ANALYZE MULTI-OMICS DATA

Process and analyze BIG MULTI-OMICS data on scale with the T-BioInfo platform. No bioinformatics or coding skills required to start. Extensive educational and research features available.

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Process and Analyze 'Omics Data

The T-BioInfo platform makes analyzing multiple types of data easy. You can use raw files like FASTA, FASTQ, SAM, BAM and many others, making use of gold-standard and proprietary algorithms to align, quantify and prepare meaningful datasets ready for data mining. Each section is organized in logical workflow modules with simple inputs and a point-and-click interface. Separate sections dedicated to supervised and unsupervised machine learning, Multi-Omics Integration and Genome-Wide Associations help extract meaningful insights from the data.

The platform hides the complexity of code-based algorithms behind an intuitive visual interface. The AI-powered guides the user to avoid mistakes and simplify access to complex algorithms. Informative pop-ups explain each method and section in detail, providing the user with an educational experience and helping build out the logical flow. The pop-ups also contain reference links that point to the publication about the method and examples. Algorithms are divided up into logical groups, within each group, there is a number of public domain and proprietary algorithms.

Absolutely no coding required.

Each button represents an algorithm and hides the complexity of building a pipeline by providing a visual interface with informative pop-ups. Some algorithms include optional inputs while most have a default preset that will be sufficient for a typical user. The pipeline options are dynamic, responding to the user’s data input and previous selection.

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Data Mining for any Omics Data

The T-BioInfo platform provides user-friendly and intuitive acces to multiple standard and custom data analysis methods for supervised and unsupervised machine learning. These include decision trees, classification and clustering methods. In addtion, segmentation and data association methods that were custom developed for specific use-cases that are easy to use and integrate into your data analysis workflow.

Meaningful Data Visualization

The T-BioInfo platform provides data processing, analysis and visualization options suited for the data type you are working with. The UCSC Genome Browser can be used to visualize Gene Expression or ChIP-seq data. Other types of data are more complex to visualize. Below is an example of a custom visualization module that allows the user to visualize longitudonal passage data from a CirSeq experiment using Dengue variation between two species. These custom visualizations can help navigate data between various formats in an integrated way and export areas of interest in CSV format for further analysis.

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Multi-omics data-driven approaches are already playing a major role in in oncology and other chronic diseases such as asthma, mental disorders, chronic infectious diseases and diabetes. A great example of the need for multi-omics integration is the complex biology of cancer where cell sub-populations and several levels of regulation contribute to the challenges in precise diagnosis and treatment selection for patients. Often times, studies that start with public-domain databases like TCGA can help focus on a specific area of interest or a mechism that is later studied in cell lines and animal models. Integrating data from these various studies and public-domain resources into an actionable analysis output requires trying various approaches before the final result is obtained.

Cloud Access

No setup or installation – just start using the platform with your own account.

Affordable

Easy and consistent pricing with no scaling up costs and no additional pricing for compute and storage resources.

Accessible Anywhere

Perfect for any device with adaptive features for advanced and beginner users.

Time saver

Even for huge datasets and complex analyses, you will see a huge improvement in speed!

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Behind The Scenes

The founding team has years of experience in big data, bioinformatics and clinical applications. We have established a wide network of collaborators with an international experience to design a comprehensive platform making big omics data analysis and integration affordable and fast.

Physician, Scientist and Philanthropist with a vision for Personalized Medicine and Big Data

Dr. Alfred Tauber

Founder and Visionary

Mathematician and Accomplished PI, Director of the Tauber Bioinformatics Research Center

Dr. Leonid Brodsky

Platform Architect

Mathematician and Chief Scientist overseeing platform development

Vladimir Galatenko

Chief Scientist

Avi has years of platform development experience and a broad view of cutting edge technologies.

Avi Titievsky

Technical Lead