Women in STEM Careers


>>From the Library of
Congress in Washington, DC.>>Sasha Dowdy: My
name is Sasha, I work here in the Library of
Congress Young Readers Center and I hope that you’re
enjoying your visit to the library so far. Who’s been here before? Oh good. And your first
then the two of you, welcome so glad you’re here. So we have a pop quiz
for you guys kind of. Pop quiz slash fun
facts how about that? Okay, so in the Library of
Congress we have millions of things okay, we have
millions and millions of items and of course we have books. So do you know what
other items we might have in the library’s collections? Yeah. [ Inaudible ] What’s that? [ Inaudible ] Fossils, I think we do yeah. [ Inaudible ] Sculptures for sure.>>Art.>>Sasha Dowdy: Art. Yeah, we have all kinds
of photographs and artwork and prints and everything. Yeah. [ Inaudible ] We have so many old
items from way back when. You saw the museum
part, that’s awesome. Yeah. [ Inaudible ] Journals, yeah absolutely. We also have maps, 5 million
maps in fact and a total of about 167 million
of things of all kinds. We even have flutes, we
have a ton of flutes, we have real expensive violins,
Stradivarius violins and cellos. So we have all kinds of stuff
and we’re going to show you some of it as we talk
to some scientists to celebrate women
in science today. So I am really happy
to introduce you guys to two scientists and
the first one is going to speak first Dr.
Svetlana Kotliarova. She got her PhD in human
genetics from Tokyo University and now she is a scientific
review officer at NIH. Have you guys heard
of NIH before? It stands for National
Institutes of Health. And she’ll tell you a little
bit more about what kind of work she does there and
how she got where she is now and what kind of work
she’s doing there. So how about we welcome Dr. K. [ Applause ]>>Dr. Svetlana Kotliarova:
Thank you very much for inviting me today and thank
you Sasha for introduction. So it’s a great honor to be here and to speak with
you, our future. So and I hope that I will
infuse some excitement into you about science. So everyone has science class?>>Yes.>>Dr. Svetlana Kotliarova:
Yeah. So you like science? That’s great, that’s great,
so half of the job is done. Actually I forgot I wanted to
start with saying good morning.>>Good morning.>>Dr. Svetlana Kotliarova:
[Foreign language]. This is good morning in Russian. And as you already figured
out I came from Russia. So I was born in the Ural
Mountains in the like kind of central or closer to
Moscow side of Russia. And everyone heard about
Moscow, but maybe not so much about Russia so I show you
something about my hometown. So the city of Ufa is in the
mountains, Ural Mountains and we have a lot
of nice nature, a lot of nice pictures you
can take there if you ever go. And this inspired
me to learn more about living things,
about life science. And this is a monument very
famous, it’s the national hero of Bashkir people,
so Ufa is capital of Bashkir Republic
inside of Russia. And Bashkir about 30%
people who live there. And they have their
special national clothing. And this is how it
maybe looks now snow, there is still snow there. So these are some
pictures from my childhood. So this is our very modest and old apartment building,
this is where I grew. And this is my baby sister and
maybe you figure this is me. So how old are you guys?>>Twelve.>>Dr. Svetlana Kotliarova:
Twelve, this is about me, this is me at your age. So and this is I’m
wearing one of my dresses, I have two dresses, one
was [inaudible] to wash and another I was wearing. And this is my school, I
liked school very much. I went there to meet my
friends and grade teachers who inspired me and who
teach me all the good things that I can use in my life. And I’m thankful for everyone
who taught me all of this. And this is me helping my mom
after school drying clothes. So we didn’t have a dryer,
so actually it’s not, it wasn’t a cultural
thing in Russia and maybe now some
people will have it. And we always just
dry them outside. So why I’m telling you all
this because regardless of your background
where you were born if you have your dream
you’ll follow your dream and you will do something that
you couldn’t even imagine. So for example my parents
were very much insisting on good education, they were
born before the World War II and they didn’t have higher
education, but they wanted for their kids to have it. And they put us into school with special emphasis
on English language. But Russia was very close
country, I never saw any of my relatives or friends
going out to other countries and I was asking myself
why I’m learning English. But then standing in front of you today I would say
my parents were right, so they were enforcing
something on me that I maybe didn’t understand but it helped me
through my life. So I suggest that you
listen to your parents. So I have a lot of
inspiration from my friends and teachers and support. This is what you seek when you
are going to pursue your dream. And so from Ufa having
interest in science and more in life sciences I
went to Novosibirsk, it’s in Siberia maybe you’ve
heard it’s very cold there but it can be also very warm, it
can be 100 degrees in summer so but it’s dry, it
feels different. So I was studying there biology, molecular biology
and biochemistry. And then it happened so I met
my husband Dr. Yuri Kotliarov during my university years. And together with him we went
to University of Tokyo in Japan to study further and
to get our PhD degrees. And I worked in the
Brain Science Institute and I will show you
some brain cells later. And when we were in Japan we had
a chance to go to a conference to the United States and we were
so impressed by the scientists and by the opportunities
that are in this country for the research and we decided
to work in the United States. So we moved and it was almost
like around the world journey. So I’m talking that
I’m scientist, but what is really science? Can you guys say
something or write?>>I think science is something
that you can’t explain, but then later on
you can explain it.>>Dr. Svetlana Kotliarova: To explain unexplained
that’s very good.>>I think science is when
you like have questions about the world and
things that you find and then some stuff is
never answered or things that are very questionable.>>Dr. Svetlana Kotliarova:
That’s very good.>>I think science is something
like a group of different things that have something to
do with like you wanted to study what was it again?>>Dr. Svetlana Kotliarova:
Molecular biology, biochemistry.>>Yes and you could,
it’s also like astronomy.>>Dr. Svetlana Kotliarova:
Yes, that’s right.>>And.>>Dr. Svetlana Kotliarova:
That’s all great answers. Science is the way we learn
about the unknown things in the world and it also
includes all the knowledge gained through centuries
and generations — from generation to generation. And scientists are
using different tools. So here you see a
couple of tools already, so anymore tools
that, so what kind of tools do you think
scientists use, just give me a couple examples? Yes please. [ Inaudible ] How did you know I’m going
to speak about microscope, so you guessed it right? Yes. [ Inaudible ] Telescopes all right. So what are microscopes used
for to see what kind of things? [ Inaudible ] Tiny objects and telescope? [ Inaudible ] Yes, that’s right. Yes. [ Inaudible ] Beakers that’s very good. Yes. [ Inaudible ] Yes, yes to measure exact
and to mix things right. So and what do scientists
do, how does science work? So what does it start
from, like what? Yes. [ Inaudible ] Question or hypothesis exactly. And then we do what to
test the hypothesis?>>Experiments.>>Dr. Svetlana Kotliarova:
Experiments. And then we get something
results. Exactly. And then we
have to explain it, is it the result we expected
or is it something unexpected. Then what do we do? So a very important thing
is to get the resources to do all the experiments,
so you need funding and we will talk about
funding a little bit later. And before you start your
experiment do you want to know if this idea occurred to someone and someone already
resolved this? Do you want to invent
a new wheel or you want to use the invented wheel and
build the new more bigger? So you go to get more
information right and now we have all
the resources, we have the computer internet, we can check some ideas
and find information. Where else we go to get
information about ideas that you want to pursue? Yes.>>The library.>>Dr. Svetlana Kotliarova:
Of course and that’s why we
are here right. And we talked about the
tools and [inaudible] from the first try that we are
talking about the microscope. So when does microscope, when did people start
thinking about microscope? Someone is thinking and sitting and saying oh I will
invent a microscope. No, so actually there
was no glass at first and glass was invented
and then they saw like if they put some glass
on some object they see that it is become bigger. And this was happening like
in the first century romans noticed that. And then one scientist
or some guy in Italy made the first
magnification eyeglass just for one eye to help
people to see. And after that two Dutch
spectacle makers made the first microscope which was a tube,
which was like consisted of three tubes that you
have to retract them. And the first microscope
that was used for many things was invented
again by a Dutcher draper and scientist Anton
van Leeuwenhoek. So probably you heard
his name because this is when the real microscopy
started and he was the first to see tiny creatures
under the microscope. And in 1665, Robert Hooke,
an English scientist, published his micrographia. The things that he observed
under the microscope and we will talk about
this in a second. So as you can see, there are
Romans, Italians, Dutch people, English scientists and
centuries So in time and space the microscope
invention was continuing, so this is how science works. It is and now it is
more like teamwork, people can move using planes
and helicopters you name it to different areas to
do research together. And if you choose to be a
scientist you could be also traveling a lot and. [ Inaudible ] Excavation or archeologists
yes, yes. So and as we spoke
about Robert Hooke, the Library of Congress has his
micrographia, so his drawing that he made looking
into the microscope. And this website actually
is a great resource both for the students and for the
teachers to get acquainted to know more about different
pieces, different information, different information on scientific discoveries,
and so on. And this is the micrographia
that Robert Hooke made. So what did he draw, what did
he look at the microscope? He look at the cork,
cork, cork on the trees, the cork like on the oak. [ Inaudible ] And he found some structures
he called them pores or cells and he called them cells because
he was thinking when looking at them that they reminded
him cells of a monastery where monks lived, like
tiny cells in a monastery. And guess what? He was the first person
whose named themselves, since then this units of
life are called cells. Actually he was seeing
the dead cells and the walls of the cells. And this is how cork cells
look under modern microscope, so he could draw very nicely. And this is the living cells
of onion under microscope. Maybe you will do or
already did this experiment in your school looking
at onions. And this is the first
microscope that was like a tube and Robert Hooke draw his
micrographia using this microscope which he invented too and this is how modern
microscope looks which you are familiar with. And these are some of my
data that were published about the brain tumor, so when
I did the brain cancer studies. So as you can see, the shape
of the cells is in green because there is protein
that is in the cell membrane which is called [inaudible]
and the nucleus which is stained in blue. So now I want to
tell you a little bit where scientists work. So it could be an academic
institution or university, industry and government. And I work in the
government organization, which is called National
Institutes of Health. This is one of the biggest
research institutions in the world and it’s
right here in Bethesda. So it’s just close to you
and you can be part of it and we’ll talk about this later. So there are many achievements
that were done at NIH, National Institutes of
Health, everyone calls it NIH. And for example,
discovery of fluoride to prevent the tooth decay
or eradication of Ebola as you heard recently. And human genome was
also sequenced at NIH. So there are 27 institutes
and scientific centers at NIH and I work in the Center
for Scientific Review and what does it mean? We will know in a minute. So what do you think
about scientific review? So we were talking about
experiments, hypothesis and what do we do
with the results, and where does scientific
peer review have place. So there are five
options for you to guess what is scientific
review, what is NIH peer review? So but I warn you this
is a tricky question so. So who is for, do
you have any ideas? What is the idea?>>Two.>>Dr. Svetlana Kotliarova: Two, scientists meet together
to discuss science.>>None of them [inaudible].>>Dr. Svetlana Kotliarova:
Three, scientists review
scientific application from other scientists. Yeah, that’s peer-to-peer
very good. But two was also correct
and one is correct because scientists
write application about their idea and
submit it to NIH. Also, when scientists meet
they evaluate the application, how interesting it is,
how it will improve, how it will advance
science further. And they will give it a
score, so four is correct too. And NIH is make sure that
this process is all fair and only experts
review the applications. And everything is done without
bias and in a timely manner. So going back to this schema,
so we were talking about funding and that we will
talk about it later. So and this is where the peer
review comes into the picture. How to distribute the funding,
government funding for research. So peer review makes sure
that the most advanced and important scientific
questions will be examined and this important
knowledge will be available for the whole population to
advance health of the population and the eradicate the disease. And we need to make sure that the best science
will be promoted. So I suggest that you experience
how peer review works just now by doing this small game. So we have three proposals that were submitted
from some scientists. And the first proposal
is smoking, is about smoking
and lung cancer. So the scientists want to know
how the cigarette smoking causes lung cancer and what
chemicals are responsible for damaging biological
molecules. So now you need to look at your
badge that you have and see if any one of you has expertise to be a reviewer for
this application. They will study chemicals
and biological molecules. So any molecular
biologists we have or any chemists,
what do you have? Molecular biology? Okay come here. Any lung cancer specialists? All right we have.>>At the back.>>One on the back. Yeah, come here. So and any chemists, chemistry
or general cancer research? We still have to have the third
person for this number one, any lung cancer, chemists,
molecular biologists or cancer, general cancer? [ Inaudible ] You, what do you have?>>Cancer research.>>Dr. Svetlana Kotliarova:
Okay come here.>>Cancer great.>>Dr. Svetlana Kotliarova:
Yeah. And we have proposal number two
about toothpaste and cavities. So the questions
that they will study, which of the three chemicals is
the best to protect your teeth? Is it sugar, is it — it sounds
sweet right, it sounds good? Baking soda or fluoride? So we need some oral hygienists,
some dentists, dentist.>>I am dentistry so.>>Dr. Svetlana Kotliarova:
Dentistry perfect. Oral hygiene come here. And now again, some
chemical expertise, we are talking about chemicals. No, no chemists? Everyone is bacteria. So this is one that’s for you. So someone need to
pretend to be chemist, so you want to be chemist? Okay, all right. And now the third proposal, how do bacteria protect
themselves from viruses? Do they synthesize
special molecules that help them to do so? So we have bacteriologists,
virologists right. So now we have all these
three different topics and we have, so okay. These stickers, so I give
everyone a sticker and please if you think that the
topic is important give it three stickers. If you think oh it
would be good to know but I’m not very excited
give it two stickers. And if you think maybe
better not to do this type of study give it
one sticker okay. And I have three boards
for each of the proposals, so put your stickers
on each one of them. So okay. So we start from you
and I give you the stickers. So there we go and to you. And then you need
to put your board, to give your board
to the next person. All right we have 27 likes
for bacteria and viruses, 24 for smoking and cancer, so
what do we have for toothpaste? Less enthusiasm for toothpaste,
so I guess everyone figured it out already that
sugar not so good. All right so this
is just an example, just a game to give you an
idea how peer review works, like scientists from
different areas of science will gather
together and decide which is the most
exciting project and which will be
beneficial to our nation. So about importance
of basis science. As you know there
is basic science and applied or clinical science. And you can easily figure out
what clinical science means, it’s just immediately
applicable to patients. But basic science is science
that will answer many questions that are unknown, many
questions about the disease that are not known,
maybe for those diseases without cure such as cancer. We need to gather
a lot of knowledge which probably will not
be immediately introduced into clinic but will be
helpful in developing such cure in the future. And basic science important
you appreciate it very much and I’m very happy. So let’s talk about this
viruses and bacteria. So would you say maybe to cure
diabetes would be more important than to know how bacteria
protect themselves about the viruses? It happened that National
Institutes of Health and National Science
Foundation funded the bacteria and viruses research. And what they find that
bacteria will protect themselves against viruses by
getting pieces of DNA. And they found that human
DNA can be also cut, like piece of the
human DNA you can cut. For example with the gene that
has coding for insulin protein and then you put it
into bacterial DNA. So now you have the bacterial
DNA which have human gene and it will synthesize
human protein and then they purify protein
and give it to patient. So this is how basic
science can lead to cure. So you can be part of NIH too
and there are several programs that are available for
high school students and for university students. And there are also a lot of
resources, maybe Sasha can email to your teacher these resources
and you can investigate them when you are doing
some projects. And there is a lot of interesting information
about science. And if you are interested,
if you have questions, if you are patient, anyone with
these qualities can scientists. And of course you read
books, you go to the library, don’t forget Library
of Congress. And you can do science camp,
you can do a lot of activities and go to earn your degree. And there are some professions
in biomedical research or in biomedical science that
do not require advanced degree. So for example environmental
field technicians, sonographers or veterinary technicians,
nurse, and if you are interested doing
forensic science for example. So you still have to have
education to do these things that you are interested
and you can choose to pursue your academic career
by going to a PhD studies and have your own lab and
ask your own questions, apply for NIH for funding,
and do your research that you would love to do. So just do not let
your imagination to give you boundaries,
so dream big and follow your dreams
so to be a scientist. That’s the end of
my presentation and now Dr. Yuri
will excite you. And we will have questions
maybe later together right.>>Sasha Dowdy: Thank
you very much. So our next scientist and Yuri
Kotliarov is the other half of the scientific
dynamic duo and he’ll talk to you a little bit about the
kinds of work that he does with scientific data,
what happens after you get the
results of the experiments and the questions
that you are asking. So he also went to
Tokyo University, got a PhD in engineering
and now also works at the National Institutes
of Health in the Center for Human Immunology,
he’s a staff scientist so science is a daily thing. Looking at a whole bunch
of things and figuring out how everything
fits together. So tell us a little bit
more about your work.>>Dr. Yuri Kotliarov: Okay,
hello good morning again to you. So just as question
I want to ask you, what do you think the most
common tools now in science as it was for centuries,
like what scientists used to generate hypothesis, thinking about the nature,
what is the tools? So Svetlana before talked with
you about some scientific tools. So but what do you
think, any ideas, like very simple tools every
scientist used for centuries? Yes.>>Magnifying [inaudible].>>Dr. Yuri Kotliarov:
Magnifying glasses, but yeah it was developed
just maybe a few, maybe a hundred years
ago, something like this. Something was simpler
what scientists are using.>>Water.>>Dr. Yuri Kotliarov: Water
okay, but not everyone maybe. Yeah. [ Inaudible ] Exactly paper and pencil
you have to write your ideas and you kind of recording
your findings right. So in last years things
change, what do we use now? So we also use pen, paper
and pencils and papers, so what do we use now?>>Technology.>>Dr. Yuri Kotliarov:
Technology, what kind of technology?>>Internet.>>Dr. Yuri Kotliarov:
Internet yes, but before? [ Inaudible ] Just let’s say computers
right more general and machines it help us
to store like large amount of data and do the analysis. [ Inaudible ] Which machine? [ Inaudible ] Computers yeah.>>[Inaudible] write
it down first.>>Dr. Yuri Kotliarov: So again
Svetlana recently described you that scientists who discovered
microscopes they just draw the pictures they saw
under the microscope. And many thought in hypothesis
was built about the pictures. So what current technology is
recording is very complicated, it’s also images that converted
to the data on the computer and it’s a large amount of data. Maybe I can just show you. So this is one of technologies,
it’s a little bit old. We use these called
DNA or MicroArrays. You know all what is DNA and
how it looks like, what is it, did you study in
your science class? Does this look like this? Yeah, like a [inaudible]
molecule that can pass the information
about you from generation to generation, why is
we look your mom and dad and why we different from
animal, from bacteria. Because every living thing
they have DNA in their cells. So this technology has, it’s
actually a very tiny chip, it’s about like one
and a little bit more [inaudible] centimeters. And they have small
pieces of DNA attached to like every micron
of this array and the DNA is very
different and it’s light when it finds similar
DNA in your sample. So we analyze like a lot of
thousands of such images, it’s very complicated. It’s written by laser
and basically when the laser finds the light
it means these genes also present in your sample,
the samples can be cells or something from your
blood, from mouse, animals, bacteria and so on. So the data takes a lot of space and this requires computer
to do the analysis. For example, we can compare
cancer patients some sample, like blood sample
from cancer patient with a healthy patient
just normal and see which genes are different. Maybe if some genes express more
it means the gene’s response in cancer patients the gene
responsible for the cancer or if some genes we find less in cancer patients maybe
this gene is important to protect healthy
people from cancer. So but the — yes?>>How is cancer formed?>>Dr. Yuri Kotliarov: This
is a complicated question, this is actually under a
very large study now how the cancer form. The problem is that the
different cancer is very different, from one patient
— if you compare one patient and another patient
even with the same type of cancer let’s say
lung cancer the nature of cancer might be
very different. Some maybe smoked a
lot and got the cancer, another one maybe lived
in different environment or had some genomic
predisposition, some mutations in their cells. So it’s a very difficult
question and it’s.>>Are you saying
that if someone from different [inaudible],
from different areas?>>Dr. Yuri Kotliarov:
Yeah, the are some — yeah.>>Dr. Svetlana Kotliarova:
Can I answer?>>Dr. Yuri Kotliarov:
Yeah, you can answer.>>Dr. Svetlana Kotliarova: So cancer is although they are
all different as Yuri said, so there are common
features of all cancers that something happens in the
DNA, in our genetic information that make the cells to
divide uncontrollably, so it cannot stop dividing. That’s why the tumor is
formed, so it’s growing. That is the main feature which
is common to many cancers. So is that what your question,
how the cancer is formed? But exactly the mechanism
can be different for all different
types of cancer. And there are a lot of.>>Dr. Yuri Kotliarov:
And even for example if there is brain cancer there
is multiple different types of brain cancer. And it’s different how people
survive, some survive longer, some survive less,
some people respond to some treatment
and survive longer. But other people do not
respond and it’s very important to know what is the
right treatment for some patients
and for another. Maybe you heard about
some program like precision medicine
initiative when scientist wants to really analyze like
sequence of DNA in your cells and know more about you
and to find better cure. [ Inaudible ] Yes, the earlier the cancer
is detected the easier to treat it usually. But it depends on the
aggressiveness of cancer and sometimes it’s very hard to
find the cancer at early stage because the cells are
very small you know and cancer cells they’re hiding,
it’s very tough and it’s one of the direction
of cancer science to detect cancer
at the early stage. So but I don’t have much time,
I want to have some fun with you about the data analysis
in general. So I show you this slide just to
have an idea that we’re dealing with some large images
that converted to the data on the computer. So but I want to talk
something different and maybe you won’t notice
it’s related to science. So in the Library of Congress
there is a very large database of old newspapers. The newspapers was scanned with optical character
recognition technology, have you heard about it? Basically you can convert
the image to the text, you could right,
it’s called OCR. So the Library of Congress
had this large database of newspapers from you see
18th century to 20th century, all the — so many newspapers and all the text
is recognizable. The computer like you’re reading
the news in the computer. So and so this project
[inaudible] in America provides very
good access to this data and you can do some very
fun research I would say. And I can just go with
you and just do them, very small analysis
with the tool I’m using. So you all like animals,
dogs and cats, anyone have dogs or
cats [inaudible]? So who is the dog people? Wow me too. And who are cats people? You have both right? Very good. So let’s ask which from 18th
century right we have all these papers and how many
papers mention dogs and how many papers
mention cats? So what people will prefer
to talk about in newspaper. Yes. [ Inaudible ] Okay yeah, we can see. So this actually,
so my thought based on there is some data
exploration like this in the Library of Congress
blog, I get the idea from there but applied it on the
tool what I am using. Okay so I will show
you my screen here. Okay so this called,
environment called RStudio and I’m using R language,
just one letter R. So I get, this is the link, it’s a coding
yes, this is like how we — so I am doing the data
analysis in my daily job and this is basically coding. So this is my code, this is
where all the output show me and this is where you will see
some pictures and variables. Any of you study
some kind of coding? You did good. What language have you used?>>I don’t use we coding
to make video games.>>Dr. Yuri Kotliarov:
What, oh I see. Oh probably like
what’s the name? Yes. [ Inaudible ] Okay, okay. So this code, this
language is very used in the science of data analysis. So I read this URL in
the code, get some data. I hope internet works well. [ Inaudible ] So you can see I am reading like
some, I’m getting some papers from Arizona and you can see that there is 300,000
papers just from this state. So let’s go to dogs, so
we can — for example. So I am doing the
request for like dogs and just it will
take a long time to analyze the whole,
the database. So I’ve taken only
just 20 pages. And it returns me to dog
mentioned just in 20 pages, it’s not newspaper pages
but it’s pages the Library of Congress gives you. And you can see it it’s around 2
million records about the dogs. So. So here I get information
for both cats and dogs, so you can see it goes through
all the 20 pages of information. And it’s getting what
state the data from and how many mentioning
of dogs and cats. Okay 20 it’s done, this actually
will take a long time for it to analyze the whole database. So some preparation. Okay and now we have a plot. So and can you see it? So this show by state and make
it a little bit smaller okay. So the red one is
cats, the blue is dogs, so this show how many
mentions from the newspaper from each state, in
the United States and again from 18th century. Again, the more, you can see
for example [inaudible] it looks like dogs more than cats. Here we have the District
of Columbia cats win. So some of them like New York
is a dog state, Kentucky, California, but other they’re
pretty much cats as well. So if you do a little
bit more plotting. So I calculated like who
is the winner basically, the ratio of number of dogs in newspaper divided
by number of cats. So these green are
the dog winners states and see Kentucky is on the top. So basically, more
dogs than cats, three times more mention
of dogs in Kentucky. This is tied, this
is the same Virginia, South Dakota and Georgia. And Arizona, Montana, Indiana
they looks like cats more. Okay you all like
Star Wars, right? Did you watch last night, no? Anyway, there is a database
about all the characters from the Star Wars in all
the movies, made movies. So about the physical
characteristics, I don’t know who compiled them but there is like a whole website
describing who is who. And this website basically has
the easy access to all the data, for example different planets,
people, vehicles, spaceship, which people using which
vehicle, and so on. And which films they
are and so on. This is the data how it look
like, so name of the person, you can see Darth Vader here
and Skywalker, even droids, C-3PO and these just
the first part, there is 88 characters total in this database
[inaudible] attributes. So again disclaimer, last movie
now is The Force Awakens no [inaudible] yet. And you can see there is the
hair and mass and hair color, eye color and gender
and where they are from, what the species and so on. So I just thought it
will be some kind of fun to do data analysis of
this database just quickly. So I already collected the
data, so I’ll just read them, [inaudible] libraries. So this gives me some ideas
about what species are in the movie, so there
is 37 humans, 5 droids, and then others just so
many species in the galaxy that are very few
representative of each. Yes and this movie is mostly
about humans you know. Let’s — so they
have mass and height and I thought let’s plot
them again each other. So here is some points,
so here is the mass so how heavy they are
and this is height. So again, we see the. So this row everyone that
has both mass and height. So you can see they’re
kind of on the line so they’re heavier the character
the higher they are or opposite. There is one exception
here, so he’s very heavy and not very high, any ideas who
can be, who knows the movies? There is the Java the Hut
remember this fat guy, bad guy? So for this I only
leave human and droids. So let me label them. So this is the BB8
very small droid and then the top we have
Darth Vader, very high and then all the other humans with another droid
like killer droids. And then basically all
the humans [inaudible] and there is a line
and some exceptions. So you know idea about the
body mass index how they, how doctors kind of assess how
health you are based on mass and height or if like your
BMI is basically mass divided by square of your
height, sorry height? So I can calculate the
BMI for these characters. Okay so this is coloring
male, it’s okay. So this is, so again here with the green one
is our healthy zone, you can see this is between like
20 and 25 really healthy BMI. And you see all the humans
are pretty good shape. Let me label them also.>>Dr. Svetlana Kotliarova:
How about Chewbacca?>>Dr. Yuri Kotliarov:
I haven’t labeled him. Actually he was there, but
he’s not human he was excluded.>>Dr. Svetlana Kotliarova:
Okay.>>Dr. Yuri Kotliarov: A beast. So see Darth Vader a
little bit overweight, but he probably has a
lot of metal in the body. Some few people are overweight and these I remember the
Luke’s step-father right, a little bit overweighted
[phonetic]. And one of the pilot called,
with nickname [inaudible]. So all the females here,
except one Captain Phasma from the Force Awakens,
it’s a very large woman. And you know this is the wartime
they all like very fit to fight and also, it’s Hollywood actors, you know they’re
supposed to be healthy. So, okay so I want to finalize,
we don’t have much time, I have some other
very fun datasets. But I want you to have an
idea that it’s very easy to use computer and with just a
few lines of code you can look from the different
prospects on your data and kind of get an idea. And generate some hypothesis
for fun experiments. Thank you very much
guys for listening. [ Applause ] Yeah, if you have questions.>>Yeah, so you do
research, you analyze data?>>Dr. Yuri Kotliarov: I analyze
data, but not this of course.>>Right, right, right.>>Dr. Yuri Kotliarov: This is
just for fun in my free time.>>Right, so what type of data, so you’re only analyzing
immunology data or are you analyzing
all the different data that comes into your office?>>Dr. Yuri Kotliarov:
Analyzing different data which related to immunology.>>Okay.>>Dr. Yuri Kotliarov:
This can be some like autoimmune diseases, it can be for example we
published a large paper about the flu vaccination.>>Okay.>>Dr. Yuri Kotliarov: How
people respond to flu vaccine, but we see that it
depends on some cells in your body some people
respond higher than others.>>Okay.>>Dr. Yuri Kotliarov:
And we find some cells that actually they stay there, the amount of those cells just
before the vaccination can — is responsible for whether
you will have response or not.>>Okay.>>Dr. Yuri Kotliarov: So and it’s very different
how young people responds versus old people, they are
very different immune system and we’re still trying
to understand what’s the like big difference between
young and old people.>>Dr. Svetlana Kotliarova:
You did cancer.>>Dr. Yuri Kotliarov:
So we study.>>Dr. Svetlana Kotliarova:
You did cancer too.>>Dr. Yuri Kotliarov:
That’s right we did.>>Do you all ever
get to work together?>>Dr. Yuri Kotliarov: We used
to work together for eight years in the cancer lab on
the brain cancers.>>Dr. Svetlana Kotliarova:
I’m whispering that you did cancer analysis
too in terms of data.>>Dr. Yuri Kotliarov: Yes, we
working on the and now you know in the cancer research
immunotherapy is very promising to prepare the cell that
is specific for a patient that will help him
to fight the cancer and then attack the
cancer cells and kill them. So this is very promising
research and also in immunology in general there is
many, many open questions that we’re trying to answer. Basically my job is
to help scientists to understand the data and to
generate some new hypothesis, how to explain what
we see in the data. Do you have any questions guys? So basically this is using the
tools that now almost everyone, many, many people have
computers in their home.>>Dr. Svetlana Kotliarova:
This is a free tool yeah.>>Dr. Yuri Kotliarov: And this
tool I’m using is actually free, it’s opensource.>>Would you rather use
the computer or like pencil and paper like because say if
like all the power went out and.>>Dr. Yuri Kotliarov:
Of course yes.>>And the data will be erased.>>Dr. Yuri Kotliarov:
Of course. Yeah, I prefer to use the
computer when it’s available but we should be ready of course
and just don’t lose [inaudible] to write and draw
with pen and pencils.>>Sasha Dowdy: We actually
have a whole bunch of research in the Library of Congress
collection, digital collections of Thomas Jefferson writing
down data with paper and pencil and he was trying to figure out,
not necessarily even figuring out just recording data
about the weather every day and he would write
down just everything that he saw around him. And then you can see
all that data online and you could also
plug it into a computer and analyze what Thomas
Jefferson was looking at every day so.>>Dr. Svetlana Kotliarova:
That’s interesting.>>Sasha Dowdy: He was a
writer, inventor, scientist, library enthusiast, everything.>>Dr. Yuri Kotliarov:
But I can say that you saw the optical
character recognition from the newspapers when
the font is very fixed and we know how the
letters look like, but when you have the
handwriting and you want to [inaudible] computer to analyze what’s written
it’s a very hard task. Different people have different
you know writing styles and sometimes you
even cannot read and you want computer
to be able to read. But there is a technology
like some deep learning and [inaudible] networks
that have helped with these and now the research is
ongoing in this area.>>Sasha Dowdy: [Inaudible]
asked your question, anyone else?>>Dr. Yuri Kotliarov: Okay.>>Dr. Svetlana Kotliarova:
Okay.>>Sasha Dowdy: All right
well how about another round of applause for our scientists? Thank you very much.>>Dr. Svetlana Kotliarova:
Thank you.>>Sasha Dowdy: I hope you
guys enjoyed the presentation and make sure to check out
the digital resources we have about all these founding
fathers who recorded their data and the original scientists. And there are so many
sources out there, if you like you can find a lot of really interesting
data and explore. If you have a question
you’re already a scientist and just keep exploring
your curiosity okay. All right guys, thank
you so much.>>This has been a
presentation of the Library of Congress, visit [email protected]