The advent of new technologies has genomics extending its reach into many diverse fields, from biomedicine to agriculture to clinical diagnostics. Whole-genome sequencing is filling the gap in our understanding of not only genome sequence but also of genome organization, genetic variation, differential gene expression and diverse aspects of transcriptional regulation. The sequencing platforms of today (Next Generation Sequencers) are much more powerful and faster, but they also generate huge volumes of data (Big Data) which needs to be sorted, organised, curated, annotated, integrated, analysed and interpreted. Bioinformaticians have a key role here as they have the necessary combination of biological and informatics knowledge. However, because the technology grew so rapidly, there is a worldwide lack of availability of skilled personnel, which is one of the key factors restraining the growth of this market. This gap in the market has resulted in a bottleneck in terms of data analysis, storage and interpretation, whereby most geneticists and biologists are left struggling to manage their own data due to the sheer volume and complexity of it. Most tools available today require scientists to be well versed in programming and scripting in order to run them, which they are not. Also, due to the diversity of applications in genomics, bioinformaticians rarely have the depth of knowledge required to truly understand the biological “problem” of the researcher, and thus are unable to come up with a practical solution. Our product is a breakthrough solution which aims to target this gap between data production and analysis, specifically in the study of transcriptomics via RNA Sequencing. RNA Sequencing, introduced in 2010, has rapidly established itself as the number one method for transcriptome studies and, in turn, transcriptomics is the most relevant omic science. Our solution is called A.I.R: Artificial Intelligence RNAseq. A.I.R. is the first SaaS (Software as a Service) solution of its kind: an easy-to-use software built with solid scientific methods. A.I.R. is revolutionary in that it is able to solve three important obstacles in the genomics field simultaneously: i. the informatics problem (specifically data storage, automatization of results and duration of analysis) ii. the scientific problem (data interpretation and data integration, as well as providing new bioinformatic and statistical functions) iii. the social problem (the lack of availability of skilled bioinformaticians). The overall objective of this project is to introduce a disruptive innovation that will allow researchers to perform transcriptomics data analysis easily, quickly and affordably. The specific objectives are to improve A.I.R.’s current performance to take it from its current TR7 (trial) stage to its final version, and to carry out a feasibility study to launch A.I.R. into the market.
