Lately, the Healthcare industry is seeing new technologies that are useful for measuring things and which are generating lots of data but it is hard (if not impossible) to process all this data and make full sense of it and share it.
Companies are currently creating tools to analyze all this data but there is yet to be something for personal use and I believe it is hard to use these in the medical field as well, and these will improve in the future. Expect to see visualizations on a phone or tablet and driven by the cloud (for computing). The cloud could address this by providing massive parallel computing.
I’ll talk more later about big data, but will now focus on one aspect of this data.
Good old Wikipedia has this definition: http://en.wikipedia.org/wiki/Omics
Here is an incredible story about Dr. Snyder who watched as his body developed diabetes : http://med.stanford.edu/ism/2012/march/snyder.html
Taken from that web-page: “The researchers call the unprecedented analysis, which relies on collecting and analyzing billions of individual bits of data, an integrative Personal “Omics” Profile, or iPOP.
The word “omics” indicates the study of a body of information, such as the genome (which is all DNA in a cell), or the proteome (which is all the proteins). Snyder’s iPOP also included his metabolome (metabolites), his transcriptome (RNA transcripts) and autoantibody profiles, among other things.
I prefer this definition to what wikipedia has.
As I see it, omics is the study of data and I guess calling it iPOP makes it more personal.
Researchers say that this data can lead to identification and prediction of conditions. How it becomes information is part of processing it. This is a subtle but major distinction. Data becomes information through analysis.
An exhaustive list of omics can be found at: http://en.wikipedia.org/wiki/List_of_omics_topics_in_biology, but the following omics are mainly talked about:
Genomics – study of genome
Proteomics – study of proteins
Metabololomics – study of metabolism
One item missing in there is Microbiomics, and I believe you will hear a lot about the Microbiome in the future. This is the study of the microbes in our gut and body and how they might cause certain (disease) conditions in our body.
Right now, genetics mainly depends more on observation and deduction, whereby scientists have identified certain gene or set of genes based on observation and co-relating mutations to a certain condition.
As computing power increases and so does memory, I think things will evolve to provide the cause on a molecular basis, i.e. which is what exactly happens in chemical terms when a gene has a mutation.
Also, in genetics many companies sequence the genome but are moving to the exome to expand their predictions. The exome contains all the genes of the body and consists of large amounts of data as opposed to the genome which is a small subset of the genes considered relevant in humans (based on what science knows currently).
Genetics is offered as genomics (for a few hundred dollars) by many direct-to-consumer companies who will offer exome data by the end of the year (for under a thousand dollars) and then there is epigenetics which is the study of RNA and how they can activate genes.
Also, there is the Connectome which maps the neural connections, and is becoming more and more important now. It is defined here – http://en.wikipedia.org/wiki/Connectome
A good talk about at TED – http://www.ted.com/talks/sebastian_seung.html
The Economist had an article about it – http://www.economist.com/node/13437729?story_id=13437729
Wired wrote about it a long time ago – http://www.wired.com/science/discoveries/news/2008/01/connectomics?currentPage=all
Omics leads to big data, and I will write about in the future but this can benefit us by helping to understand health conditions better and curing and predicting them in the future…