InSyBio’s solution for clustering biological networks

Clustering biological networks is extremely significant in the field of molecular biology and its applications as it allows for the functional annotation of cellular molecules and the prediction of physical complexes formulated by proteins and/or RNA molecules.

InSyBio’s scientific team has recently published a new methodology (Gradually Expanding Dense Neighborhoods – GENA) that encompasses several properties, such as handling effectively weighted biological networks and predicting overlapping clusters, which allow it to significantly outperform the state-of-the-art methods.

The Research and Development Manager of InSyBio Christos Dimitrakopoulos, who was the head of this work, has stated that “The computational prediction of protein complexes is becoming more precise and informative. GENA makes realistic assumptions about the underlying molecular mechanisms of the cell“.

The full paper is published by the prestigious journal of Artificial Intelligence in Medicine with the title: “Predicting overlapping protein complexes from weighted protein interaction graphs by gradually expanding dense neighborhoods” and it is available online at  http://dx.doi.org/10.1016/j.artmed.2016.05.006 . The implementation of the code is available upon request (requests should be sent at info@insybio.com) for academic usage only, while it will also be integrated in the next version of InSyBio BioNets tool, which is a web based tool integrated in InSyBio Suite (try it at http://demo.insybio.com).

About InsyBio: InSyBio is a bioinformatics pioneer company in personalized healthcare which focuses on developing computational frameworks and tools for the analysis of complex life-science and biological data. The key objective of our analysis lies in the discovery of predictive integrated biomarkers (biomarkers of various categories) with increased prognostic and diagnostic aspects for personalized Healthcare Industry. Find more details at www.insybio.com

A thorough study of Systemic mechanisms and effects of ionizing radiation

Z. Nikitaki et al. have recently published the article Systemic mechanisms and effects of ionizing radiation: A new ‘old’ paradigm of how the bystanders and distant can become the players in Seminars in Cancer Biology journal (online available at: http://www.sciencedirect.com/science/article/pii/S1044579X16300049 ). “Exposure of cells to any form of ionizing radiation (IR) is expected to induce a variety of DNA lesions , including double strand breaks (DSBs), single strand breaks (SSBs) and oxidation, as well as loss of bases, i.e. abasic sites”  as the authors mention in their article. The main contribution of this article is the collection a detailed list of proteins implicated in either bystander or systemic effects, using improved text-mining and bioinformatics tools. With this analysis the authors have successfully identified DNA damage response and repair pathway (DDR/R) and made protein-protein interaction (PPI) networks. Moreover, the most significant signaling pathways participating in non-targeted effects (NTE) were identified, and “a biophysical hypothesis for the regulation of NTE, based on DNA damage and apoptosis gradients between the irradiation point and various distances corresponding to bystander (5 mm) or distant effects (5 cm)” was formulated.

InSyBio Suite was utilized in this research work to formulate and analyze weighted PPI networks from proteins related to bystander or systemic effects of ionizing radiation. In Specific, InSyBio Interact tool was used to formulate weighted PPI networks from the protein products of genes related to bystander and/or systemic effects of ionizing radiation. InSyBio BioNets tool was then used, to visualize and validate these networks, uncover significant clusters of proteins among them and locate the most significant proteins (biomarkers) for the examined effects of ionizing radiation. A demo version of InSyBio Suite (including InSyBio Interact and InSyBio BioNets tools) is freely available at: http://demo.insybio.com . To gain a free one month evaluation lisence you can contact info@insybio.com.

About InsyBio: InSyBio is a bioinformatics pioneer company in personalized healthcare which focuses on developing computational frameworks and tools for the analysis of complex life-science and biological data. The key objective of our analysis lies in the discovery of predictive integrated biomarkers (biomarkers of various categories) with increased prognostic and diagnostic aspects for personalized Healthcare Industry. Find more details at www.insybio.com

Utmost efficiency in gene expression data and biological networks analysis with InSyBio BioNets

We are extremely happy to announce the launching of the first commercial version of InSyBio BioNets (part of the InSyBio Suite). InSyBio BioNets is an innovative set of tools that provide a user friendly web interface to perform most available analysis steps for gene expression datasets, while also providing a novel systems medicine approach to uncover meaningful biomarkers from them.
InSyBio BioNets facilitates the construction, preprocessing, meta-analysis and visualization of biological networks. Additional tools for parsing/preprocessing gene expression files, and uncovering differential expression biomarkers have been incorporated in InSyBio BioNets to enable the construction and analysis of gene co-expression networks.
With InSyBio BioNets your processes for publishing reliable research works and/or for starting clinical trials for new diagnostic and prognostic tests will be enormously accelerated. InSyBio BioNets possesses the following key properties which can directly and positively affect both the time and efficiency of your research:

• Biomarker discovery using a novel systems medicine approach based on biological network comparison which leads to more compact biomarker sets with increased predictive accuracy;
• Semi-automated web-based analysis of gene expression data and biological network analysis;
• No need for personal supercomputers to perform difficult computing tasks: everything is now executed in our cloud infrastructure with minimum burden on the user’s pc.;
• Flexible analysis: experienced users can select through a variety of provided algorithms and parameters while inexperienced ones can use our fine-tuned default setups;
• Informative biomarkers reports which integrate information from multiple sources (OMIM, GeneCards and so on).

More details about this product (white papers, user manuals, video examples and detailed desctrptions) are provided in InSyBio’s web page: http://www.insybio.com/pages/bionets.
A demo version of InSyBio BioNets is freely available at http://demo.insybio.com.
To request a free one-month license or to request a quote for the full version of InSyBio BioNets please email us at info@insybio.com.

About InsyBio: InSyBio is a bioinformatics pioneer company in personalized healthcare which focuses on developing computational frameworks and tools for the analysis of complex life-science and biological data. The key objective of our analysis lies in the discovery of predictive integrated biomarkers (biomarkers of various categories) with increased prognostic and diagnostic aspects for personalized Healthcare Industry. Find more details at www.insybio.com