SCIENTIST I – MODELING, ANALYSIS AND THEORY
The Modeling, Analysis and Theory team at the Allen Institute is seeking a candidate with strong mathematical and computational skills who will work closely with both the team as well as experimentalists in order to both maximize the potential of datasets as well as realize that potential via analysis and theory. The successful candidate will be expected to develop analysis for populations of neurons as well as establish theoretical results on cortical computation, object recognition, and related areas in order to aid the Institute in understanding the most complex piece of matter in the universe.
Michael Buice, Scientist II
Early Romantic composer Felix Mendelssohn’s Song Without Words Op 109 played by English cellist Jacqueline du Pré, whose career was tragically shortened by multiple sclerosis.
Read former LBM fellow Michael Buice’s explanation of the dress colour illusion.
Huffington Post: …In the case of the dress, one’s assumptions about lighting have a strong impact on the perceived color. In particular, your perception will be affected by whether your visual system sees the dress as being in bright light or in shadow. Comic book coloristNathan Fairbairn put together the following in order to illustrate these two different potential hypotheses about light and color in the picture.
So what happens if we try to remove contextual information? It so happens that these average colors are close to being inverses of one another. Inverting them gives us:
Inverting the colors in the original photo should approximately “swap” the two colors on the dress, as well as remove contextual information (or perhaps render it nonsensical). The color inverted dress looks like:
I see white-and-gold here, and I saw white-and-gold in the original. My wife is a die hard Black-and-bluer, and she sees the inverted dress as light-blue-and-gold. Notice that the image now has artifacts that look (to me anyway) like damage in an old photograph. This is a sample size of one, so I’m curious to know if this inversion changes the perceptions of any other black-and-bluers out there.
We know that training can alter the “light-from-above” prior, and it seems plausible that people’s differing perceptions of the photo are due to their different experience, and in particular their experience with light, shading, material, and overexposed photographs.
Our brains have to make guesses, but they don’t always make the same guesses, even though we live in the same world. One of the hardest inference problems our brains have to solve is figuring out how everyone else sees the world. Perhaps with some very hard work, I can be a Black-and-bluer, too.
Michael Buice is a scientist at the Allen Institute for Brain Science. His research interests are in identifying and understanding the mechanisms and principles that the nervous system uses to perform the inferences which allow us to perceive the world.
Recent paper in Molecular Endocrinology 7:1194-206. doi: 10.1210/me.2014-1069:
John A. Blackford, Jr., Kyle R. Brimacombe, Edward J. Dougherty , Madhumita Pradhan, Min Shen, Zhuyin Li, Douglas S. Auld, Carson C. Chow, Christopher P. Austin, and S. Stoney Simons, Jr.
Abstract: Glucocorticoid steroids affect almost every tissue-type and thus are widely used to treat a variety of human pathologies. However, the severity of numerous side-effects limits the frequency and duration of glucocorticoid treatments. Of the numerous approaches to control off-target responses to glucocorticoids, small molecules and pharmaceuticals offer several advantages. Here we describe a new, extended high throughput screen in intact cells to identify small molecule modulators of dexamethasone-induced glucocorticoid receptor (GR) transcriptional activity. The novelty of this assay is that it monitors changes in both GR maximal activity (Amax) and EC50, or the position of the dexamethasone dose-response curve. Upon screening 1280 chemicals, ten with the greatest change in the absolute value of Amax or EC50 were selected for further examination. Qualitatively identical behaviors for 60 –90% of the chemicals were observed in a completely different system, suggesting that other systems will be similarly affected by these chemicals. Additional analysis of the ten chemicals in a recently described competition assay determined their kinetically-defined mechanism and site of action. Some chemicals had similar mechanisms of action despite divergent effects on the level of GR-induced product. These combined assays offer a straightforward method of identifying numerous new pharmaceuticals that can alter GR transactivation in ways that could be clinically useful.
The paper describing the updated version of the genome analysis software tool Plink has just been published.
Second-generation PLINK: rising to the challenge of larger and richer datasets
Christopher C Chang, Carson C Chow, Laurent CAM Tellier, Shashaank Vattikuti, Shaun M Purcell, and James J Lee
GigaScience 2015, 4:7 doi:10.1186/s13742-015-0047-8
PLINK 1 is a widely used open-source C/C++ toolset for genome-wide association studies (GWAS) and research in population genetics. However, the steady accumulation of data from imputation and whole-genome sequencing studies has exposed a strong need for faster and scalable implementations of key functions, such as logistic regression, linkage disequilibrium estimation, and genomic distance evaluation. In addition, GWAS and population-genetic data now frequently contain genotype likelihoods, phase information, and/or multiallelic variants, none of which can be represented by PLINK 1’s primary data format.
To address these issues, we are developing a second-generation codebase for PLINK. The first major release from this codebase, PLINK 1.9, introduces extensive use of bit-level parallelism, View MathML-time/constant-space Hardy-Weinberg equilibrium and Fisher’s exact tests, and many other algorithmic improvements. In combination, these changes accelerate most operations by 1-4 orders of magnitude, and allow the program to handle datasets too large to fit in RAM. We have also developed an extension to the data format which adds low-overhead support for genotype likelihoods, phase, multiallelic variants, and reference vs. alternate alleles, which is the basis of our planned second release (PLINK 2.0).
The second-generation versions of PLINK will offer dramatic improvements in performance and compatibility. For the first time, users without access to high-end computing resources can perform several essential analyses of the feature-rich and very large genetic datasets coming into use.
Keywords: GWAS; Population genetics; Whole-genome sequencing; High-density SNP genotyping; Computational statistics
This project started out with us trying to do some genomic analysis that involved computing various distance metrics on sequence space. Programming virtuoso Chris Chang stepped in and decided to write some code to speed up the computations. His program, originally called wdist, was so good and fast that we kept asking him to put in more capabilities. Eventually, he had basically replicated the suite of functions that Plink performed so he contacted Shaun Purcell, the author of Plink, if he could just call his code Plink too and Shaun agreed. We then ran a series of tests on various machines to check the speed-ups compared to the original Plink and gcta. If you do any GWAS analysis at all, I highly recommend you check out Plink 1.9.
English composer Ralph Vaughn Williams’s Fantasia on Greensleeves played by Ibis, who are based near here in Arlington Virginia.
I’m giving a talk at University of Maryland, Baltimore County today at noon. The talk will be similar to the one I gave at SMB this past summer. Slides can be found here.
Italian composer Luigi Boccherini’s Guitar Quintet No. 1 played by the Boccherini Ensemble.
Here is an excerpt from a well written opinion piece by Washington Post columnist Joel Achenbach:
Washington Post: We live in an age when all manner of scientific knowledge — from the safety of fluoride and vaccines to the reality of climate change — faces organized and often furious opposition. Empowered by their own sources of information and their own interpretations of research, doubters have declared war on the consensus of experts. There are so many of these controversies these days, you’d think a diabolical agency had put something in the water to make people argumentative.
Science doubt has become a pop-culture meme. In the recent movie “Interstellar,” set in a futuristic, downtrodden America where NASA has been forced into hiding, school textbooks say the Apollo moon landings were faked.
I recommend reading the whole piece.
Yo Yo Ma and Itzhak Perlman play Antonin Dvorak’s Humoresque in G-flat minor with Seiji Ozawa and the Boston Symphony Orchestra.
Everyone in computational neuroscience knows about the McCulloch-Pitts neuron model, which forms the foundation for neural network theory. However, I never knew anything about Warren McCulloch or Walter Pitts until I read this very interesting article in Nautilus. I had no idea that Pitts was a completely self-taught genius that impressed the likes of Bertrand Russell, Norbert Wiener and John von Neumann but was also a self-destructive alcoholic. One thing the article nicely conveys was the camaraderie and joie de vivre that intellectuals experienced in the past. Somehow this spirit seems missing now.
Here is a list of open source software that you may find useful. Some, I use almost every day, some I have not yet used, and some may be so ubiquitous that you have even forgotten that it is software.
1. XPP/XPPAUT. Bard Ermentrout wrote XPP in the 1980’s as a dynamical systems tool for himself. It’s now the de facto tool for the Snowbird community. I still find it to be the easiest and fastest way to simulate and visualize differential equations. It includes the equally excellent bifurcation continuation software tool AUTO originally written by Eusebius Doedel with contributions from a who’s who list of mathematicians. XPP is also available as an iPad and iPhone App.
2. Julia. I only learned about Julia this spring and now I use it for basically anything I used to use Matlab for. It’s syntax is very similar to Matlab and it’s very fast. I think it is quickly gaining a large following and may be as comprehensive as Python some day.
3. Python often seems more like a way of life than a software tool. I would probably be using Python if it were not for Julia and the fact that Julia is faster. Python has packages for everything. There is SciPy and NumPy for scientific computing, Pandas for statistics, Matplotlib for making graphs, and many more that I don’t yet know about. I must confess that I still don’t know my way around Python but my fellows all use it.
4. R. For statistics, look no further than R, which is what academic statisticians use. It’s big in Big Data. So big that I heard that Microsoft is planning to write a wrapper for it. I also heard that billionaire mathematician James Simons’s hedge fund Renaissance Technologies uses it. For Bayesian inference there is now Stan, which implements Hamilton Monte Carlo. We tried using it for one of our projects and had trouble getting it to work but it’s improving very fast.
5. AMS-Latex. The great computer scientist Donald Knuth wrote the typesetting language TeX in 1978 and he changed scientific publication forever. If you have ever had to struggle putting equations into MS Word, you’ll realize what a genius Knuth is. Still TeX was somewhat technical and thus LaTeX was invented as a simplified interface for TeX with built-in environments that are commonly used. AMS-Latex is a form of LaTeX that includes commands for any mathematical symbol you’ll ever need. It also has very nice equation and matrix alignment tools.
6. Maxima. Before Mathematica and Maple there was Macsyma. It was a symbolic mathematics system developed over many years at MIT starting in the 60’s. It was written in the programming language Lisp (another great open source tool but I have never used it) and was licensed by MIT to a company called Symbolics that made dedicated Lisp machines that ran Macsyma. My Thesis advisor at MIT bought one of these machines (I think it cost him something like 20 thousand dollars, which was a lot of money back then) and I used it for my thesis. I really loved Macysma and got quite adept at it. However, as you can imagine the Symbolics business plan really didn’t pan out and Macysma kind of languished after the company failed. However, after many trials and tribulations, Macsyma was reborn as the open source software tool Maxima and it’s great. I’ve been running wmMaxima and it can do everything that I ever needed Mathematica for with the bonus that I don’t have to find and re-enter my license number every few months.
7. OpenOffice. I find it reprehensible that scientific journals force me to submit my papers in Microsoft Word. But MS Office is a monopoly and all my collaborators use it. Data always comes to me in Excel and talks are in PowerPoint. For my talks, I use Apple Keynote, which is not open source. However, Apple likes to completely overhaul their software so my old talks are not even compatible with the most recent version. I also dislike the current version. The reason I went to Keynote is because I could embed PDFs of equations made in LaTeXiT (donation ware). However, the new version makes this less convenient. PDFs looked terrible in PowerPoint a decade ago. I have no idea if this has changed or not. I have flirted with using OpenOffice for many years but it was never quite 100% compatible with MS Office so I could never fully dispense with Word. However, in my push to open source, I may just write my next talk in OpenOffice.
8. Plink The standard GWAS analysis tool is Plink, originally written by Shaun Purcell. It’s nice but kind of slow for some computations and was not being actively updated. It also couldn’t do some of the calculations we wanted. So in steps my collaborator Chris Chang who took it upon himself to write a software tool that could do all the calculations we needed. His code was so fast and good that we started to ask him to add more and more to it. Eventually, it did almost everything that Plink and gcta (tool for estimating heritability) could do and thus he asked Purcell if he could just call it Plink. It’s currently called Plink 1.9.
10. Inkscape is a very nice drawing program, an open source Adobe Illustrator if you will.
11. GNU Project. Computer scientist Richard Stallman kind of invented the concept of open software. He started the free software foundation and the GNU Project, which includes GNU/Linux, the editor emacs, gnuplot among many other things.
Probably the software tools you use most that are currently free (but may not be forever) are the browser and email. People forget how much these two ubiquitous things have completely changed our lives. When was the last time you went to the library or wrote a letter in ink?
Yundi Li playing Frederic Chopin’s famous Fantaisie-Impromptu Op 66.
Here is “Siegfried’s Death and Funeral March” from Richard Wagner’s opera Gotterdammerung of the Ring Cycle played by the London Philharmonic conducted by Klaus Tennstedt. This piece was used to great effect by director John Boorman in the movie Excalibur.
The twentieth century’s greatest pianist Vladimir Horowitz (arguments?) plays Domenico Scarlatti’s Keyboard Sonata in B minor, K. 87. Baroque composers Scarlatti, George Frideric Handel, and JS Bach were all born in 1685.
When I was a post doc at BU in the nineties, I used to go to a cafe on Commonwealth Ave just down the street from my office on Cummington Street. I don’t remember the name of the place but I do remember getting a cappuccino that looked something like this:Now, I usually get something that looks like this: Instead of a light delicate layer of milk with a touch of foam floating on rich espresso, I get a lump of dry foam sitting on super acidic burnt quasi-espresso. How did this unfortunate circumstance occur? I’m not sure but I think it was because of Starbucks. Scaling up massively means you get what the average customer wants, or Starbucks thinks they want. This then sets a standard and other cafes have to follow suit because of consumer expectations. Also, making a real cappuccino takes training and a lot of practice and there is no way Starbucks could train enough baristas. Now, I’m not an anti-Starbucks person by any means. I think it is nice that there is always a fairly nice space with free wifi on every corner but I do miss getting a real cappuccino. I believe there is a real business opportunity out there for cafes to start offering better espresso drinks.
Here is a piece by turn of the last century British composer Samuel Coleridge-Taylor, named after the poet who wrote The Rime of the Ancient Mariner. Coleridge-Taylor met with some racism because he was of mixed African descent but had achieved some renown before dying at the young age of 37.
The New York Times Magazine has a nice profile on theoretical neuroscientist Sebastian Seung this week. I’ve known Sebastian since we were graduate students in Boston in the 1980’s. We were both physicists then and both ended up in biology though through completely different paths. The article focuses on his quest to map all the connections in the brain, which he terms the connectome. Near the end of the article, neuroscientist Eve Marder of Brandeis comments on the endeavor with the pithy remark that “If we want to understand the brain, the connectome is absolutely necessary and completely insufficient.” To which the article ends with
Seung agrees but has never seen that as an argument for abandoning the enterprise. Science progresses when its practitioners find answers — this is the way of glory — but also when they make something that future generations rely on, even if they take it for granted. That, for Seung, would be more than good enough. “Necessary,” he said, “is still a pretty strong word, right?”
Personally, I am not sure if the connectome is necessary or sufficient although I do believe it is a worthy task. However, my hesitation is not because of what was proposed in the article, which is that we exist in a fluid world and the connectome is static. Rather, like Sebastian, I do believe that memories are stored in the connectome and I do believe that “your” connectome does capture much of the essence of “you”. Many years ago, the CPU on my computer died. Our IT person swapped out the CPU and when I turned my computer back on, it was like nothing had happened. This made me realize that everything about the computer that was important to me was stored on the hard drive. The CPU didn’t matter even though every thing a computer did relied on the CPU. I think the connectome is like the hard drive and trying to figure out how the brain works from it is like trying to reverse engineer the CPU from the hard drive. You can certainly get clues from it such as information is stored in binary form but I’m not sure if it is necessary or sufficient to figure out how a computer works by recreating an entire hard drive. Likewise, someday we may use the connectome to recover lost memories or treat some diseases but we may not need it to understand how a brain works.
The most dangerous form of bias is when you are unaware of it. Most people are not overtly racist but many have implicit biases that can affect their decisions. In this week’s New York Times, Claudia Dreifus has a conversation with Stanford psychologist Jennifer Eberhardt, who has been studying implicit biases in people experimentally. Among her many eye opening studies, she has found that convicted criminals whose faces people deem more “black” are more likely to be executed than those that are not. Chris Mooney has a longer article on the same topic in Mother Jones. I highly recommend reading both articles.