Big data is huge. It’s hard to emphasize how important it will be for nearly every aspect of our lives over the next century. The headlines say it all: data is the new oil, the information explosion is the greatest gold rush in history, and data scientist is the “sexiest job in the world.”
These are not exaggerations, though the “sexiness” of a position may be subjective. The most successful companies today were either built with data from the beginning or are overhauled with data science in mind.
But data, however diverse or expansive, does nothing by itself. Curated collections of information are the lifeblood for popular buzzwords that are sometimes used interchangeably (and inaccurately): Deep Learning, machine learning, and artificial intelligence.
Right now the global bioinformatics market is set at around six billion dollars. It is conservatively estimated to exceed 18 billion by 2025. These figures do not take into account the value of therapeutics that are being uncovered with the assistance of bioinformatics techniques; any one of which can be worth considerably more than either of the figures given by the analysts.
Moreover, disruptive technologies can greatly outpace the guesses of financial analysts. Unlike artificial intelligence, which has had more than one discontented winter after a period of irrational exuberance, bioinformatics is moving at a brisk pace and its foundations are in place.
While it is related to artificial intelligence, machine learning and data science are not about getting computers to think. Using self-driving cars as an example, Sergio Bengio, one of the pivotal figures in Deep Learning, explains gives the following example to illustrate the field’s current limitations:
“Humans don’t need to live through many examples of accidents to drive prudently. They can just imagine accidents.”
Imagination lets us generalize and analogize. Getting an AI to do these things even adequately in the real world is a hurdle researchers have not yet cleared. However, bioinformatics does not require software programs to understand why things happen. The techniques needed to extract value from biological data are already here.
If a gene is correlated with responsiveness to a particular cancer treatment, the why of the matter can be figured out at a later date. The patients who will be helped by the insight may be curious about its underlying mechanisms of action, but are probably more interested in if it works.
Algorithms can be trained on vast information repositories to spot patterns and make predictions. In medicine this means they can be used to study the effects of a therapy or help researchers figure out why people react differently to the same therapeutic. This is a necessary step towards creating truly personalized medicine.
What is Bioinformatics?
Bioinformatics is the use of computers to analyze biological data. It is a profoundly interdisciplinary field standing at the intersection of more than a few difficult subjects. It is being used to understand biology on every level: from DNA to RNA to proteins to aetiologies of disease to whole organisms and entire ecosystems. BioViva’s Multiomics Program takes an ensemble approach to uncovering what lies behind health and disease.
These components, the differences between people, and the way they interact with each other, are all crucial to creating a working atlas of human health. Naturally, it will be continuously revised, but with enough data we will begin gleaning insights from it almost immediately.
Bioinformatics helps us rapidly identify relationships between biomarkers and even uncover new ones. It can launch lines of inquiry that may have taken human researchers centuries to uncover.
Understanding the Aging Process
Aging is the root cause of the most devastating diseases in the developed world. There is no area of healthcare that offers a larger market or a greater opportunity to help humanity. As a deeply complex problem, aging can only be satisfactorily addressed with the assistance of bioinformatics.
Like nearly every other aspect of our bodies, aging is not the same for everyone. This is why BioViva is not just using bioinformatics to broadly understand the processes of aging, but leveraging these insights to create personalized health recommendations and personalized treatment plans. Data science may be the number one trend in healthcare, but precision medicine is not far behind.
BioViva’s mission is to apply the power of bioinformatics to human data to unravel the mysteries of aging.
Deep Learning and Artificial Intelligence
An AI recently detected heart failure from a single heartbeat. More impressive was this was done with 100% accuracy. This is an amazing breakthrough, but it’s just the tip of the iceberg. Earlier comments in this article about these fields were not meant to be dismissive. They were only meant to emphasize that bioinformatics is not a speculative endeavor. Deep Learning is already assisting us in unraveling the nuances of biological phenomena and more powerful AIs will soon be joining the fray.
We briefly mentioned the need for curated data. Deep Learning is meant to be more the way people (generally) learn about the real world – unsupervised and without explicit labels on everything. We learn cars can be dangerous if they’re not properly maneuvered; as children we learn a stove is hot and, if we’re lucky, eventually realize other things can burn too.
This all may smack of the abstract and it may seem to have little to do with the topics at hand, but it is crucial for the future. The next steps in fully undressing the mysteries of longevity may require the sorts of synthetic minds described by Bengio in his self-driving car example. All this has to start somewhere and that is why BioViva is launching The Vault.
Welcome to the Vault
Computational analysis of disease biomarkers are pushing the boundaries of precision medicine and longevity research. BioViva Sciences is putting itself at the forefront of this endeavor as it pertains to healthy longevity.
With partner companies like Integrated Health Systems, a clinic dedicated to advancing gene therapy, BioViva is preparing to collect the necessary data to begin furnishing aging research with the analysis it needs to move forward.
BioViva is committed to ensuring the privacy of any data shared with us. We go above and beyond the requirements of HIPAA and GDPR. We are focused on user anonymity and secure data analysis.