Thursday, December 21, 2017

Time and Myself in Berlin by Jihwan

Time and Myself in Berlin
Jihwan Myung
Taipei Medical University & Shuang Ho Hospital, Taiwan

It was like any other day. I think it was rainy. The details of weather were irrelevant. In the
place where I was, the day started with darkness at 25 degrees Celsius and ended with
darkness at 25 degrees Celsius. My job was to look at how time is kept in the tiny little circadian
clock in the mouse brain, and for that reason I spent long hours in a small room under constant
conditions along with my mice. I remember the day, and the jokes I exchanged with a fellow
researcher under an umbrella, not because I was particularly worried about smelling like a damp
mouse, but because of a realization that hit hard on me—I was getting old and these constant
conditions were making me agnostic about the fact. Suddenly the slogan I saw the other day on
the Internet, “Gain Time to Think (at the Wissenschaftskolleg),” felt immensely appealing. Time
was always there but for a long time, time was not entirely mine. Time was also the topic that
fascinated me from the beginning. Would I be able to have time of my own and think thoroughly
about time in the brain?

Take a time machine back to when I was a child. Albert Einstein, the quintessential scientist for
many people, was a revolutionary for me. He powerfully demonstrated that philosophers do not
know the truth. Yet, he did so not through experimental data but through Gedankenexperiment,
something that the philosophers had been supposedly doing all along. But that was only one
part of the irony. The enigma of Einstein's theory came from the fact that its central subject was
time, which had been entirely philosophical. A famous show-down happened when Einstein was
42 years old and the young physicist announced to the old philosopher Henri Bergson that
philosopher’s time was no more special than the physicist’s time. According to Einstein, the only
remaining, unstudied kind of time was a psychological one, which was what I was studying.
Decades have passed since then and Einstein became a cliché. I, an aspiring physics student,
became a 42-year old, and became a biologist. The mystic statement about time became a
plain statement that light travels at a constant speed and the whole theory became simply a
classical mechanics analogy for certain things in electrodynamics. In 2016, when all the
fascination about time had completely dwindled, I found myself, along with my wife Hitomi, at the
Wissenschaftskolleg, the Institute for Advanced Study in Berlin.

In addition to psychological time, there was biological time. Almost all living organisms on Earth
harbor a clock that is set to predict the 24-hour day-night cycles. The biological clock is not
exactly precise, and all organisms effectively live in their slightly subjective time. Regardless,
Einstein might have said there is no biologist's time. The laws of physics supervene the laws of
biology. A barrier of complexity, however, lies in between physics and biology and it is not easy
to derive laws governing biological time from physical principles. Biological time stands as a
good enough conceptual approximation for all practical purposes. Since biological time has an
objective basis as does physical time, I thought I could use it to understand psychological time,
which was subjective. This was a more ambitious plan than it sounded. Circadian rhythms
provide a rough guideline to the brain on the daily ration of usable time. In many animals, the
sleep-wake cycle is largely determined by the circadian clock. The human species is a bit of an
outlier—they often willfully ignore what their internal clock says and just work or play through the
night. Therefore, approaching subjective time from the biological basis clearly had its limit. I
had to think about time from the subjective perspective. This was like drilling the Channel
Tunnel. A scientific study of subjective time must start from the biological side but it cannot be
subjective if it is not understood on the first-person side. So one has to bore the tunnel between
subjectivity and objectivity from both directions. Luckily, a small library at the
Wissenschaftskolleg had the whole collection on Aristotle, who had thought about this issue. I
tried other philosophers, such as Heidegger, but without much success. When I was struggling,
I rediscovered Henri Bergson. Aristotle could define time before and after "now," the moment
one is conscious of. Bergson literally stretched the "now" moment into a duration like an elastic
rubber band. This is the consciousness's comfort zone, where it can wield its free will. I then
imagined that biology puts a constraint on the duration's elasticity. The duration has to do with
our attention to life, and this we know by our experience of time running fast when we are having
fun and time slowing down when we are gloomy. The circadian clock, which counts objective
time of the day, can modulate the extent of temporality by limiting the release time of dopamine
that accelerates the flow of subjective time. The circadianly controlled release happens to occur
in the morning and this has an intuitively clear consequence, such that we quite often say "Oh
it's already time for lunch" but we never really say the same thing about dinner. Time does run
fast during the morning thanks to the timed dopamine release. Then I made a second statement
that the qualia of time perception are mood states. This is likely, yet at this moment only
correlational, because global analysis of Twitter patterns shows that people in the morning use
the words associated with heightened mood states. I presented these thoughts at the
Colloquium. Little did I know at the time was that the presentation would be the basis of my
future job talk which would take me to Taiwan to study consciousness seriously.

The time I had in Berlin has definitely made some permanent changes in my life. It allowed me
to ask myself the most exciting question I knew of. It allowed me to come back to where I had
started. There are so many more things I wish to write about, like when I had to pass by the
ruins of the Israelitisches Krankenheim while commuting to my office in an old human anatomy
building. For now, let me close one chapter with my small intellectual encounter with Einstein
and Bergson, which would not have been possible without the particular flavor of Winter in

Tuesday, February 28, 2017

Alan Turing: this time, the book, which is excellent

I wanted to write a letter to my friends about the movie The Imitation Game and the book that, the poster says, "inspired it". I did.
If my writing has any value at all, it is in clarifying my thoughts for myself and potentially for others.
But what exactly do I want to say about Alan Turing and the film about him? Simply that he was a genius who contributed immensely to his country then killed himself, assumedly at least in part due to his mistreatment (because of his homosexuality) by the country whose defense he made such a contribution to.
I enjoyed the film, but as soon as it was over I began to have second thoughts about its veracity and quality. Having reflected on it for a few days, I simply cannot comprehend how it won any awards.

The book Alan Turing: The Enigma, or even the Foreword by Douglas Hofstadter or the Preface by the author (Andrew Hodges) 30 years after his biography of Alan Turing was published, is far more interesting than the movie, whose sole merits are that it takes only two hours to watch and it will promote sales of the excellent book. The e-book of Hodges's magnum opus can be had for a little over $5 and the sample including the Foreword and Preface and much of the first chapter can be obtained for free. Read them and you already have your money's worth -- and know more about Alan Turing than the movie will teach you.
A major merit of the book is his portrayal of Turing as a human being rather than a superman. It corrected my misunderstanding of his achievements as inexplicable. No, what was wonderfully unique about him was not so much his foresight or vision or discoveries as his complexity: some things he understood and explained before others had, but mainly he was exceptional because he could do what others had done without knowing about them, without using their methods, sometimes less elegantly (especially in his written explanations) but often more simply, more "elegantly" in the mathematical sense. He was never "best in the class" but in retrospect his legacy excelled, and others' stand in the shadows. It's fun to cheer for the underdog.
I've still read little about his productive wartime period, but the Foreword and post-publication Preface give very inspiring overviews and summaries of his career and contributions to mathematics and cryptography.
May 9, 2015

Monday, January 25, 2016

What I Talk About When I Talk About Running

To keep on going, you have to keep up the rhythm. This is the important thing for long-term projects. Once you set the pace, the rest will follow. The problem is getting the flywheel to spin at a set speed and to get to that point takes as much concentration and effort as you can manage.

Saturday, January 23, 2016

Online LaTeX Editor and CV template

ShareLaTex is an online Latex Editor which can be used to generate high quality PDF documents. The personal use is free and there are quite a number well designed CV templates.

Friday, December 18, 2015

The isoform of Ube3a

The isoform abundances of Ube3a (in colon and brain cortex of adult mice)

Use Tophat for the transcriptome analysis and examined the isoform_exp.diff file 
mRNA_id         gene_id         locus                   fpkm_colon  fpkm_cortex
NM_001033962    Ube3a_isoform_3 chr7:66484119-66562097  0.004558    5.07055
NM_011668       Ube3a_isoform_2 chr7:66484119-66562097  0.230222    0.60659
NM_173010       Ube3a_isoform_1 chr7:66484119-66562097  5.82296     1.36267
It seems that iso3 of Ube3a is the main variant in the mouse cortex. The iso2 of Ube3a encodes the full length protein. Iso1 is considered to be E3-ligase deficient as it lacks 87 amino acids from the C-terminal HECT domain. Both iso1 and iso3 lack 21 amino acids from N-terminus as well. Regarding the localization, Iso1 and Iso2 are ubiquitously found throughout a cell, where Iso3 is confined to the nucleus.

Tuesday, December 1, 2015

MOOC Courses for Genetics/Genomics Data Analysis

I have taken a number of Massive open online course (MOOC) since 2014 and here is a short summary. 

In general, I believe learning-by-doing is the most efficient way, and learning a subject without applying the knowledge to solve any practical problem is unlikely resulting in a good understanding. That being said, I'm kind of opposed to learn things (I feel) which are less relevant to my current work, for example, I used to think it doesn’t make much sense to learn NGS analysis if I am not doing NGS study. However there is a dilemma that, in many circumstances, when facing a complex problem, you  need a certain level of skill/knowledge and be aware of existing tools available to use. Through this personal learning experience,  I could say I benefited quite a lot from the MOOC and I am happy that I invested my time in learning. These MOOC courses serve as a good staring point to build a broad knowledge base.

The most popular MOOC websites are Coursera, EdX, Stanford OpenEdX. The former two provide more courses on genetics/genomics/bioinforamatics; and in OpenEdX, some courses are not free. 

At Coursera, I obtained a certificate from courses including:
Johns Hopkins University  Regression Models 
Johns Hopkins University  Statistical Inference
Johns Hopkins University  The Data Scientist’s Toolbox
Johns Hopkins University  Reproducible Research
Johns Hopkins University  R Programming (highly recommended)
University of Michigan  Programming for Everybody (Python)

At EdX, the courses I finished with a certification:
HarvardX -  PH525x  Data Analysis for Genomics (highly recommended)
MITx -  6.00.1x   Introduction to Computer Science and Programming Using Python (highly recommended)

At OpenEdX, I took the course Statistics in Medicine but didn’t finish it. 

The courses I like the most are
this course covers almost a wide range of the genomics analysis and it is easy to follow the instruction. And you can always find something useful. From this course, I got to know the pheatmap , a handy tool to plot (elegant) heatmap, and now it becomes one of my favourite R package. 

very entertaining and I like the way how Prof Crimson taught. It is not only about how to program with Python, I learned more on computational thinking. 

R Programming - I skipped a lot lecture videos but enjoyed working on the assignments

The Quantitative Biology Workshop (7.QBWx), in my opinion, is not very focused and the transition from the learning material to the question is not always smooth. Although I understand that Matlab is widely used in the field of neuroscience, I do hope the course can adopt R or Octave over Matlab as the former two are free software.