Dataset Information

ProtocolNavigator: emulation-based software for the design, documentation and reproduction biological experiments.

ABSTRACT:

Motivation

Experimental reproducibility is fundamental to the progress of science. Irreproducible research decreases the efficiency of basic biological research and drug discovery and impedes experimental data reuse. A major contributing factor to irreproducibility is difficulty in interpreting complex experimental methodologies and designs from written text and in assessing variations among different experiments. Current bioinformatics initiatives either are focused on computational research reproducibility (i.e. data analysis) or laboratory information management systems. Here, we present a software tool, ProtocolNavigator, which addresses the largely overlooked challenges of interpretation and assessment. It provides a biologist-friendly open-source emulation-based tool for designing, documenting and reproducing biological experiments.

Availability and implementation

ProtocolNavigator was implemented in Python 2.7, using the wx module to build the graphical user interface. It is a platform-independent software and freely available from http://protocolnavigator.org/index.html under the GPL v2 license.

SUBMITTER: Khan IA

PROVIDER: S-EPMC4296150 | biostudies-literature | 2014 Dec

REPOSITORIES: biostudies-literature

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Publications

ProtocolNavigator: emulation-based software for the design, documentation and reproduction biological experiments.

Khan Imtiaz A IA Fraser Adam A Bray Mark-Anthony MA Smith Paul J PJ White Nick S NS Carpenter Anne E AE Errington Rachel J RJ

Bioinformatics (Oxford, England) 20140822 23

<h4>Motivation</h4>Experimental reproducibility is fundamental to the progress of science. Irreproducible research decreases the efficiency of basic biological research and drug discovery and impedes experimental data reuse. A major contributing factor to irreproducibility is difficulty in interpreting complex experimental methodologies and designs from written text and in assessing variations among different experiments. Current bioinformatics initiatives either are focused on computational res ...[more]

PMID: 25150250

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Project description:BackgroundBiclustering has been largely applied for the unsupervised analysis of biological data, being recognised today as a key technique to discover putative modules in both expression data (subsets of genes correlated in subsets of conditions) and network data (groups of coherently interconnected biological entities). However, given its computational complexity, only recent breakthroughs on pattern-based biclustering enabled efficient searches without the restrictions that state-of-the-art biclustering algorithms place on the structure and homogeneity of biclusters. As a result, pattern-based biclustering provides the unprecedented opportunity to discover non-trivial yet meaningful biological modules with putative functions, whose coherency and tolerance to noise can be tuned and made problem-specific.MethodsTo enable the effective use of pattern-based biclustering by the scientific community, we developed BicPAMS (Biclustering based on PAttern Mining Software), a software that: 1) makes available state-of-the-art pattern-based biclustering algorithms (BicPAM (Henriques and Madeira, Alg Mol Biol 9:27, 2014), BicNET (Henriques and Madeira, Alg Mol Biol 11:23, 2016), BicSPAM (Henriques and Madeira, BMC Bioinforma 15:130, 2014), BiC2PAM (Henriques and Madeira, Alg Mol Biol 11:1-30, 2016), BiP (Henriques and Madeira, IEEE/ACM Trans Comput Biol Bioinforma, 2015), DeBi (Serin and Vingron, AMB 6:1-12, 2011) and BiModule (Okada et al., IPSJ Trans Bioinf 48(SIG5):39-48, 2007)); 2) consistently integrates their dispersed contributions; 3) further explores additional accuracy and efficiency gains; and 4) makes available graphical and application programming interfaces.ResultsResults on both synthetic and real data confirm the relevance of BicPAMS for biological data analysis, highlighting its essential role for the discovery of putative modules with non-trivial yet biologically significant functions from expression and network data.ConclusionsBicPAMS is the first biclustering tool offering the possibility to: 1) parametrically customize the structure, coherency and quality of biclusters; 2) analyze large-scale biological networks; and 3) tackle the restrictive assumptions placed by state-of-the-art biclustering algorithms. These contributions are shown to be key for an adequate, complete and user-assisted unsupervised analysis of biological data.SoftwareBicPAMS and its tutorial available in http://www.bicpams.com .

Dataset Information

ProtocolNavigator: emulation-based software for the design, documentation and reproduction biological experiments.

Motivation

Availability and implementation

Publications

ProtocolNavigator: emulation-based software for the design, documentation and reproduction biological experiments.

Similar Datasets

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