Systems and Methods for Annotating Biomolecule Data

Abstract

Systems, methods, software and computer-usable media for annotating biomolecule-related data are disclosed. In certain exemplified embodiments, the biomolecules can be nucleic acids and the data can be sequence-related data. In various embodiments, systems can include one or more public or private biological attributes (e.g., annotation information databases, data storage devices and systems, etc.) sources, one or more genomic features data sources (e.g., genomic variant tools, genomic variant databases, genomic variant data storage devices and systems, etc.), a computing device (e.g., workstation, server, personal computer, mobile device, etc.) hosting an annotations module and / or a reporting module, and a client terminal.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS[0001]This application claims priority to U.S. Ser. No. 61 / 406,548, filed Oct. 25, 2010, and U.S. Ser. No. 61 / 482,325, filed May 4, 2011, the disclosures of which are hereby incorporated herein by reference in their entirety as if set forth fully herein.FIELD[0002]The present disclosure relates to biomolecule-related data, and in particular to systems, methods, software and computer-usable media for annotating genomic variant-related data.INTRODUCTION[0003]Upon completion of the Human Genome Project, one focus of the sequencing industry has shifted to finding higher throughput and / or lower cost nucleic acid sequencing technologies, sometimes referred to as “next generation” sequencing (NGS) technologies. In making sequencing higher throughput and / or less expensive, the goal is to make the technology more accessible for sequencing. These goals can be reached through the use of sequencing platforms and methods that provide sample preparation for ...

AI Technical Summary

Problems solved by technology

While the quantity of nucleic acid sequence data that one can gather using conventional sequencing techniques is very large, it can often not be presented or analyzed in the most useful context.

Conventional techniques do not facilitate easy identification of these types of candidate gene mutations.

This is due to the enormous amount of information being generated by the researchers, and the lack of adequate tools to organize the information in a manner which facilitates analysis of the information.

However, the information provided by the various sources of information identified above and other sources has not been integrated in a coherent manner conducive to identification of candidate genes.

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