Easy Biomedical Data Analysis

Our company delivers computational analysis solutions for big data analysis, focused on 'omics data and machine learning.

“Your intuitive web-based platform is perfectly suited for the educational setting and I am excited at the prospect of it being more widely available in this capacity. It has been a great pleasure to work with the Pine Biotech team thus far, and I look forward to our continued collaborations.”

Chris McGowin, LSU HSC

T-Bio: Easy and Intuitive Data Analysis

By hiding complicated mathematical algorithms behind a user-friendly interface, T-BioInfo enables faster and easier analysis, integration, and visualization of different types of big data. As an answer to a multi-source heterogeneous dataset analysis need, T-BioInfo combines many data types as well as many industry-standard and novel algorithms into flexible, interactive, visual pipelines. The platform is designed to eliminate dependency on bioinformaticians and streamline the way big data is collected, analyzed and interpreted.

The approach to analysis and data mining of Big Biomedical Data, we can assist in drug and vaccine discovery in collaboration with medical and scientific research teams, by integrating heterogenous datasets and visualizing association networks. Learn more

Making Your Next Discovery

Pharmaceutical companies and healthcare organizations are turning to genomic, transcriptomic, proteomic, metabolomic and other “omics” data to diagnose and treat various diseases. From cancer to high blood pressure and dementia, networks of intra-cellular regulations can be monitored by looking at -omics data using technology that is becoming cheaper and more precise every year. Discoveries in this field are leading to new treatments and technologies, but they are just the start of a big data revolution in healthcare that will help cure disease, protect us from microorganisms and find new ways to enable healthier and longer lives.

You too can participate in this discovery by learning the logic of biomedical omics data analysis.

Meet Our Instructors, Advisors and Co-Presenters

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Dr. Vladimir Galatenko

Associate Professor of Mathematics
Dario Ghersi

Dr. Dario Ghersi

Biomedical Informatics
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Dr. Lucio Miele

Genetics Department Head
JackLeBien

Jack LeBien

Data Scientist
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Dr. Saaket Varma

Biomedical Data Scientist
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Dr. Leonid Brodsky

Professor of Bioinformatics
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Dr. Claudia Copeland

Educational Content Creator