Coupled with the Ability to Make Specified Autonomous Decisions,
The Automation of Complex Workflow Tasks Can Enable Unprecedented
Productivity in the Field of Genomics
The last decade bore witness to major advancements in human genomics. However, the remaining challenges involve the development of technologies that utilize the glut of data output from these sequencing platforms towards actionable insights. With technologies like high throughput screening (HTS) and next generation sequencing (NGS), a huge amount of biological data is getting generated. To keep pace with the massive speed and data overload of these systems, a technology is needed to swiftly sift through already known facts, and use this information to ‘identify’ as well as ‘tag’ genes, antibodies or active compounds of importance in real-time data. To accomplish such varied and complex tasks, knowledge work automation will need to pave the way for intelligent software and algorithms that have the ability to ‘learn on the ?y.’
Employing medical machine learning, arti?cial neural networks and intelligent programs created to mimic human problem solving skills, the ‘Automation of Knowledge’ solution has the ability to efficiently handle and retrieve relevant scientific information from research publications or large scale biological data. It identifies biomedical entities of interest using a context specific analysis and it develops efficient algorithms to process text and make information accessible to computer applications. It has the ability to create a map of relations/concepts between the bio-medical entities, and it provides the corpus of annotations which can be grouped or classified based on the relationship between the entities. In the context of NGS, the automation of complex workflow tasks, coupled with the ability to make specified autonomous decisions, can enable unprecedented productivity.
The volume of literature in the field of genomics, measured in bytes, is about ?fty times the size of the entire human genome. Locked in this literature is an enormous amount of information. To make full use of such information for diagnostic and prognostic purposes, it is imperative that signi?cant ?ndings be annotated to generate a rich database of biological entities and relationships. This is why Optra’s ‘Automation of Knowledge’ solution for capturing information from genomics studies is such a useful tool for bridging the gap.
The ‘Automation of Knowledge’ tool can be exploited by a number of end users, both in the research and clinical settings. This invaluable tool can create robust databases for clinically significant variants and mutations responsible for inherited disorders, drug-gene interactions, epigenetic markers for research, developing automated frameworks for annotations of pathological reports, and for generating personalized risk reports for prenatal screening or counseling for diagnostic labs.
The ‘Automation of Knowledge’ solution for NGS, a market forecasted to grow from
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