Category: Uncategorized
BD2K2U2B
NIH recently announced a BD2K initiative. A number of new centers were funded. I am honored to be included on the roster of one. Is it progress? Yes absolutely. Is it the end point? I don’t think so.
In our COMPUTATIONAL BRIDGE TO EXPERIMENTS initiative we argued for a longer term view on Computational Thinking about Biology.
There are two relevant quotes
“The key to good decision making is not knowledge. It is understanding. We are swimming in the former. We are desperately lacking in the latter.”
― Malcolm Gladwell,
“Any fool can know. The point is to understand.” Albert Einstein
These are perhaps taken out of context and a bit extreme but certainly do not lack credibility…
However, these quotes do suggest that we should stop thinking about computer science and computational biology just as a signal/text processing field supporting the Data to Knowledge Transformation.
We need to start thinking about computational biology or genomic systems biology as a closed loop (BD2K2U2B):
Biological Data -> Knowledge -> Understanding -> Biology -> Biological Data -> ….
If you are a biomedical engineer or a synthetic biologist you probably would argue that in order to really understand something one needs to be able to build it (2B could mean to Build) or at least be able to reprogram it (e.g., work by a joint PhD student Esther Rheinbay with Mario Suva in Brad Bernstein’s, lab Mario Suva and Esther Rheinbay et al). This independent perspective from George Church is also useful.
However, some scientists or philosophers of science would argue that understanding is equal to the ability to ask good questions. For a full perspective on this concept see our COmputational BRidges To EXperiments framework.
We equate UNDERSTANDING with the ability to predict accurately enough to enable synthetic design and we propose to quantify each experiment in terms of what improvement in prediction accuracy we get after conducting the experiment (INFORMATION GAIN). This enables us to prioritize experiments (using ACTIVE LEARNING) depending on the amount of information we obtain, i.e., increase in understanding.
Can conflicting opinions be both right ?
New York Times recently reported that John Paulson donated $400 million to endow Harvard Engineering School. Many of us affiliated with science and engineering were rather thrilled about this generous charitable gesture and the promise it holds.
However, the donation also received a critical response from many prominent people that suggested the money could have been better spent on a contribution to the poor.
Who is right?
I heard this old story a while back. A very bright rabbinical student is doing an internship where he is observing a renowned and highly respected old Rabbi as he is lending his wisdom to his community.
Warning: this is an old story with the out of date cultural flavors and traditional roles (tradition is not always a good thing unless it evolves).
A struggling married couple enters the Rabbi's studio and bitterly complain about each other .
The wife asserts that her husband does not work hard enough, does not provide for his family and does not dedicate enough time to study the Talmud with the boys. As a result they cannot fulfill their mission as a good religious family.
The Rabbi says " You are right, you are right ...".
Then the husband complains that his wife does not fulfill her traditional roles in taking care of the family and teaching the girls to do the same.As a result they cannot fulfill their mission as a good religious family.
Rabbi repeats: "You are right, you are right ...".
The young bright student is perplexed and timidly asks the Rabbi. "Rabbi, with all due respect, they contradict each other, they can't be both right"
.. and the Rabbi replies ... "You are also right " !
Fast forward back to modern times and the Paulson charitable donation, and we get a series of tweets from a prominent writer.
"It came down to helping the poor or giving the world's richest university $400 [million] it doesn't need. Wise choice John!" Gladwell tweeted.
Read more: http://www.businessinsider.com/defense-of-john-paulson-harvard-donation-2015-6#ixzz3cEnPxY00.
Its a really interesting argument. However, numerous people came to John Paulson's defense as documented in this piece.
But the opinion I like the most came from one hedge fund manager:
"Still, others felt like Gladwell had a right to his opinion, but Paulson also had the right to donate his money.
"I think that guy, Malcolm Gladwell, actually has an argument from a social standpoint," acknowledged one hedge fund portfolio manager. "The disparity of wealth in this country is going to be a problem. The middle class is shrinking. It's harder and harder for people to make it. Gladwell has the right to his opinion, but John Paulson has the right to do what he wants with his money."
Read more: http://www.businessinsider.com/defense-of-john-paulson-harvard-donation-2015-6#ixzz3cEo5pKYB
I guess he is also right.
For the record, there are scientists and engineers everywhere who do worry about people who need it most.
Here are a few examples: engineering fo the developing world, computer science and society and genomic medicine for the poor:
We need to do more for sure!
My daughter who just graduated high school, offered another opinion. "Money is either spent and wasted or used to help cultivate something".
One thing that is hard to dispute. Allston will finally have one modern coffee shop. Welcome aboard Pete's and Starbucks. After all, mathematicians, scientists and engineers are just "machines that convert coffee into theorems discoveries and inventions". So the future looks promising for the new school.
Wisdom from the young generation: We fear “the new”
"Emily Bruell, a valedictorian at Roaring Forks High School in Carbondale, Colorado, delivered a powerful message to her fellow graduates. Objectively, it was about labels. But the ultimate takeaway was the importance of courage.
She acknowledged the tendency we all have when faced with something new:
“And the easiest thing to do when you are scared of something is to ignore it, to just keep on acting the way you did before you got scared.”"
Many scientists face this response to new proposals, ideas or beliefs.
Contrast this simple but profound quote to the long speech from Bill Clinton that the university probably paid $100,000 or more for.
He talked about the significance of education and its role in advancing society. We all agree with the importance of education of course. Education is essential to create useful advances but is it sufficient?
He concluded his speech with this recommendation:
THE WORLD IS IN A RACE BETWEEN THE POSITIVE AND THE NEGATIVE FORCES OF OUR INTERDEPENDENCE. GETTING OUT OF EACH OTHER IS NOT AN OPTION. THE ONLY OPTION IS VICTORY FOR THE POSITIVE FORCES. AND NONE OF US CAN DO THAT ALONE. SO JOIN THE FIGHT. AND GOOD LUCK.
From: Clinton commensement speech to NYU
An inspiring speech of course from a brilliant man with many off-scale accomplishments. But I think we all read this somewhere, and heard about "positive or negative" or "good and "bad" a "few" times... Oh yes, in virtually every religious speech ...or text. Is this a sound advice, yes, whether one is religious or not. Is it new or novel, not so much. Also, each one of us also has a different definition of positive or negative... and isn't "fight" negative almost by definition. How about stand-up to by creative innovation?
Perhaps Bill Clinton knows what the young student observed --- it is hard to teach people something they don't know already, it will mostly create fear and rejection Unless we find ways to change that.
The young student was talking about "new vs old". That distinction is pretty clear. The society's response to new is a very important point here. Its fear, rejection, or simply ignoring it.
This has to improve.
Bill Clinton talks about education and tightly connects it to "invention". Education does not create invention. The search for novelty and change does. In order to experiment and adopt the new we must have courage to consider and accept it.
Education + Innovation + Removing the barriers (e.g. fear) to integrating innovation into the real world is my proposal for catalyzing more rapid advances, technological, medical, political or societal.
See my blog on Agile and Lean Education: Lessons from Bacteria
Go NEW Generation !
p.s. Here is one example of a cool idea from a jointly supervised PhD student, Clark Freifeld (BS Yale, MA MIT, PhD Boston University) who won the Engineering Best Societal Dissertation Award.
Crossing Epidemiology and Public Health with Twitter cannot be found in textbooks.... and I can brag about it because the idea and the solution are not mine.
But I did sign Clark's thesis approval papers and I am already trying to integrate it into other significant real world problems....
Towards “Agile and Lean” Education: Learning about “Learning” from Bacteria
"We Don’t See Things As They Are, We See Them As We Are"
Rabbi Shemuel ben Nachmani, as quoted in the Talmudic tractate Berakhot (55b.) from quotation investigator...
Putting this old wisdom together with some new wisdom in "Singularity is Near" should we rethink EDUCATION?
In other words, knowledge and technology are growing at a dizzying pace. In many fields, there are more scientists working today than during the entire history of humanity and the technology keeps accelerating. Thus, we might expect to frequently reformulate our views of entire disciplines based on the increased bandwidth of discoveries, and subjective views of a discipline might not be consistent with the rapidly evolving community view. I will start with a few BASIC questions and follow-up with a proposed new solution inspired by "bacterial learning".
1. Size of Knowledge Modules Matters: Smaller is Better?
Should we continue writing, studying and learning from 1000 page textbooks?
I have enormous respect for the brilliant scholarship and dedication needed to produce such pyramids of knowledge based on wide foundations. They are built to survive. However, most textbooks are written by single authors with their own perspective on the field... and reflecting their own learning process and understanding rather the objective view of the discipline (if there is such a thing). They do not necessarily attempt to speed-up learning but indoctrinate students with a particular world perspective. Moreover, by the time the book is written (3-10 years) the field evolves significantly (remember "singularity is near").
I am not opposed to textbooks. One example of a knowledge pyramid that stands up above others in the field of computer science is the Art of Computer Programming by Don Knuth. There are many others pyramids in every field (e.g. Feynman Lectures on Physics) but this monumental Art of the Art stands alone in CS. I loved it. It challenges any pre-conception of what a single human mind is capable of. Nevertheless, it emphasizes certain parts of the Art and may not be the best way to learn computer science for everyone. As a result the "speed" of propagation of algorithmic ideas across disciplines is relatively slow. This is unfortunate, since Computer Science is a beautiful field and at least in my view algorithmic thinking might be as broadly applicable as calculus or algebra (that remain important of course).
Along the same vein, should we continue teaching semester long courses ?
The alternative is shorter open access plug-in modules, that can be integrated together as legos across books, presentations, videos, games, perspectives, real world examples, inter-disciplinary observations and more. This process can lead to building societies of knowledge reminiscent of the "knowledge" produced and evolved by societies of bacteria. However, we can use modern technology to search, integrate and evolve this knowledge.
2. Learning in Old (Classical), Possible (Academic) and Real Worlds.
2.1 Statistics:
My first example is from the old world of statistics and its application to science or medicine. Statistics is typically taught from the foundation, built by the brilliant mathematical prowess of people like Fisher, Kolmogorov, Pearson and others.
But this foundation is not always properly integrated into practice. Consider the recent debate about p-values , and the fact many scientists do not understand it or other simple statistical concepts. Most statistics courses or textbooks present the definition and textbook uses of a concept. Rarely do we get to see the misuses and misrepresentations. Even more rarely do we see modern thinking. For instance, the simplest way to think about assessing the probability of obtaining a result by chance (not the probability it is true or false as sometimes interpreted by scientist) is simply by exhaustively enumerating all possibilities on a computer. We do it by permutations. This brute force approach avoids making assumptions not satisfied in the real world. But permutation based analysis has become feasible only due to the advent of modern computers that can compute such permutations very quickly. This was not available to the founders of statistics.
Bottom-up teaching makes it difficult for many smart but information, math or knowledge challenged professionals that are seeking to quickly learn important concepts but rarely see or use these ideas integrated in their own "environment" as bacteria might. This is particularly true for fields such as medicine, biomedical engineering and others that are increasingly built on breadth of rapidly evolving knowledge.
The result is not optimal. In particular consider this extract from a recent article (interview with Zak Kohane).
"A related, pedagogical goal is enhancing physicians’ search and numeracy skills. “The best predictor of a doctor ordering a genetic test is knowing whether the patient asked for it,” Kohane continues—usually because that patient has searched on Google. But researchers have found that even “well-trained physicians are both uncomfortable and incompetent in interpreting these tests,” often because they lack numeracy skills. One of Kohane’s former students, Arjun Manrai ’08, asked doctors and residents at a Boston hospital a simple question: “If a test to detect a disease whose prevalence is one in a thousand has a false positive rate of 5 percent, what is the chance that a person found to have a positive result actually has the disease?” The test will yield 50 false positives in a population of 1,000, but only one patient will actually be ill—so a positive test result would mean that a patient has only about a 2 percent chance of having the disease. More than three-quarters of the respondents in the study got this wrong; the most common answer was 95 percent."
What is the point ? We need to develop methodologies to extract, teach, modularize, simplify, exchange, search and make portable "knowledge modules" and make them quickly available to many fields and real world learning.
The problem is lack of integration and creative application of knowledge in our own environment, which bacteria do very well and we do not. Without that trial and error in the real world, we do not really learn, at least not quickly.
3. Agile and Lean Learning is Built for Dissemination and Evolution of Knowledge: A Lesson from Bacteria
I now review some basic principles of "bacterial learning" and argue they should be adopted in education. These principles incentivize the simplification, modularization, evolvability, transportability and miniaturization of knowledge leading to higher bandwidth in creativity, diversification and dissemination?
One can equate learning to evolution of knowledge. Should we learn from evolution of bacteria to evolve our knowledge in most expedient fashion rather than from "advanced" evolutionary organisms that are "stuck" with large, complex biological modules that are too complex to modify easily. Bacteria evolve by inheriting, duplicating, modifying, exchanging, combining, erasing, keeping dormant, contextually activating, trying, conditioning, genes and modules,
What makes bacteria so good at "learning".
- Simple systems and many small conserved, partially-variable and ultra-variable exchangeable modules or even smaller motifs.
- Easy mechanisms for "recombination" of knowledge.
- Rapid mechanism for innovation via horizontal (lateral transfer) from other bacteria (interdisciplinary learning) and vertical evolution from ancestors (bottom-up learning).
- Trial and error of innovative solutions in real environments.
- Societies of distributed knowledge and their interactions with the surrounding ecology.
- Willingness to cannibalize less fit "ideas" quickly.
- Altruism and community spirit to exchange useful knowledge (genes and modules) quickly.
- Lack of central authorities (except basic chemistry).
- Learning from simpler/faster organisms (phages).
- Balancing the speed of learning and survival risk depending on the urgency of producing solutions.
In truth, viruses "learn" even faster. However, viruses are not independently living organisms and do not have the foundation to survive on their own.
These ideas are just abstractions. There are many computational or Data Science based opportunities to improve on bacterial learning, e.g., by building better tools to search for relevant knowledge. Wikipedia is just one example. Knol (by Udi Manber from Google) was another attempt.
4. Proposal: Three Tier Knowledge Systems
The software industry has been recently moving to an "Agile and Lean" mode of development.
I propose to rethink education in terms of these ideas and in particular use the paradigm of bacterial evolution as a new model for "lean and agile" education aimed to catalyze creativity, diversification, and innovation.
In our joint work with Rich Roberts and Yu Zheng we defined a three tier "learning system" for bacteria. We suggested that the bacterial gene compendium consists of three classes of genes: conserved, segmentally variable and highly variable genes. Genes and gene modules are the building blocks of microbial knowledge.
Conserved units of knowledge are highly conserved (in terms of their text = sequence) in virtually all bacteria. These units form the foundation of knowledge, allowing bacteria to survive. Segmentally variable units of knowledge consist of multi-part units, that are comprised of conserved sub-units and variable sub-units that are changing locally or being exchanged rapidly in response to the needs of being fit. Finally, highly variable units of knowledge evolve very rapidly and have few conserved parts that we can recognize (except the basic structure on which the rapid changes can take place). This organization enables bacteria to optimize the most important selective pressure in nature: diversification. Dyson Freeman stated a related idea in the context of human languages: "Just as speciation gave life freedom to experiment with diversity of form and function, the differentiation of languages gave humanity freedom to experiment with diversity of social and cultural traditions". But the paradigm is naturally broader and applies to any form of knowledge.
We have nothing similar and widely available in the educational system that is more geared towards "conserved" knowledge and building foundations. But one must wonder whether this serves the needs of people who deliver the knowledge rather the need to match the pace of knowledge evolution and the best tools of "fitness" of the students.
The alternative is "real world, top-down, bottom-up and side-ways learning with a much wider range of alternatives for learning".
"Doing real world projects is, I think, the best way to learn and also to engage the world and find out what the world is all about". Ray Kurzweil.
A while back I was giving my daughter who was 12 at at time a very hard time about discipline or something, either in sports or school. I used the quote "What does not kill you will make you stronger". She was getting increasingly frustrated with my style of "teaching" and finally stepped as hard as she could on my toe. I was a bit shocked and asked her, why did you do that. She said "I just made you stronger". Not a lesson one can learn from a big textbook.
I will not continue expanding on this because I risk 'seeing things the way I see them instead of the way they are". I am a genomic system biology scientist and know about education only from my experience as a professor and a parent. Hope smarter and more knowledgeable educational folks take notice and make sense out of this rambling.
Supplement:
Few examples of immersive learning... I will keep collecting and posting. Please send me email if you want to be listed here.
Small World Initiative by Jo Handelsman.
COMBREX (Computational Bridges to Experiments) by Simon Kasif, Martin Steffen and Richard Roberts (simple introduction,
Undergraduate Robotics Education
NIH Undergraduate Biomedical Competition
Data Science Tools I have used for Systems Biology of Human Disease
Translational medicine in your "garage"
Goodbye to “orgo” ? A new engineering based medical school…
I just learned from Gene Robinson that University of Illinois is opening a new engineering based medical school. This is a novel and interesting development !
I recall as a faculty at Johns Hopkins many of our gifted engineering, physics or computer science undergrads struggled with orgo (Organic Chemistry). It was the big barrier to the top medical schools and many smart pre-meds that received a C in this class and would not see Harvard Medical School or Johns Hopkins at least until their residency...
I never understood why this class is a key requirement for many medical schools given the breadth of knowledge needed in medicine. Drugs are important. Chemistry is very important of course but one can imagine other courses that could be equally useful as a screen for a future physician.
When I jokingly suggested that perhaps it should be dropped as a requirement and become an option or module depending on emphasis, one of my friends and colleagues who is a Professor of Medicine at Harvard Medical School commented ..
"No orgo? How will med students support themselves on the side making crystal meth?..".
Clearly a doctor with as sense of humor, but more seriously, medicine is a problem solving discipline that is becoming increasingly driven by computational technology and thinking, engineering and information.
A thought provoking presentation was given a while back by Danny Hillis, who is never boring...
In general, I can imagine a broader slice of relevant topics to screen for best physicians (e.g., statistics, algorithms, logic, chemistry (physical, bio, organic, etc), biology, systems biology, neuroscience, genetics) using a more flexible, modular educational system as discussed in my "agile education" blog. The emphasis should be on motivating and selecting the best talent, rather than loosing gifted future physicians that do not excel in a particular subfield needed to build the vast arsenal of knowledge and skill to be a top physician. Once this pool is selected, they can fill the needed gaps. So NO narrowly defined requirements!
On scientists and boxers
I just ran into an article in Boston Globe on how John Quack enbush is planning to fight cancer by boxing.
Anyway to fight cancer should be a good thing. What provoked me in this article is the quote:
‘I know a lot of people think I am crazy doing this. But I think what we’re doing is a metaphor for what patients go through.’
John Quackenbush, physicist at the Dana-Farber Cancer Institute and new boxer
No John, hopefully you will never know what patients go through and comparing training and a three round boxing match with another amateur to the suffering cancer patients and their families go through is offensive.
Perhaps try a three months daily bout with Mike Tyson, assuming he does not feel like knocking you cold in the first second of the match.
I would like to propose that Boston Globe covers Arthur Pardee at Dana Farber, an inspiring scientist not an amateur boxer-scientist. Arthur is 94 years old. But he is still thinking about cancer and the knowledge he produced and catalyzed inspires us daily. I am also told he shows up in his office at Farber. He also plays the cello. I think it's a great story to cover.
Arthur Pardee is a humble scientist who made countless and seminal contributions to biology and cancer research.
So let me convert my indignation into a potentially useful suggestion.
I propose crowdfunding a new campaign for understanding cancer and relevant physiology in honor of Arthur Pardee.
We can stand up to cancer on his shoulders to catalyze the quest for understanding, preventing and curing cancer. He is a living inspiration to all of us.
I am personally pledging a $1000 to start this campaign, not to mention many work hours and infinite passion working on computational biology of human disease.
I do appreciate the effort by John. I know him well and he typically does what he can to contribute. However, I think we need higher aims for inspiring the science and medicine of cancer than the boxing metaphor. Arthur is the best example of aiming higher.
The campaign we need is for a better understanding: "Know Your Enemy".
From Wikipedia, The Art of War
"So it is said that if you know your enemies and know yourself, you can win a hundred battles without a single loss.If you only know yourself, but not your opponent, you may win or may lose. If you know neither yourself nor your enemy, you will always endanger yourself."
Here are a few examples how better understanding leads to novel ideas and clinically viable solutions.
Predicting Drug Targets in Cancer
Monitoring Drug Response in the Tumor
Reprogramming Cancer Stem Cells
Cancer Drivers with Systems Biology
Cancer Panels for Precision Medicine
The only thing we want to fight is ignorance, apathy and lack creativity. It will take all we can manufacture to stand-up to cancer.
On fashion…
"There always is a big difference between those who are fashionable and those who truly made a difference". Zak Kohane.
For aspiring visionaries…
"You have to be a little clueless to be a real visionary"... Simon Kasif -- but I don't recall if I heard/saw this somewhere...
Fame and Real Work
"Nobody is too famous to do real work" , Rich Roberts.
Nature and Imagination
15 years ago when I was getting immersed in computational genomics I had a conversation with my good friend David Lipman. I was observing that when I was working in Artificial Intelligence and Computer Science many of us were highly motivated by the famous quote from Albert Einstein that "Imagination is more important than Knowledge"...
However, in Biology it appears that Knowledge is very important... and many creative ideas end up failing because of constraints imposed by Nature.
David, who has been working in the field much longer than me commented back;
"Perhaps Nature Has a Bigger Imagination"
(see slide below for my illustration of his observation):
All pictures on this slide were found on the web... my deep thanks to the brilliant artists who produced this art..
