-: So my name's Jeff Robinson, I'm a bioinformatician,
and I also teach as an adjunct professor
here at the UMBC Universities at Shady Grove Campus.
I use software applications and programming
to analyze biomedical data,
especially large scale data such as genome data
and transcriptome data,
and statistics.
Nowadays we're moving into data science
and artificial intelligence.
For example, 23andMe data,
which is you give them a saliva sample,
and they analyze all the single point mutations
in the genome, and find out
what your specific differences are,
which mutations that you or your family has,
and that can be applied to
a wide range of biological topics, for example, diseases.
We would collect biological samples,
for example, blood samples from a clinical population,
we'd have a certain number of people
that were healthy individuals, or healthy controls,
and then certain number of people
that have a particular disease.
And we would take their bio samples,
in this case let's just say it's a blood sample,
and extract the DNA, and lab DNA or RNA.
And we would take that data and use our bioinformatics tools
to analyze that, and basically compare
what variations in the genome data correspond,
or are associated with the disease state,
or what variations in RNA expression correspond,
or are associated with the disease state.
The volume of that data requires
some special analysis that aren't commonly done
in the more standard type of data analysis,
so that's kind of the realm of bioinformatics.
I'm kinda more moving into the independent research phase
of my career, so I do have a lot of flexibility
of where I can go to do my analysis.
And so in those times that you do a lot of data analysis
for example, you don't necessarily have to be on site
to do that, you just basically need a terminal
and access to the cloud computing resources.