Transforming the avalanche of genomic complexity into insightful information streams.
Reproducible -omics data interpretation, i.e. the derivation of actionable molecular biomarkers, is currently the main bottleneck in streamlined applications, obstructing the transformation of genomic information into insights for Biomedicine and Biotech. Interpretation is still largely performed manually and slowly, in contrast to upstream processing of raw -omic data, far more standardized and automated.
Intelligent interpretation of genomic data
Interpretation goes beyond typical genomic data analysis and implies the derivation of few actionable biomarkers and molecular pathways, with causal relation in regard to the phenotype, filtered out of a sea of confounders, i.e. false associations. BioInfoMiner enables data-driven, robust and reproducible interpretation, through an innovative framework that efficiently resolves biological complexity.
A high-performance cloud environment for Intelligent, streamlined analysis of genomic data
Integration of BioInfoMiner with the Seven Bridges Platform enables offers complete genomic data analysis, from raw files to actionable biomarker signatures. Customized state-of-the-art workflows are coupled with BioInfoMiner interpretation analysis for biomarker discovery and target prioritization, including:
- Microarrays (Affymetrix, Illumina)
- Whole Genome Exome Sequencing – Variant calling and prioritization
- RNA Sequencing – Differential Expression analysis with pathway and gene prioritization
- Whole Genome Bisulfite Sequencing – Differential Methylation Analysis with pathway and gene prioritization
- Phage Display – Functional analysis of massive peptide repertoires and rapid critical biomarker identification
(powered by Seven Bridges Genomics Inc)
Selected publications involving BioInfoMiner
Integrative analysis at a fraction of the normal cost and time
Transform your raw (e.g. FASTQ) files to molecular mechanisms and actionable biomarkers, without any expertise in bioinformatics. The results will be directly relevant to your experiment and biologically interpretable. No need for in-house experts in Bioinformatics, Biostatistics or cloud computing. No need for computational infrastructure. Raw data and a description of the experiment (conditions, batches) will be enough.
Reproducibility, robustness and transparency
BioInfoMiner interpretation methodology is based on advanced semantics processing/computational intelligence and exploits constantly updated, codified biological knowledge. It does not aggregate but it processes and integrates information.
The process is genuinely data-driven and ensures robustness and unbiased results. The output, however will evolve together with the accumulation of community knowledge.
Biomarker signatures for comparative analyses and stratification
Derived signatures constitute deconvoluted projections onto biological knowledge networks, corrected for biases and inconsistencies. Thus, they serve as a rational basis for unsupervised and systematic comparison between different physiological conditions.
Wide spectrum of streamlined applications
Applications in the fields of Precision Medicine, Clinics, Molecular Diagnostics, Pharmacogenomics and Agrigenomics. BioInfoMiner works with a variety of organisms of all Kingdoms.