Tagged: Computational Biology Toggle Comment Threads | Keyboard Shortcuts

  • richardmitnick 11:09 am on July 1, 2021 Permalink | Reply
    Tags: "The power of two", , , , , Computational Biology, , , Ellen Zhong, , , , Software called cryoDRGN   

    From Massachusetts Institute of Technology (US) : “The power of two” 

    MIT News

    From Massachusetts Institute of Technology (US)

    June 30, 2021
    Saima Sidik | Department of Biology

    Graduate student Ellen Zhong helped biologists and mathematicians reach across departmental lines to address a longstanding problem in electron microscopy.

    1
    Ellen Zhong, a graduate student from the Computational and Systems Biology Program, is using a computational pattern-recognition tool called a neural network to study the shapes of molecular machines.
    Credit: Matthew Brown.

    MIT’s Hockfield Court is bordered on the west by the ultramodern Stata Center, with its reflective, silver alcoves that jut off at odd angles, and on the east by Building 68, which is a simple, window-lined, cement rectangle. At first glance, Bonnie Berger’s mathematics lab in the Stata Center and Joey Davis’s biology lab in Building 68 are as different as the buildings that house them. And yet, a recent collaboration between these two labs shows how their disciplines complement each other. The partnership started when Ellen Zhong, a graduate student from the Computational and Systems Biology (CSB) Program, decided to use a computational pattern-recognition tool called a neural network to study the shapes of molecular machines. Three years later, Zhong’s project is letting scientists see patterns that run beneath the surface of their data, and deepening their understanding of the molecules that shape life.

    Zhong’s work builds on a technique from the 1970s called cryo-electron microscopy (cryo-EM), which lets researchers take high-resolution images of frozen protein complexes. Over the past decade, better microscopes and cameras have led to a “resolution revolution” in cryo-EM that’s allowed scientists to see individual atoms within proteins. But, as good as these images are, they’re still only static snapshots. In reality, many of these molecular machines are constantly changing shape and composition as cells carry out their normal functions and adjust to new situations.

    Along with former Berger lab member Tristan Belper, Zhong devised software called cryoDRGN. The tool uses neural nets to combine hundreds of thousands of cryo-EM images, and shows scientists the full range of three-dimensional conformations that protein complexes can take, letting them reconstruct the proteins’ motion as they carry out cellular functions. Understanding the range of shapes that protein complexes can take helps scientists develop drugs that block viruses from entering cells, study how pests kill crops, and even design custom proteins that can cure disease. Covid-19 vaccines, for example, work partly because they include a mutated version of the virus’s spike protein that’s stuck in its active conformation, so vaccinated people produce antibodies that block the virus from entering human cells. Scientists needed to understand the variety of shapes that spike proteins can take in order to figure out how to force spike into its active conformation.

    Getting off the computer and into the lab

    Zhong’s interest in computational biology goes back to 2011 when, as a chemical engineering undergrad at the University of Virginia (US), she worked with Professor Michael Shirts to simulate how proteins fold and unfold. After college, Zhong took her skills to a company called D. E. Shaw Research, where, as a scientific programmer, she took a computational approach to studying how proteins interact with small-molecule drugs.

    “The research was very exciting,” Zhong says, “but all based on computer simulations. To really understand biological systems, you need to do experiments.”

    This goal of combining computation with experimentation motivated Zhong to join MIT’s CSB PhD program, where students often work with multiple supervisors to blend computational work with bench work. Zhong “rotated” in both the Davis and Berger labs, then decided to combine the Davis lab’s goal of understanding how protein complexes form with the Berger lab’s expertise in machine learning and algorithms. Davis was interested in building up the computational side of his lab, so he welcomed the opportunity to co-supervise a student with Berger, who has a long history of collaborating with biologists.

    Davis himself holds a dual bachelor’s degree in computer science and biological engineering, so he’s long believed in the power of combining complementary disciplines. “There are a lot of things you can learn about biology by looking in a microscope,” he says. “But as we start to ask more complicated questions about entire systems, we’re going to require computation to manage the high-dimensional data that come back.”


    Reconstructing Molecules in Motion.

    Before rotating in the Davis lab, Zhong had never performed bench work before — or even touched a pipette. She was fascinated to find how streamlined some very powerful molecular biology techniques can be. Still, Zhong realized that physical limitations mean that biology is much slower when it’s done at the bench instead of on a computer. “With computational research, you can automate experiments and run them super quickly, whereas in the wet lab, you only have two hands, so you can only do one experiment at a time,” she says.

    Zhong says that synergizing the two different cultures of the Davis and Berger labs is helping her become a well-rounded, adaptable scientist. Working around experimentalists in the Davis lab has shown her how much labor goes into experimental results, and also helped her to understand the hurdles that scientists face at the bench. In the Berger lab, she enjoys having coworkers who understand the challenges of computer programming.

    “The key challenge in collaborating across disciplines is understanding each other’s ‘languages,’” Berger says. “Students like Ellen are fortunate to be learning both biology and computing dialects simultaneously.”

    Bringing in the community

    Last spring revealed another reason for biologists to learn computational skills: these tools can be used anywhere there’s a computer and an internet connection. When the Covid-19 pandemic hit, Zhong’s colleagues in the Davis lab had to wind down their bench work for a few months, and many of them filled their time at home by using cryo-EM data that’s freely available online to help Zhong test her cryoDRGN software. The difficulty of understanding another discipline’s language quickly became apparent, and Zhong spent a lot of time teaching her colleagues to be programmers. Seeing the problems that nonprogrammers ran into when they used cryoDRGN was very informative, Zhong says, and helped her create a more user-friendly interface.

    Although the paper announcing cryoDRGN was just published in February, the tool created a stir as soon as Zhong posted her code online, many months prior. The cryoDRGN team thinks this is because leveraging knowledge from two disciplines let them visualize the full range of structures that protein complexes can have, and that’s something researchers have wanted to do for a long time. For example, the cryoDRGN team recently collaborated with researchers from Harvard and Washington universities to study locomotion of the single-celled organism Chlamydomonas reinhardtii. The mechanisms they uncovered could shed light on human health conditions, like male infertility, that arise when cells lose the ability to move. The team is also using cryoDRGN to study the structure of the SARS-CoV-2 spike protein, which could help scientists design treatments and vaccines to fight coronaviruses.

    Zhong, Berger, and Davis say they’re excited to continue using neural nets to improve cryo-EM analysis, and to extend their computational work to other aspects of biology. Davis cited mass spectrometry as “a ripe area to apply computation.” This technique can complement cryo-EM by showing researchers the identities of proteins, how many of them are bound together, and how cells have modified them.

    “Collaborations between disciplines are the future,” Berger says. “Researchers focused on a single discipline can take it only so far with existing techniques. Shining a different lens on the problem is how advances can be made.”

    Zhong says it’s not a bad way to spend a PhD, either. Asked what she’d say to incoming graduate students considering interdisciplinary projects, she says: “Definitely do it.”

    See the full article here .


    five-ways-keep-your-child-safe-school-shootings
    Please help promote STEM in your local schools.

    Stem Education Coalition

    MIT Seal

    USPS “Forever” postage stamps celebrating Innovation at MIT.

    MIT Campus

    Massachusetts Institute of Technology (US) is a private land-grant research university in Cambridge, Massachusetts. The institute has an urban campus that extends more than a mile (1.6 km) alongside the Charles River. The institute also encompasses a number of major off-campus facilities such as the MIT Lincoln Laboratory, the Bates Center, and the Haystack Observatory, as well as affiliated laboratories such as the Broad and Whitehead Institutes.

    Founded in 1861 in response to the increasing industrialization of the United States, Massachusetts Institute of Technology (US) adopted a European polytechnic university model and stressed laboratory instruction in applied science and engineering. It has since played a key role in the development of many aspects of modern science, engineering, mathematics, and technology, and is widely known for its innovation and academic strength. It is frequently regarded as one of the most prestigious universities in the world.

    As of December 2020, 97 Nobel laureates, 26 Turing Award winners, and 8 Fields Medalists have been affiliated with MIT as alumni, faculty members, or researchers. In addition, 58 National Medal of Science recipients, 29 National Medals of Technology and Innovation recipients, 50 MacArthur Fellows, 80 Marshall Scholars, 3 Mitchell Scholars, 22 Schwarzman Scholars, 41 astronauts, and 16 Chief Scientists of the U.S. Air Force have been affiliated with Massachusetts Institute of Technology (US) . The university also has a strong entrepreneurial culture and MIT alumni have founded or co-founded many notable companies. Massachusetts Institute of Technology (US) is a member of the Association of American Universities (AAU).

    Foundation and vision

    In 1859, a proposal was submitted to the Massachusetts General Court to use newly filled lands in Back Bay, Boston for a “Conservatory of Art and Science”, but the proposal failed. A charter for the incorporation of the Massachusetts Institute of Technology, proposed by William Barton Rogers, was signed by John Albion Andrew, the governor of Massachusetts, on April 10, 1861.

    Rogers, a professor from the University of Virginia (US), wanted to establish an institution to address rapid scientific and technological advances. He did not wish to found a professional school, but a combination with elements of both professional and liberal education, proposing that:

    “The true and only practicable object of a polytechnic school is, as I conceive, the teaching, not of the minute details and manipulations of the arts, which can be done only in the workshop, but the inculcation of those scientific principles which form the basis and explanation of them, and along with this, a full and methodical review of all their leading processes and operations in connection with physical laws.”

    The Rogers Plan reflected the German research university model, emphasizing an independent faculty engaged in research, as well as instruction oriented around seminars and laboratories.

    Early developments

    Two days after Massachusetts Institute of Technology (US) was chartered, the first battle of the Civil War broke out. After a long delay through the war years, MIT’s first classes were held in the Mercantile Building in Boston in 1865. The new institute was founded as part of the Morrill Land-Grant Colleges Act to fund institutions “to promote the liberal and practical education of the industrial classes” and was a land-grant school. In 1863 under the same act, the Commonwealth of Massachusetts founded the Massachusetts Agricultural College, which developed as the University of Massachusetts Amherst (US)). In 1866, the proceeds from land sales went toward new buildings in the Back Bay.

    Massachusetts Institute of Technology (US) was informally called “Boston Tech”. The institute adopted the European polytechnic university model and emphasized laboratory instruction from an early date. Despite chronic financial problems, the institute saw growth in the last two decades of the 19th century under President Francis Amasa Walker. Programs in electrical, chemical, marine, and sanitary engineering were introduced, new buildings were built, and the size of the student body increased to more than one thousand.

    The curriculum drifted to a vocational emphasis, with less focus on theoretical science. The fledgling school still suffered from chronic financial shortages which diverted the attention of the MIT leadership. During these “Boston Tech” years, Massachusetts Institute of Technology (US) faculty and alumni rebuffed Harvard University (US) president (and former MIT faculty) Charles W. Eliot’s repeated attempts to merge MIT with Harvard College’s Lawrence Scientific School. There would be at least six attempts to absorb MIT into Harvard. In its cramped Back Bay location, MIT could not afford to expand its overcrowded facilities, driving a desperate search for a new campus and funding. Eventually, the MIT Corporation approved a formal agreement to merge with Harvard, over the vehement objections of MIT faculty, students, and alumni. However, a 1917 decision by the Massachusetts Supreme Judicial Court effectively put an end to the merger scheme.

    In 1916, the Massachusetts Institute of Technology (US) administration and the MIT charter crossed the Charles River on the ceremonial barge Bucentaur built for the occasion, to signify MIT’s move to a spacious new campus largely consisting of filled land on a one-mile-long (1.6 km) tract along the Cambridge side of the Charles River. The neoclassical “New Technology” campus was designed by William W. Bosworth and had been funded largely by anonymous donations from a mysterious “Mr. Smith”, starting in 1912. In January 1920, the donor was revealed to be the industrialist George Eastman of Rochester, New York, who had invented methods of film production and processing, and founded Eastman Kodak. Between 1912 and 1920, Eastman donated $20 million ($236.6 million in 2015 dollars) in cash and Kodak stock to MIT.

    Curricular reforms

    In the 1930s, President Karl Taylor Compton and Vice-President (effectively Provost) Vannevar Bush emphasized the importance of pure sciences like physics and chemistry and reduced the vocational practice required in shops and drafting studios. The Compton reforms “renewed confidence in the ability of the Institute to develop leadership in science as well as in engineering”. Unlike Ivy League schools, Massachusetts Institute of Technology (US) catered more to middle-class families, and depended more on tuition than on endowments or grants for its funding. The school was elected to the Association of American Universities (US)in 1934.

    Still, as late as 1949, the Lewis Committee lamented in its report on the state of education at Massachusetts Institute of Technology (US) that “the Institute is widely conceived as basically a vocational school”, a “partly unjustified” perception the committee sought to change. The report comprehensively reviewed the undergraduate curriculum, recommended offering a broader education, and warned against letting engineering and government-sponsored research detract from the sciences and humanities. The School of Humanities, Arts, and Social Sciences and the MIT Sloan School of Management were formed in 1950 to compete with the powerful Schools of Science and Engineering. Previously marginalized faculties in the areas of economics, management, political science, and linguistics emerged into cohesive and assertive departments by attracting respected professors and launching competitive graduate programs. The School of Humanities, Arts, and Social Sciences continued to develop under the successive terms of the more humanistically oriented presidents Howard W. Johnson and Jerome Wiesner between 1966 and 1980.

    Massachusetts Institute of Technology (US)‘s involvement in military science surged during World War II. In 1941, Vannevar Bush was appointed head of the federal Office of Scientific Research and Development and directed funding to only a select group of universities, including MIT. Engineers and scientists from across the country gathered at Massachusetts Institute of Technology (US)’s Radiation Laboratory, established in 1940 to assist the British military in developing microwave radar. The work done there significantly affected both the war and subsequent research in the area. Other defense projects included gyroscope-based and other complex control systems for gunsight, bombsight, and inertial navigation under Charles Stark Draper’s Instrumentation Laboratory; the development of a digital computer for flight simulations under Project Whirlwind; and high-speed and high-altitude photography under Harold Edgerton. By the end of the war, Massachusetts Institute of Technology (US) became the nation’s largest wartime R&D contractor (attracting some criticism of Bush), employing nearly 4000 in the Radiation Laboratory alone and receiving in excess of $100 million ($1.2 billion in 2015 dollars) before 1946. Work on defense projects continued even after then. Post-war government-sponsored research at MIT included SAGE and guidance systems for ballistic missiles and Project Apollo.

    These activities affected Massachusetts Institute of Technology (US) profoundly. A 1949 report noted the lack of “any great slackening in the pace of life at the Institute” to match the return to peacetime, remembering the “academic tranquility of the prewar years”, though acknowledging the significant contributions of military research to the increased emphasis on graduate education and rapid growth of personnel and facilities. The faculty doubled and the graduate student body quintupled during the terms of Karl Taylor Compton, president of Massachusetts Institute of Technology (US) between 1930 and 1948; James Rhyne Killian, president from 1948 to 1957; and Julius Adams Stratton, chancellor from 1952 to 1957, whose institution-building strategies shaped the expanding university. By the 1950s, Massachusetts Institute of Technology (US) no longer simply benefited the industries with which it had worked for three decades, and it had developed closer working relationships with new patrons, philanthropic foundations and the federal government.

    In late 1960s and early 1970s, student and faculty activists protested against the Vietnam War and Massachusetts Institute of Technology (US)’s defense research. In this period Massachusetts Institute of Technology (US)’s various departments were researching helicopters, smart bombs and counterinsurgency techniques for the war in Vietnam as well as guidance systems for nuclear missiles. The Union of Concerned Scientists was founded on March 4, 1969 during a meeting of faculty members and students seeking to shift the emphasis on military research toward environmental and social problems. Massachusetts Institute of Technology (US) ultimately divested itself from the Instrumentation Laboratory and moved all classified research off-campus to the MIT (US) Lincoln Laboratory facility in 1973 in response to the protests. The student body, faculty, and administration remained comparatively unpolarized during what was a tumultuous time for many other universities. Johnson was seen to be highly successful in leading his institution to “greater strength and unity” after these times of turmoil. However six Massachusetts Institute of Technology (US) students were sentenced to prison terms at this time and some former student leaders, such as Michael Albert and George Katsiaficas, are still indignant about MIT’s role in military research and its suppression of these protests. (Richard Leacock’s film, November Actions, records some of these tumultuous events.)

    In the 1980s, there was more controversy at Massachusetts Institute of Technology (US) over its involvement in SDI (space weaponry) and CBW (chemical and biological warfare) research. More recently, Massachusetts Institute of Technology (US)’s research for the military has included work on robots, drones and ‘battle suits’.

    Recent history

    Massachusetts Institute of Technology (US) has kept pace with and helped to advance the digital age. In addition to developing the predecessors to modern computing and networking technologies, students, staff, and faculty members at Project MAC, the Artificial Intelligence Laboratory, and the Tech Model Railroad Club wrote some of the earliest interactive computer video games like Spacewar! and created much of modern hacker slang and culture. Several major computer-related organizations have originated at MIT since the 1980s: Richard Stallman’s GNU Project and the subsequent Free Software Foundation were founded in the mid-1980s at the AI Lab; the MIT Media Lab was founded in 1985 by Nicholas Negroponte and Jerome Wiesner to promote research into novel uses of computer technology; the World Wide Web Consortium standards organization was founded at the Laboratory for Computer Science in 1994 by Tim Berners-Lee; the MIT OpenCourseWare project has made course materials for over 2,000 Massachusetts Institute of Technology (US) classes available online free of charge since 2002; and the One Laptop per Child initiative to expand computer education and connectivity to children worldwide was launched in 2005.

    Massachusetts Institute of Technology (US) was named a sea-grant college in 1976 to support its programs in oceanography and marine sciences and was named a space-grant college in 1989 to support its aeronautics and astronautics programs. Despite diminishing government financial support over the past quarter century, MIT launched several successful development campaigns to significantly expand the campus: new dormitories and athletics buildings on west campus; the Tang Center for Management Education; several buildings in the northeast corner of campus supporting research into biology, brain and cognitive sciences, genomics, biotechnology, and cancer research; and a number of new “backlot” buildings on Vassar Street including the Stata Center. Construction on campus in the 2000s included expansions of the Media Lab, the Sloan School’s eastern campus, and graduate residences in the northwest. In 2006, President Hockfield launched the MIT Energy Research Council to investigate the interdisciplinary challenges posed by increasing global energy consumption.

    In 2001, inspired by the open source and open access movements, Massachusetts Institute of Technology (US) launched OpenCourseWare to make the lecture notes, problem sets, syllabi, exams, and lectures from the great majority of its courses available online for no charge, though without any formal accreditation for coursework completed. While the cost of supporting and hosting the project is high, OCW expanded in 2005 to include other universities as a part of the OpenCourseWare Consortium, which currently includes more than 250 academic institutions with content available in at least six languages. In 2011, Massachusetts Institute of Technology (US) announced it would offer formal certification (but not credits or degrees) to online participants completing coursework in its “MITx” program, for a modest fee. The “edX” online platform supporting MITx was initially developed in partnership with Harvard and its analogous “Harvardx” initiative. The courseware platform is open source, and other universities have already joined and added their own course content. In March 2009 the Massachusetts Institute of Technology (US) faculty adopted an open-access policy to make its scholarship publicly accessible online.

    Massachusetts Institute of Technology (US) has its own police force. Three days after the Boston Marathon bombing of April 2013, MIT Police patrol officer Sean Collier was fatally shot by the suspects Dzhokhar and Tamerlan Tsarnaev, setting off a violent manhunt that shut down the campus and much of the Boston metropolitan area for a day. One week later, Collier’s memorial service was attended by more than 10,000 people, in a ceremony hosted by the Massachusetts Institute of Technology (US) community with thousands of police officers from the New England region and Canada. On November 25, 2013, Massachusetts Institute of Technology (US) announced the creation of the Collier Medal, to be awarded annually to “an individual or group that embodies the character and qualities that Officer Collier exhibited as a member of the Massachusetts Institute of Technology (US) community and in all aspects of his life”. The announcement further stated that “Future recipients of the award will include those whose contributions exceed the boundaries of their profession, those who have contributed to building bridges across the community, and those who consistently and selflessly perform acts of kindness”.

    In September 2017, the school announced the creation of an artificial intelligence research lab called the MIT-IBM Watson AI Lab. IBM will spend $240 million over the next decade, and the lab will be staffed by MIT and IBM scientists. In October 2018 MIT announced that it would open a new Schwarzman College of Computing dedicated to the study of artificial intelligence, named after lead donor and The Blackstone Group CEO Stephen Schwarzman. The focus of the new college is to study not just AI, but interdisciplinary AI education, and how AI can be used in fields as diverse as history and biology. The cost of buildings and new faculty for the new college is expected to be $1 billion upon completion.

    The Caltech/MIT Advanced aLIGO (US) was designed and constructed by a team of scientists from California Institute of Technology (US), Massachusetts Institute of Technology (US), and industrial contractors, and funded by the National Science Foundation (US) .

    MIT/Caltech Advanced aLigo .

    It was designed to open the field of gravitational-wave astronomy through the detection of gravitational waves predicted by general relativity. Gravitational waves were detected for the first time by the LIGO detector in 2015. For contributions to the LIGO detector and the observation of gravitational waves, two Caltech physicists, Kip Thorne and Barry Barish, and Massachusetts Institute of Technology (US) physicist Rainer Weiss won the Nobel Prize in physics in 2017. Weiss, who is also an Massachusetts Institute of Technology (US) graduate, designed the laser interferometric technique, which served as the essential blueprint for the LIGO.

    The mission of Massachusetts Institute of Technology (US) is to advance knowledge and educate students in science, technology, and other areas of scholarship that will best serve the nation and the world in the twenty-first century. We seek to develop in each member of the Massachusetts Institute of Technology (US) community the ability and passion to work wisely, creatively, and effectively for the betterment of humankind.

     
  • richardmitnick 2:05 pm on February 1, 2021 Permalink | Reply
    Tags: "Medicine by Design researchers focus on promoting self-repair of the brain", , , , Computational Biology, , Medicine by Design-a strategic research initiative working at the convergence of engineering; medicine; science to catalyze transformative discoveries in regenerative medicine., Neurobiology, Stem Cell Biology, ,   

    From University of Toronto (CA): “Medicine by Design researchers focus on promoting self-repair of the brain” 

    U Toronto Bloc

    From University of Toronto (CA)

    January 28, 2021
    Julie Crljen

    1
    Credit: Jolygon via Getty Images.

    If you asked Freda Miller 10 years ago if stem cells could be harnessed to repair brain injuries and disease, she would have said it was too early to tell.

    Today, she describes the progress that she and other regenerative medicine experts have made in understanding what regulates populations of stem cells – cells with the potential to turn into many different cell types – and the rapid advances those discoveries have driven.

    “Science is like a playground right now,” says Miller, an adjunct scientist in the neurosciences and mental health program at The Hospital for Sick Children (SickKids) and a professor in the department of molecular genetics in the University of Toronto’s Temerty Faculty of Medicine.

    “The approaches we’re using allow us to find so much information on things we could only dream of before.”

    Miller, who is also a professor at the University of British Columbia, is leading a Medicine by Design-funded team with expertise in computational biology, neurobiology, bioengineering and stem cell biology that is investigating multiple strategies to recruit stem cells to promote self-repair in the brain and in muscle. If it succeeds, the research could improve treatments for diseases such as multiple sclerosis (MS) and cerebral palsy, as well as brain injury.

    Miller’s team is one of 11 at U of T and its partner hospitals that are sharing nearly $21 million in funding from Medicine by Design over three years. Funded by a $114-million grant from the Canada First Research Excellence Fund, Medicine by Design is a strategic research initiative that is working at the convergence of engineering, medicine and science to catalyze transformative discoveries in regenerative medicine and accelerate them toward clinical impact.

    This is the second round of large-scale, collaborative team projects that Medicine by Design has funded. The support builds on the progress made in the first round of projects (2016-2019) and is spurring further innovation to push regenerative medicine forward. It also led to a 2017 publication – by many of the same researchers on Miller’s current project – in Cell Reports that essentially provided a roadmap for how brain stem cells build the brain developmentally, and then persist to function in the adult brain.

    Miller, a neuroscientist, has always been fascinated by the brain and neurons, the network of billions of nerve cells in the brain. Around 15 years ago, when she started to take an interest in the potential regenerative capabilities of stem cells, she began to wonder if she could use stem cells to treat brain injury or disease. Though too little was known about stem cells at the time, she knew that it was a question worth investigating. But she also realized that making and integrating new nerve cells, which are the working parts of brain circuits, would be a daunting task.

    “Even if you can convince the stem cells to make more neurons, those neurons then have to survive and they have to integrate into this really complex circuitry,” says Miller. “It just made sense to me that if we’re really going to test this idea of self-repair in the brain, we should go after something that’s more achievable biologically.”

    So, Miller turned her attention to a substance called myelin, which covers nerves and allows nerve impulses to travel easily. In many nervous system diseases – MS is a well-known example – and brain injuries, damage to and loss of myelin is a main factor in debilitating symptoms. Thanks in part to the team project award from Medicine by Design, Miller leads a team that has a focus on recruiting stem cells to promote the generation of myelin.

    Miller says repairing myelin, also called remyelination, will eventually help to better understand the effects of the target disease or injury, possibly even leading scientists to discover how to reverse it. Boosting myelin is a promising area of research, she adds, because it’s not an all-or-nothing situation.

    “Even a little bit of remyelination could have a big impact. You don’t have to win the whole lottery; you don’t have to have 100 per cent remyelination to have a measurable outcome.”

    The team’s work is not limited to generating myelin to treat nervous system diseases or brain injury. They are also looking at how they could recruit stem cells to generate more muscle. They are specifically looking at muscular dystrophy, but Miller says the applications from that work can be used in other diseases or situations where damage to muscles has occurred, such as age-related disorders.

    Miller’s team includes experts from diverse fields: Gary Bader, a professor at the Donnelly Centre for Cellular and Biomolecular Research and a computational biologist; bioengineers Alison McGuigan, a professor in the department of chemical engineering and applied chemistry in the Faculty of Applied Science & Engineering, and Penney Gilbert, an associate professor at the Institute of Biomedical Engineering; Sid Goyal, a professor at the department of physics in the Faculty of Arts & Science; Professor David Kaplan and Assistant Professor Yun Li, both in the Temerty Faculty of Medicine and a senior scientist and a scientist, respectively, at SickKids; stem cell biologist Cindi Morshead, a professor and chair of the division of anatomy in the department of surgery in the Temerty Faculty of Medicine; and Peter Zandstra, a University Professor in the Faculty of Applied Science & Engineering and director of Michael Smith Laboratories at the University of British Columbia.

    Miller says Medicine by Design’s contribution in bringing teams like hers together is immeasurable.

    “There are tangible results you can measure like publications and other grants and clinical trials,” Miller says. “But there are a lot of intangible things Medicine by Design brings to the table like developing a culture of people from very diverse places and allowing them to do science together at a time when the biggest breakthroughs are going to be made by combining technological and biological approaches. It’s hard to do that if you’re on your own.”

    This large, interdisciplinary team effort combines data and computer modelling to look at individual stem cells in the brain and predict their behaviours. Through experimentation, they can then test if the cells behave the way they predicted, which Miller says they have had great success with. From there, the team casts a wide net, testing various ways to try to control cells’ behaviour with the end goal of convincing the stem cells to turn into cells that aid in healing and repair.

    One approach they use is testing already approved pharmaceuticals to see if they have the desired effect on the stem cells’ behaviour. This approach has had success. In summer 2020, Morshead, Miller and their collaborators, led by Donald Mabbott, a SickKids senior scientist and professor in the department of psychology in the Faculty of Arts & Science, published a paper in Nature Medicine that showed that metformin, a common diabetes drug, has the potential to reverse brain injury in children who had had cranial radiation as a curative therapy for brain tumours.

    Miller says that, to her knowledge, this is the first paper that demonstrates that this type of brain repair is possible in humans.

    See the full article here .


    five-ways-keep-your-child-safe-school-shootings

    Please help promote STEM in your local schools.

    Stem Education Coalition

    The University of Toronto (CA) is a public research university in Toronto, Ontario, Canada, located on the grounds that surround Queen’s Park. It was founded by royal charter in 1827 as King’s College, the oldest university in the province of Ontario. Originally controlled by the Church of England, the university assumed its present name in 1850 upon becoming a secular institution. As a collegiate university, it comprises eleven colleges each with substantial autonomy on financial and institutional affairs and significant differences in character and history. The university also operates two satellite campuses located in Scarborough and Mississauga.
    University of Toronto has evolved into Canada’s leading institution of learning, discovery and knowledge creation. We are proud to be one of the world’s top research-intensive universities, driven to invent and innovate.
    Our students have the opportunity to learn from and work with preeminent thought leaders through our multidisciplinary network of teaching and research faculty, alumni and partners.
    The ideas, innovations and actions of more than 560,000 graduates continue to have a positive impact on the world.
    Academically, the University of Toronto is noted for movements and curricula in literary criticism and communication theory, known collectively as the Toronto School. The university was the birthplace of insulin and stem cell research, and was the site of the first electron microscope in North America, the identification of the first black hole Cygnus X-1, multi-touch technology, and the development of the theory of NP-completeness. The university was one of several universities involved in early research of deep learning. It receives the most annual scientific research funding of any Canadian university and is one of two members of the Association of American Universities outside the United States, the other being McGill University.
    The Varsity Blues are the athletic teams that represent the university in intercollegiate league matches, with ties to gridiron football, rowing and ice hockey. The earliest recorded instance of gridiron football occurred at University of Toronto’s University College in November 1861. The university’s Hart House is an early example of the North American student centre, simultaneously serving cultural, intellectual, and recreational interests within its large Gothic-revival complex.
    The University of Toronto has educated three Governors General of Canada, four Prime Ministers of Canada, three foreign leaders, and fourteen Justices of the Supreme Court. As of March 2019, ten Nobel laureates, five Turing Award winners, 94 Rhodes Scholars, and one Fields Medalist have been affiliated with the university.

     
  • richardmitnick 8:43 pm on December 19, 2014 Permalink | Reply
    Tags: , Computational Biology,   

    From Quanta: “Machine Intelligence Cracks Genetic Controls” 

    Quanta Magazine
    Quanta Magazine

    December 18, 2014
    Emily Singer

    Every cell in your body reads the same genome, the DNA-encoded instruction set that builds proteins. But your cells couldn’t be more different. Neurons send electrical messages, liver cells break down chemicals, muscle cells move the body. How do cells employ the same basic set of genetic instructions to carry out their own specialized tasks? The answer lies in a complex, multilayered system that controls how proteins are made.

    2

    Most genetic research to date has focused on just 1 percent of the genome — the areas that code for proteins. But new research, published today in Science, provides an initial map for the sections of the genome that orchestrate this protein-building process. “It’s one thing to have the book — the big question is how you read the book,” said Brendan Frey, a computational biologist at the University of Toronto who led the new research.

    Frey compares the genome to a recipe that a baker might use. All recipes include a list of ingredients — flour, eggs and butter, say — along with instructions for what to do with those ingredients. Inside a cell, the ingredients are the parts of the genome that code for proteins; surrounding them are the genome’s instructions for how to combine those ingredients.

    Just as flour, eggs and butter can be transformed into hundreds of different baked goods, genetic components can be assembled into many different configurations. This process is called alternative splicing, and it’s how cells create such variety out of a single genetic code. Frey and his colleagues used a sophisticated form of machine learning to identify mutations in this instruction set and to predict what effects those mutations have.

    1
    Olena Shmahalo/Quanta Magazine

    The researchers have already identified possible risk genes for autism and are working on a system to predict whether mutations in cancer-linked genes are harmful. “I hope this paper will have a big impact on the field of human genetics by providing a tool that geneticists can use to identify variants of interest,” said Chris Burge, a computational biologist at the Massachusetts Institute of Technology who was not involved in the study.

    But the real significance of the research may come from the new tools it provides for exploring vast sections of DNA that have been very difficult to interpret until now. Many human genetics studies have sequenced only the small part of the genome that produces proteins. “This makes an argument that the sequence of the whole genome is important too,” said Tom Cooper, a biologist at Baylor College of Medicine in Houston, Texas.

    Reading the Recipe

    The splicing code is just one part of the noncoding genome, the area that does not produce proteins. But it’s a very important one. Approximately 90 percent of genes undergo alternative splicing, and scientists estimate that variations in the splicing code make up anywhere between 10 and 50 percent of all disease-linked mutations. “When you have mutations in the regulatory code, things can go very wrong,” Frey said.

    “People have historically focused on mutations in the protein-coding regions, to some degree because they have a much better handle on what these mutations do,” said Mark Gerstein, a bioinformatician at Yale University, who was not involved in the study. “As we gain a better understanding of [the DNA sequences] outside of the protein-coding regions, we’ll get a better sense of how important they are in terms of disease.”

    Scientists have made some headway into understanding how the cell chooses a particular protein configuration, but much of the code that governs this process has remained an enigma. Frey’s team was able to decipher some of these regulatory regions in a paper published in 2010, identifying a rough code within the mouse genome that regulates splicing. Over the past four years, the quality of genetics data — particularly human data — has improved dramatically, and machine-learning techniques have become much more sophisticated, enabling Frey and his collaborators to predict how splicing is affected by specific mutations at many sites across the human genome. “Genome-wide data sets are finally able to enable predictions like this,” said Manolis Kellis, a computational biologist at MIT who was not involved in the study.

    Frey’s team used an approach called deep learning. Like any kind of machine-learning technique, the model tries to find a relationship between two sets of data. In this case, Frey’s team connected the human reference genome with rich data sets cataloging the amounts of different protein components in different tissues. (Just as two different cake recipes vary in their ratios of flour and sugar, brain cells and liver cells vary in how much of each protein they produce.) In essence, the algorithms trained a computational model to read instructions embedded in the DNA.

    While scientists already knew how to read some aspects of the splicing code, the new model is unique. It allows scientists to predict how a wide array of genetic components will interact. “This group took what we knew about splicing and put it into a computational framework where we can weight all [the variables],” Burge said.

    For example, researchers can use the model to predict what will happen to a protein when there’s a mistake in part of the regulatory code. Mutations in splicing instructions have already been linked to diseases such as spinal muscular atrophy, a leading cause of infant death, and some forms of colorectal cancer. In the new study, researchers used the trained model to analyze genetic data from people afflicted with some of those diseases. The scientists identified some known mutations linked to these maladies, verifying that the model works. They picked out some new candidate mutations as well, most notably for autism.

    One of the benefits of the model, Frey said, is that it wasn’t trained using disease data, so it should work on any disease or trait of interest. The researchers plan to make the system publicly available, which means that scientists will be able to apply it to many more diseases.

    A Broader Context

    The model also reveals that when it comes to the genome, “context is important, just like in English,” Frey said. “‘Cat’ means different things whether we’re talking about pets or construction equipment.” In the same way, how the cell interprets a set of splicing instructions depends on other nearby instructions. A string of DNA that means “make lots of component X” might mean “don’t make component X” when it’s sitting near a second set of instructions. “Whether a sequence has an effect depends on whether another sequence has an effect,” Frey said. “Without understanding that, it’s hard to predict how a pattern will affect splicing.”

    In addition, the model could help scientists reconsider known mutations, Burge said. Researchers already knew that some splicing instructions are found within protein-coding regions. In these cases, the same genetic sequence might code for both an ingredient and an instruction for what to do with it. (Consider whipped cream — it’s an ingredient, but it’s also in some ways an instruction.) A mutation in this protein-coding region might be dismissed as unimportant if it appears to do little or nothing to alter the corresponding protein. But when interpreted using the splicing code, that mutation might be found to have a profound effect by interfering with the splicing instructions. Frey’s group found many examples of these errors across the genome.

    Frey hopes the model will ultimately prove useful for personalized medicine. For example, doctors cannot yet determine whether healthy people with novel mutations are predisposed to diseases like cancer. With further validation, Frey’s model might help to answer this question. “We can analyze any mutation, even those that haven’t been identified yet,” Frey said. This allows researchers to predict whether a novel mutation is likely to be dangerous or harmless — in essence, performing a screening test. “I want to see it have a huge impact on medicine,” he said. “I want to translate this into practice.”

    See the full article, with video, here

    Please help promote STEM in your local schools.

    STEM Icon

    Stem Education Coalition

    Formerly known as Simons Science News, Quanta Magazine is an editorially independent online publication launched by the Simons Foundation to enhance public understanding of science. Why Quanta? Albert Einstein called photons “quanta of light.” Our goal is to “illuminate science.” At Quanta Magazine, scientific accuracy is every bit as important as telling a good story. All of our articles are meticulously researched, reported, edited, copy-edited and fact-checked.

     
c
Compose new post
j
Next post/Next comment
k
Previous post/Previous comment
r
Reply
e
Edit
o
Show/Hide comments
t
Go to top
l
Go to login
h
Show/Hide help
shift + esc
Cancel
%d bloggers like this: