InSyBio Suite overview
InSyBio Suite is an integrated platform providing tools for biological data management, secured storage and analysis based on the Cloud model of Software as a Service (SaaS). All the services are delivered through the Internet without requesting clients to purchase any additional equipment or software. InSyBio Suite is competitive because of its valuable analysis tools that cover the most fields of the experimental biological data.
InSyBio Suite tools
The Intracellular interaction analysis tool for analyzing proteins, their interactions and predicting their functionality.
Proteins are the functional components of many cellular processes and the identification of their physical Protein-Protein Interactions (PPIs) is an area of mature academic research. InSyBio Interact enables users to combine a variety of sequential, structural and functional information using a high performance machine learning technique to predict a confidence score for each protein pair. This confidence score indicates the probability of these two proteins to interact. Users are able to tune this confidence score and extract their own datasets as well as obtaining only positives or negative interactions. Moreover, InSyBio Suite also provides visualization and meta-analysis of the Protein Interaction Networks. The protein interaction networks are clustered using a novel methodology to extract information about the protein complexes which the proteins form to perform specific tasks. These complexes and the overall PPI networks may be visualized using an interactive visualization module.
The Non-coding RNA analysis tool for predicting and analyzing non-coding RNAs and miRNA target genes.
Non-coding RNA genes are RNA sequences transcribed from DNA, but not translated to proteins. Their identification as well as the identification of the genes they regulate is a promising research area. Non-coding RNA analysis is conducted by the calculation of the 58 most informative features described in literature and miRNA-miRNA targets interactions analysis by the 125 most informative ones. These analyses along with high performance machine learning techniques allow the computational prediction of miRNA genes and of their target genes. The results are stored in a knowledge base equipped with information retrieval tools which allows users to produce and extract their own datasets.
The Biological networks analysis tool for the meta-analysis and visualization of interaction networks and for the functional characterization of intra-cellular molecules.
Proteins do not function independently but they form structural protein complexes. Their identification and characterization from computational techniques deploying PPI networks is an open problem. A set of four state-of-the-art algorithms (MCL, RNSC) is provided to enable the effective clustering of interaction networks. Users are able to import their data on a user friendly interface, select the parameters for the algorithms and evaluate their results using literature evaluation datasets or their own datasets. Moreover, two basic algorithms for the functional characterization of intra-cellular molecules are provided (MVPA and HDPA algorithms). This module also offers a variety of network analysis (haircut filters, neighborhood analysis) and visualization services.