Open-source research

It is essential that, with the use of evidence-based medicine to inform decisions in health care, the processes used in program development be as transparent as possible. Information about the limited evidence and inherent uncertainty should be disclosed and available for scrutiny, even within the software itself. In fact, in an attempt to maximize transparency, some have advocated open source development and publication of interactive software models [49, 50]. Certainly, details of methodologies, sources, and other techniques employed for development of the underlying models must be acknowledged. However, the proprietary nature of many of these programs must be taken into consideration and measures put into place to ensure confidentiality. Requested publication of all NIH-sponsored research online (in PubMed) [51] within a reasonable time frame after journal acceptance will help to ensure that these data are available in the public domain in short order. 

MOREHyS was developed by the German-French Institute for Environmental Research (DFIU/IFARE), in Karlsruhe (Germany), in co-operation with the Fraunhofer Institute for System and Innovation Research (ISI) (Karlsruhe) (Ball, 2006 Ball el al., 2006 Kienzle, 2005). MOREHyS is based on the open-source BALMOREL model (Baltic model of regional energy market liberalisation), which was initially developed... 

J. Wright and A. Wagner, The systems biology research tool Evolvable open source software. BMC Syst. Biol. 2, 55 (2008). 

CellProfiler and CellProfiler Analyst are free Open Source software for automated image analysis, data visualization, and machine learning. Versions for Mac, Windows, and Linux are available and both software can be downloaded at http //www.cellprofiler. org. CellProfiler was developed by Anne Carpenter and Thouis Jones in the laboratory of David Sabatini at the Whitehead Institute for Biomedical Research and by Polina Golland at the CSAIL of the MIT. 

The corresponding drawback of using volunteers is that the supply is more or less fixed. Paying researchers to volunteer turns open source into a grant model. 

GraphViz Stephen C. North—AT T Labs Research Open-source graph visualization software (http //www.graphviz.org/)... 

Munos B (2006) Can open-source R D reinvigorate drug research Nat Rev Drug Discov 5(9) 723-729... 

Bio-Spice, Defense Advanced Research Projects Agency (DARPA). URL https //community.biospice.org/. Open source framework and software toolset for systems biology. 

The BioPerl, BioJava, BioPython, BioRuby, BioCorba, and BioPipe [20] family of packages are facilitated by the Open Bioinformatics Foundation to provide open source modules and scripts for life science research in the major programming languages of bioinformatics. 

Software architecture used in discovery informatics is characterized by its diversity. It is rare to find an environment used in target identification and validation that consists solely of commercial off-the-shelf software. In most cases the research environment consists of a variety of commercial, open-source, and locally developed software packages. HTML and Web technologies are often used as a mechanism to integrate these disparate environments. One aspect of research IT is its datacentric nature, often involving a wide variety and types of data in unstructured and semis-tructured textual forms and in structured forms as relational and object-oriented... 

The use of open source tools is one way to investigate how you might use a workflow system without having to make any cash investment. They can provide a workable system for an individual researcher or a small group, if you are able to supply the software development and IT skill set (with the necessary time) to configure and extend the system and to handle low-level administration. 

We make our research based on the information that we can obtain in open sources. Also we take into account the veracity and credibility of each one of the sources consider to make the study. 

In order for the code to be applicable to mixtures consisting of a wide and expandable number of compounds, we decided to store all data in a relational database and to provide a variety of access methods to that database. In fact, any database that can be accessed by Perl-DBI or ODBC methods (which include all major commercial and open source products) can be used to store compound data. Since many of these databases are network-accessible, the HCToolkit framework can be driven by a common institution-wide (or multi-institution) database to ensure consistency of properties and mixtures in a calculation. We also store mixture information in the database to ease collaboration in studying specific compositions. Hence, all researchers in a specific institution can connect to the same database, and all can use consistent fluid compositions (e.g. fluid 72 ) in numeric simulations. 

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