spectrometry data, and gene names corresponding to the proteins in the lists may be encoded in the Gaggle microformat for further characterization, including pathway analysis. STRAP, a tutorial, and the C# source code are freely available from http://cpctools.sourceforge.net.

Dataset Information

Phenobook: an open source software for phenotypic data collection.

Publications

Phenobook: an open source software for phenotypic data collection.

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