Picture: 2013 Accomplishment By A Senior Scientist Award Prize Winner, David Eisenberg

ISCB Congratulates 2013 Senior Scientist Award Winner: David Eisenberg

By Christiana N. Fogg, Freelance Science Writer, Kensington, MD

Each year, ISCB honors an esteemed member of the computational biology community with the Accomplishment by a Senior Scientist Award. This award recognizes an individual’s significant contributions to computational biology through research, service, and education. The winner of 2013 ISCB Accomplishment by a Senior Scientist Award is Dr. David Eisenberg, Professor of Chemistry and Biochemistry and Biological Chemistry at the University of California, Los Angeles.

David Eisenberg’s love of medicine and science was cultivated first during his childhood by his father, a gentle and beloved pediatrician. Eisenberg recalled, “Every night after dinner he would make house calls. I saw how appreciated—even loved— he was in our village.”

Eisenberg’s father also stoked his scientific curiosity by encouraging him to try some experiments in their basement, including attempts to petrify an egg and to grow worms in chocolate. Eisenberg reminisced, “None of these [experiments] worked, but they were fun.

Eisenberg strongly considered following in his father’s footsteps and pursuing a career in medicine. With that goal in mind, he focused his undergraduate studies on biochemical sciences at Harvard University. As a sophomore, he was assigned to Dr. John T. Edsall as a tutor.

Edsall was a pioneering researcher in the field of biophysical chemistry, and under his guidance, Eisenberg had his first encounter with laboratory research. “In my junior year, he assigned me to read scientific papers, most of which baffled me, and at the end of that year, I started a research project in his lab, which became the subject of my senior thesis.” Eisenberg recounted. “After graduation, Dr. Edsall turned my thesis into a short paper which was published in Science.”

In spite of Eisenberg’s eye-opening undergraduate research experiences, he applied and was accepted to medical school. Edsall was also trained as a medical doctor, but Eisenberg remembered how “Dr. Edsall convinced me that if my goal was to improve the health of mankind, I might have a greater impact working in biochemistry, than as a practicing physician.”

Eisenberg took Edsall’s advice to heart and “finessed making an immediate choice by going to Oxford to study theoretical chemistry under Dr. Charles Coulson, one of the founders of quantum chemistry.” Edsall’s guidance had also given him a strong foundation in math and physics, which served him well as a graduate student at Oxford as he recalled being “(just) able to work with Coulson on the energetics of hydrogen bonding.”

Eisenberg’s postdoctoral studies took him to Princeton in 1964 to work with Dr. Walter Kauzmann, well known for his discovery of the hydrophobic interaction. Eisenberg recollected his ambitious postdoctoral plan “to compute the energy of the hydrophobic interaction in myoglobin, the first protein with a known 3D structure. This plan now seems hopelessly naïve: computers were not yet up to such a calculation, potential functions and theory had not advanced to the point that this was a practical problem, and the early protein crystallographers were not eager to release their atomic coordinates.”

In light of these challenges, Eisenberg’s work with Kauzmann culminated in “a monograph on ice and water, which, incidentally, is still in print 44 years later.”

His failed postdoctoral research plan also opened his eyes. He knew if he wanted to pursue protein energetics, which required knowing protein coordinates, he had to learn X-ray crystallography. Eisenberg’s next postdoc took him “to Caltech to study X-ray crystallography with Richard Dickerson, who had been part of the team who had determined the structure of myoglobin.”

His X-ray crystallography training was pivotal to establishing his own lab at UCLA that focused on studying diverse protein structures. Melittin, a component of bee venom, was one of the first structures he determined with his then graduate student Tom Terwilliger. Eisenberg vividly recalled that, “At last I was able to get down to energetic calculations on a protein, and came up with the idea of the hydrophobic moment. This and related ideas gave me for the first time the feeling that I could make discoveries.”

Eisenberg also remembers the excitement of solving the structure of diphtheria toxin dimer, which he worked on with John Collier, Senyon Choe, and Melanie Bennett (Brewer). He recalled the excitement that stemmed from Bennett (Brewer)’s observation that “two monomers of the dimer swapped their third domains, and we called this phenomenon “3D domain swapping.” We explored the implications of 3D domain swapping, again calling on my background in energetics. Diphtheria toxin was the first structural example of 3D domain swapping; now there are hundreds.”

Eisenberg’s work on protein structures awakened his interest in how protein sequences relates to 3D structures. While on sabbatical at the Laboratory of Molecular Biology in Cambridge, he worked with Andrew McLachlan and Mike Gribskov to develop methods to examine protein sequences and use profile analysis to predict the presence of potential structural motifs. These studies led to his work on 3D profiles with Jim Bowie and Roland Luethy, which Eisenberg has now seen “applied to many protein problems.”

Burkhard Rost, president of the ISCB, considers Eisenberg’s work on hydrophobicity profiling as groundbreaking as it “describes an important feature of the constituents which] we found we could extract information on protein interactions from sequenced genomes.” These cutting edge studies resulted in several publications that showed how protein function and protein-protein interactions could be predicted from genome sequences.

Eisenberg has focused his research over the last decade on studying amyloid-forming proteins. Several neurodegenerative diseases are associated with amyloid-forming proteins, including Alzheimer’s, Parkinson’s and amyotrophic lateral sclerosis (Lou Gehrig’s) disease. “Just before the turn of the century, I realized that amyloid diseases represent the greatest unmet medical problem facing the world.” Eisenberg recounted. “And at the same time, I realized that structural and computational biology, which have illuminated other areas of biomedicine so well, have not been widely applied to the fundamental problems of amyloid disease. In particular, there had been almost no single crystal x-ray studies of amyloid-forming proteins.”

Eisenberg also acknowledges that, “Having several friends afflicted with amyloid disorders is a great inspiration. I would love to be able to help them, and others. If we can, it would validate Dr. Edsall advice that sometimes biochemists can do as much or more to help mankind than physicians.”

Eisenberg’s group has studied the structural basis of how normal proteins convert to amyloid fibrils. They have gained great insight into this conversion process by determining the atomic structures of the spines of many different types of amyloid fibrils. The use of computational biology with this structural data has helped support the definition of the “amyloid state” of proteins. “Bioinformatics and computational biology are great partners with structural biology. Using the tools together can be surprisingly powerful,” said Eisenberg.

Eisenberg remains humble about his accomplishments. When asked about being the recipient of the ISCB Senior Scientist Accomplishment Award, he felt “honored, but perhaps over-honored. There are many others who are equally or more deserving of this recognition.” But he also recognizes that this award helps highlight the importance of studying amyloid diseases, especially using the tools of computational biology. Eisenberg speaks warmly of the mentors that have guided and shaped his scientific training. “I was enormously fortunate to find myself in the research groups of four great mentors: John Edsall, Charles Coulson, Walter Kauzmann, and Richard Dickerson, not to mention my father. All were creative scientists, and also humanists. Watching them I saw their pleasure in scientific discovery, and also saw their insistence on fairness to all those involved in the process of science.”

Their examples have not only served him well as a scientist, but also as a mentor. Eisenberg delights in working with trainees because he loves “their eagerness to learn and to succeed, and their willingness to think freshly about hard problems.”

Eisenberg’s scientific curiosity remains insatiable, and when asked for advice to motivate young scientists, his sage answer was “work on fundamental problems, maintain your curiosity, and above all, persevere.”

This article is excerpted from the June 28, 2013, issue of PLOS Computational Biology. To link to the full journal article please visit: www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1003116

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Congratulations to 2013 ISCB Overton Prize Winner: Goncalo Abecasis

By Christiana N. Fogg, Freelance Science Writer, Kensington, MD

ISCB recognizes the achievements of an early or mid-career scientist annually with the Overton Prize. The Overton Prize honors the memory of G. Christian Overton, a prominent bioinformatics researcher and founding ISCB Board member who died suddenly in 2000. Winners of the Overton Prize are up-and-coming independent scientists honored for their significant contributions to computational biology through research, teaching, and service. ISCB is thrilled to recognize Dr. Goncalo Abecasis, Felix E. Moore Collegiate Professor of Biostatistics at the University of Michigan, as the 2013 winner of the Overton Prize.

Goncalo Abecasis was drawn to biology ever since he was a child. “From a young age, I have always been fascinated with understanding how life works,” said Abecasis. He fondly recalls spending Sundays at a bookstore with his parents and gradually collecting a small library of wildlife books.

But it was his experiences in a high school computer programming club that opened his eyes to an entirely different field. “Although I didn't know it at the time, a key skill that later contributed to my success in genetics was my interest in computer programming,” recalled Abecasis. “The club was meant to keep us busy and out of trouble, but they did encourage us to try programming and point us in the direction of very useful techniques, like object oriented programming and the like.”

Human genetics appealed to Abecasis as he pursued his undergraduate studies at the University of Leeds, and he landed a position in the lab of Dr. Mary Anne Shaw studying “how genetic variation in the interleukin-1 gene cluster, a set of immune genes where variation was easy to measure with then available techniques, was related to infection by Leishmania and other tropical parasites.” This experience proved invaluable for helping Abecasis to receive funding for his Ph.D. training in the lab of Dr. William Cookson at the University of Oxford.

Cookson’s lab was studying genes that contribute to asthma susceptibility at the Wellcome Trust Center for Human Genetics at Oxford. In the late 1990’s and early 2000’s, Abecasis described this Center as “a mecca for human geneticists at the time, with great support from the Wellcome Trust, and lots of smart people trying new ways to run genetic studies and looking to make rapid progress in many different traits.” Abecasis also recalled that, “as we pushed the limits of the sequencing and genotyping technologies of the time, we were soon generating datasets that were beyond the reach of existing analysis tools and methods.”

Abecasis saw that, “It was easy to realize that new analysis methods and computer software were needed -- and being in Oxford, working at the Wellcome Trust Center was just the right place to be.” With Cookson’s support, and under the comentorship of statistical geneticis Dr. Lon Cardon, Abecasis developed software to tackle the analysis of large genetic datasets. Abecasis remembered dealing with many software bugs along the way, but then, as now, he repeated the mantra to himself that “all software is buggy, and this is no exception!”

Abecasis was pursuing his Ph.D. at the same time as the race to sequence the first human genome was wrapping up. As the field of genomics was emerging, he realized that several of the methods he had developed could be used to look at how “individual genomes differed from this initial sequence and to understand how these differences contribute to the great diversity we see among people today.” The application of these methods to genome data also shifted his research focus away from “laboratory methods, technology and data generation,” and toward “issues related to study design and analysis.”

Abecasis’s unique knowledge and training in human genetics, biostatistics, and computational analysis landed him a faculty position in the Biostatistics Department at the University of Michigan. Abecasis recounted the support and mentorship of Dr. Michael Boehnke in the department. “Mike somehow convinced the Biostatistics Department at the University of Michigan to take a flutter on me, when I had just finished my Ph.D. and had much less formal training in statistics than most of my colleagues. He has always been generous with his time, and I probably can't count the times that I have interrupted him in his office, bounced some ideas off him, and came out energized and thinking about something new to try.”

Along with Boehnke, Abecasis acknowledged how fortunate he has been in the mentorship he received throughout his training, including the volunteers who taught him to code in his high school club. “As I knew them, I remember my mentors as demanding, generous with their time, unrelentingly positive and encouraging, and totally transparent. It is obviously a standard I'd like to meet, although I doubt I am there yet.”

Their example also motivates Abecasis to be a good mentor. “It is great to set a student free on an interesting open problem and have them solve it. You can do so much more with a few good trainees than you could ever accomplish on your own.”

Abecasis’s research, and the field of human population genetics in general, have been transformed by the advent of high-throughput genetics. “We now have very clear answers about the degree and structure of genetic variation in the world today, but have also gained a lot of detail on human population history -- including very ancient events, like admixture with Neanderthals,” said Abecasis.

Abecasis’s lab is now focused primarily on identifying genetic variants relevant to human disease. They look at linkage disequilibrium within human genomes in order to describe, “how groups of variants are shared among individuals.”

One of the observations that Abecasis’s group and others made several years ago that he recalled as being surprising was “that much of the genetic variation in any individual could be recovered very accurately by comparing each individual to a reference set of individuals and, more recently, we have used the process to make it relatively inexpensive to sequence large numbers of individuals. At our last count, >30,000 human genomes had been sequenced using our "low-coverage" linkage disequilibrium based approach.”

One of the highlights of Abecasis’s career was being invited to the White House in 2010. “I was thrilled. I remember I had very short notice (perhaps a couple of days) and had to rush and find something to wear, recalled Abecasis. Although it is cheesy, it is really amazing to live in a country that functions so much like a meritocracy. I didn't have to write a check, join a committee, vote - anything. I had a good idea about how to sequence a lot of genomes more rapidly, proposed it, and not only did I get funded to try it out (it worked, by the way), but my work was selected as one of the highlights for Vice President Biden’s speech on the important of technology development and biomedical research.”

Abecasis described the importance of collaborations to his research and is a strong proponent of sharing data and software tools. “So many great discoveries and advances come from bringing in insights, ideas and approaches from a different field,” said Abecasis.

But Abecasis also agreed that data sharing is not without challenges. “There are legitimate concerns about protecting the identity and privacy of research subjects and, once in a while, people do use data you share pre-publication to gain an advantage,” said Abecasis. “Still, there is no doubt we are moving in the right direction -- expectations for data sharing and collaboration are so much more open than when I started.”

Abecasis has felt fortunate to work with so many great collaborators. One of his most interesting collaborations has been his work with Drs. David Schlessinger, Francesco Cucca, and Serena Sanna and many others on the “SardiNIA project.” “When I first met David, and he described the idea of conducting a thorough genetic study in an isolated valley in Sardinia, I never thought it would happen,” remembered Abecasis. “It seemed so ambitious. But David and our Sardinian colleagues have boundless energy and real dedication, and the study probably accounts for most of my highly cited papers!”

“The work of Goncalo underscores the importance of the theoretical developments and their implementation in computational method for the progress in current biomedical research, bringing genomic information closer to the study of the complex genetic basis of common diseases,” said Alfonso Valencia, chair of the ISCB’s Awards committee.

Abecasis feels truly honored and humbled to be the 2013 recipient of the Overton Prize. Abecasis also hopes that, “If this award encourages members of the ISCB to bring some of their considerable expertise to bear on the big open problems in genetics, that would be an amazing outcome.”

This article is excerpted from the June 28, 2013, issue of Bioinformatics. A transcript of the full interview with Dr. Abecasis can be found at http://genome.sph.umich.edu/wiki/Goncalo_Abecasis:_Interview_with_Christiana_Fogg

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Congratulations to 2012 ISCB Overton Prize Winner

Ziv Bar-Joseph loves to run. He rises early and hits the streets and trails around Pittsburgh where he lives, often in training for a long-distance race. This dedication has paid off. He has the enviable distinction of having run a sub-three hour marathon, a feat achieved by few amateurs. "Running is very important to me," he says.

But it is not just in his running that Bar-Joseph shows a willingness to go the distance. As a computer scientist and computational biologist at Carnegie Mellon University in Pittsburgh, Bar-Joseph shows a similar dedication as head of the Systems Biology Group at the School of Computer Science. "We have all been impressed by the novelty of the approaches he has developed," says Alfonso Valencia, chair of the ISCB Awards Committee.

Bar-Joseph gained a PhD in computer science from the Massachusetts Institute of Technology between 1999 and 2003. That time turned out to be hugely significant, not least because computational biology was undergoing a revolution. "For the first time, we were getting sequences for large species. First, the fly, then humans. It was very inspiring," he says.

Initially, Bar-Joseph knew little about computational biology but took a class to better understand the significance of these advances and the problems they posed. "It seemed to me that these types of problems were well-suited for the machine learning tools I had experience with," he says.

One of the key problems was how to compare sequences either within species or between them. Various researchers had developed methods to do this using a branch of computer science called combinatorics, which essentially counts the number of similar patterns.

But while this works well when comparing two sequences, it's not so good for comparing seven or eight sequences. It doesn't scale. Consequently, researchers began to experiment with probabilistic approaches that focus on the statistical properties of the patterns. In particular, computational biologists had significant successes with a statistical approach called a hidden Markov model. That attracted Bar-Joseph who had studied this model.

He also recognised that other earlier studies, attempting to reconstruct networks in cells, were significantly limited: the data was a snapshot of a complex dynamic system but they treated it as if it were static.

Clearly, biological systems change. "One thing I've been involved in is introducing dynamics into the algorithms so that they can cope with the way things change in time. That requires different tools," he says.

The approach has paid off when it comes to understanding regulatory networks and explaining how proteins control each other. For example, yeast has about 6,000 proteins. Of these, some 250 are control proteins and each of these, on average, controls 100 or so other proteins. However, each control protein is itself controlled by a handful of other proteins.

Understanding a system like this is a tricky business. The static data can tell you what proteins control other proteins, but that doesn't tell you when and under what conditions because that requires more experiments.

Other types of data are more temporal and can reveal how protein levels change over time. "The question we asked was whether we can use this temporal data to try and recover the underlying network dynamics," he says. "We came up with methods to integrate these datasets in order to reconstruct the set of events over time and these have since been used in various other systems too."

Bar-Joseph has learnt to work closely with biologists who test the results. "If the algorithm predicts that 'a' controls 'b', for example, you can do the experiment to test whether that's true." That's important because the patterns that the algorithms reveal must be biologically relevant.

To better understand the challenges that experimentalists face, Bar-Joseph spent a sabbatical working in a wet lab doing exactly this kind of work. That taught him some valuable lessons. For example, wet lab work is not just a question of validating the model. "The results from the lab feed back into the model and enhance it. It's a two-way street," he says. Others have been impressed with Bar-Joseph's approach to experimental work. "Ziv is an example of somebody coming from the theoretical side of things and completely embracing the experimental approach," says Burkhard Rost, president of the ISCB. "It's stunning how he is able to handle such a diverse set of technical methods."

This process of feedback from biology to computer science has become an important theme in Bar-Joseph's work. One of his recent successes is in explaining the way fruit flies develop bristles on their foreheads. These bristles are like aircraft sensors, measuring temperature, wind speed, and so on. To work well, they need to be spaced in a very precise way.

The bristles grow from cells but clearly only a small subset of cells. The cells do not know how many neighbours they have or the local density of bristles nearby. So what determines which cells grow into bristles and the spacing between them?

Bar-Joseph quickly realised that this was similar to a problem that computer scientists have wrestled with for 30 years. This is the problem of determining the subset of computers in a network that control all the others. When each computer in the network is connected to one computer in this subset (but no two in the subset are connected to each other), this subset is called maximally independent.

Finding maximally independent sets is hard, particularly in large distributed networks. Computer scientists do it by assuming that every computer knows who all its neighbours are.

Bar-Joseph realised that the fruit fly cells that eventually become bristles form a maximally independent set---they are connected to all other cells but not to each other. However, they do not know who their neighbours are and so must solve this problem in a different way. His breakthrough was to work out how they did it and develop an algorithm that does the same thing while assuming no knowledge of the neighbours. "It takes a bit longer but that's the trade-off," he says.

This may have important applications for wireless sensor networks that researchers are using to monitor everything from ocean conditions to volcanic eruptions. "We only published at the beginning of 2011 so we don't know if it will penetrate the commercial world," he says.

Valencia is also impressed by Bar-Joseph's broader contribution to the computational biology community. "He is a member of the editorial board for the journal Bionformatics, so clearly his contributions go beyond this theoretical and experimental work," says Valencia. "That's very good for a young scientist."

The future holds many promising problems for Bar-Joseph too. He is particularly interested in studying how pathogens interact with cells, how the proteins from flu viruses interact with cell proteins, for example. "If we can reconstruct the networks of interactions then we might be able to determine intervention points that will guide us to therapeutics," he says.

He also wants to study the interaction networks in different species. Many of the genes in humans and mouse are similar, but drugs that work well in mouse often don't work in humans because the pathways, levels, and interactions are different.   "We want to get more insight into this," he says.

That's clearly a long game. These are problems that will require dedication, talent, and endurance to solve. Exactly the kind of qualities you might find in a marathon runner.
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This article is excerpted from the May 2012 issue of PLoS Computational Biology. To link to the full journal article please visit www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002535.

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Picture: 2003 ISCB ASSA Winner, David Sankoff

2003 ISCB Accomplishment by a Senior Scientist Award Winner -
David Sankoff

The ISCB will present the first-ever ISCB Senior Scientist Accomplishment Award to David Sankoff, Canada Research Chair in Mathematical Genomics at the University of Ottawa and a member of the Centre de Recherches Mathématiques at the Université de Montréal. The prize will be awarded to Sankoff at ISMB2003, where he will present a keynote lecture on July 2, 2003.

In sequence comparison, he introduced the quadratic version of the Needleman-Wunsch algorithm, developed the first statistical test for alignments, initiated the study of the limit behavior of random sequences with Vaclav Chvatal and described the multiple alignment problem, based on minimum evolution over a phylogenetic tree. In the study of RNA secondary structure, he developed algorithms based on general energy functions for multiple loops and for simultaneous folding and alignment, and performed the earliest studies of parametric folding and automated phylogenetic filtering.

Sankoff and Robert Cedergren collaborated on the first studies of the evolution of the genetic code based on tRNA sequences. His contributions to phylogenetics include early models for horizontal transfer, a general approach for optimizing the nodes of a given tree, a method for rapid bootstrap calculations, a generalization of the nearest neighbor interchange heuristic, various constraint, consensus and supertree problems, the computational complexity of several phylogeny problems with William Day, and a general technique for phylogenetic invariants with Vincent Ferretti. Over the last fifteen years he has focused on the evolution of genomes as the result of chromosomal rearrangement processes. Here he introduced the computational analysis of genomic edit distances, including parametric versions, the distribution of gene numbers in conserved segments in a random model with Joseph Nadeau, phylogeny based on gene order with Mathieu Blanchette and David Bryant, generalizations to include multi-gene families, including algorithms for analyzing genome duplication and hybridization with Nadia El-Mabrouk, and the statistical analysis of gene clusters with Dannie Durand. Sankoff is also well known in linguistics for his methods of studying grammatical variation and change in speech communities, the quantification of discourse analysis and production models of bilingual speech.

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Picture: 2011 ISCB ASSA Winner, Michael Ashburner Photo courtesy of European Molecular Biology Laborator

2011 ISCB Accomplishment by a Senior Scientist Award Winner:  Michael Ashburner

If computational biology seems challenging in the second decade of the 21st century, spare a thought for those who pioneered the discipline in the 1980s. Michael Ashburner at the University of Cambridge was one of them. “His work is now seen as a landmark and an achievement in technology,” says Alfonso Valencia, chair of the ISCB awards committee.

Ashburner began his career with a degree in genetics from the University of Cambridge in 1964. He stayed on to do a PhD, studying Drosophila and, in particular, polytene chromosomes, which form when certain specialised cells undergo repeated rounds of DNA replication. Polytene chromosomes have a characteristic banded structure. In Drosophila there are some 5,000 bands and a subset of these undergo, during development, a reversible structural modification as the result of transcription; this is known as puffing and can be considered an analog of gene activity. In the late 1960s and early 1970s, Ashburner studied puffing patterns and inferred the existence of a cascade of genetic controls under the influence of the hormone ecdysone during larval development.

In the late 1970s, Ashburner turned his attention to the study of the Alcohol dehydrogenase gene and its environs. By the mid-1980s, he had the most detailed analysis in full genetic terms of any small chromosome region of any multi-cellular organism, and had the Adh gene sequences from several different species of Drosophila. “That drew me into bioinformatics because we needed a way of comparing sequences,” he says. “There was almost no software available to help.”

Two people came to his aid. The first was Walter Bodmer, director of the Imperial Cancer Research Fund, who gave Ashburner the use of a DEC computer with access to the early network. “We could access this machine by dial-up and do some analysis,” he says. The second was Doug Brutlag at Stanford University, who was developing MOLGEN, an early bioinformatics system, which he allowed Ashburner to access.

That presented a significant obstacle, however. Getting a computer in the United Kingdom to speak to one in Stanford was not straightforward. Today, everybody uses the Internet, defined by the TCP/IP protocol. But in the early ‘80 s, the UK and United States used different systems. The US was pioneering TCP/IP while the UK had a standard called the Coloured Book protocols. “The only place that had an interface between the two protocols was University College, London, and they were very helpful,” says Ashburner, “giving us 5 kb of disk space.”

The process of connecting to Stanford was far from simple. “The way you did it was to dial up your local packet switching exchange at the Post Office and connect to the Rutherford Appleton Laboratory. You then typed in some code which connected you to UCL where you could use TCP/IP,” he says. The signal was routed via Goonhilly satellite station in Cornwall to Carnegie Mellon University and from there to Stanford. “I had a dumb terminal, that is a box with no memory, so everything had to be captured by a printer in parallel.” Ashburner was far from deterred, however.

At about that time, the European Molecular Biology Laboratory (EMBL) in Heidelberg and GenBank in the US released the first nucleotide sequence libraries in quick succession. Using his network access, Ashburner and his colleagues, collaboratively with MOLGEN, set up one of the first bulletin boards, called BioNet, to keep people informed of changes to the library and to software. “This became well used and things evolved from there,” he says.

As the field of bioinformatics grew, the need for an institution to house the data and conduct research increased. So in 1992, the EMBL decided to set up an institute of bioinformatics that would house this library and carry out research. This organisation became known as the European Bioinformatics Institute, based in Hinxton, UK, with Ashburner and John Sulston having led the UK bid to host it. “I was persuaded to become the first program coordinator and took half-time leave from Cambridge to do that,” he says. He eventually took over as joint-director, a post he held until 2001. “At first, the finances were sticky and the politics were horrendous. But it has since gone from strength to strength,” he says.

At the same time, Ashburner continued his interest in Drosophila genetics. This is a field with a rich and long history of collecting and sharing mutations. The first catalogue of mutations was published in 1925 and it was still being revised in paper form in the late 1980s. But the field was beginning to expand quickly and the books were out of date as soon as they were published. “It became clear to me that we couldn't carry on publishing in paper form every 10 or 20 years,” he recalls.

So in 1989 he proposed that the community set up an electronic database to take over the role of the printed one. In 1992, the NIH funded the project that became known as FlyBase, one of the first genetic and now genomic databases.

FlyBase was a crucial factor in triggering Ashburner's interest in a structured, controlled vocabulary, a formal representation of knowledge about genes and gene products. He began to define terms for gene products by their biological processes, such as wing development, and then defined the data structure in which these terms were related to each other. “It occurred to me that if you were able to do this for several model species, you'd have a fantastic tool,” he says.

But this insight initially met with little interest. “My first presentation, at ISMB in Greece in 1997, went down like a lead balloon,” he recalls. Eventually, he and three like-minded colleagues settled the matter in a bar at the Montreal ISMB in 1998.

Together, they decided to set up a cross-species ontology to be used by the Drosophila, yeast, and mouse databases. They called it the Gene Ontology, and it is now a major bioinformatics project that covers over 1,800 species. Their original paper on the idea in Nature Genetics is one of the most highly cited in the field. “His achievement is not just to have built this system but also to have organised the consortium behind it. It is now one of the most used resources in all of biology,” says Valencia.

He went on to collaborate with Gerry Rubin and Craig Venter in sequencing the Drosophila genome in 1999. “The process turned me into a nervous wreck,” he jokes. He published his account of this roller-coaster experience in a short but entertaining book called Won for All: How the Drosophila Genome was Sequenced (Cold Spring Harbor Laboratory Press, 2006).

“We're lucky to have such an inspirational figure in the community,” says Valencia. “This award has been well deserved for a number of years.”

This article is excerpted from the June 2011 issue of PLoS Computational Biology. To link to the full journal article please visit www.ploscompbiol.org/article/info%3Adoi/10.1371/journal.pcbi.1002081

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2010 ISCB Accomplishment by a Senior Scientist Award Winner – Chris Sander

Picture: 2010 ISCB ASSA Winner, Chris Sander

The ISCB’s Accomplishment by a Senior Scientist Award is presented annually to a scientist who has made distinguished contributions over many years of research, teaching and service. This year’s award goes to Chris Sander of Memorial Sloan Kettering Cancer Center, New York, USA. He will be presented with his award and deliver a keynote lecture at ISMB 2010 in Boston, on July 12th.

Sander is one of the best-known researchers in protein structure analysis and genomics pathway analysis. Like other founders of bioinformatics, Sander was initially trained as a physicist, with a first degree in physics and mathematics from the University of Berlin in 1967, and a PhD in theoretical physics after graduate studies at the State University of New York, the Niels Bohr Institute in Copenhagen and the University of California in Berkeley. His interest in biology was first kindled by Joe Franklin, a research chemist, during a high school exchange year in Texas. At the age of 21, he went straight to the top to explore this interest, took a trip to Caltech and knocked on the door of Max Delbrück, a physicist turned pioneering bacterial geneticist. Delbrück elaborated on the potential of theoretical physics in molecular biology, but it was not until after completing his first postdoc in theoretical high-energy nuclear physics in Heidelberg that Sander made the lateral transition to biology.

Sander chose to work on protein folding because, as he said with a smile, "I liked stereo views of molecules". He became a post-doc with Shneior Lifson, then a leader in the field of molecular force fields for biopolymers at the Weizmann Institute in Israel. "Lifson taught me that the most important skill in science is to ask good questions," Sander says with admiration.

Having successfully switched from theoretical physics to biology, he then moved to the Max-Planck Institute for Biophysics in Heidelberg to work with Georg Schulz, a protein crystallographer, and biophysicist Ken Holmes. His first independent collaboration with post-doc colleague Wolfgang Kabsch led to the development of the algorithm for analyzing protein structures, DSSP, that 17 years later is still used as a standard for identifying protein secondary structures in experimental 3D structures.

In 1986, Sander took a giant leap from senior post-doc to department chair and founder of the Biocomputing Program at the European Molecular Biology laboratories (EMBL) in Heidelberg, with the support of Sydney Brenner, one of the grand masters of molecular biology. "EMBL is an ideal environment for young, independent scientists to flourish", he says. "It is highly stimulating, collaborative and international." During that period he also pursued his dream of building international collaborations and a worldwide bioinformatics infrastructure as active co-founder of the European Molecular Biology Network (EMBnet). When, in 1995, EMBL moved its bioinformatics research and services from Heidelberg to the European Bioinformatics Institute (EMBL-EBI) in Cambridge, UK, he joined the new institute as a group leader. Soon thereafter he was a founding member of the Board of Directors of ISCB when the society was established in early 1997.

By the late 1990s Sander was motivated by "having more impact in the real world than can be afforded by publications and conferences. While a guest at the MIT Genome Center in Cambridge, Massachusetts in 1998, he co-founded the bioinformatics company Millennium Information, a short-lived spinout from Millennium Pharmaceuticals. Recruited by Harold Varmus, in 2002 Sander accepted the challenge to found his second department of computational biology, now at Memorial Sloan-Kettering Cancer Center in New York, with strong emphasis on translational, i.e., clinically relevant, techniques and applications, particularly in cancer medicine.

Sander predicts about his own work: "the best is yet to come". He is continuing to innovate, and expects to present new results in his keynote lecture at ISMB 2010, describing a novel approach to cell biology that builds network models based on systematic perturbation of the cellular system and rich observation of the resulting changes in molecules and cellular phenotypes. "We rapidly cycle between experiment and theory and I now have a wet lab in my group for the first time in my career", he says.

Sander reflects, "The two key ingredients for successful science are asking good questions and working with good people in a friendly atmosphere. The results of my past and present work are in essence the product of my collaborations with scientists across varied disciplines and from many countries, and I am their fan."

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2009 ISCB Accomplishment by a Senior Scientist Award Winner - Webb Miller

Picture: 2009 ISCB ASSA Winner, Webb Miller

Ten years ago, Webb Miller was already well known to bioinformaticians worldwide for two very highly cited classic papers on the BLAST algorithms for searching sequence databases. Today Miller's name is equally well known for the alignment, comparison, and analysis of complete vertebrate genomes. Much of the code written in his group is embedded in the University of California Santa Cruz (UCSC) Genome Browser.

Miller's initial training was in mathematics. In the mid-1960s, at Whitman College in Walla Walla, Washington, he found a book in the library on the theoretical limits of what is computable, and he decided that he could undertake real, publishable research in this field. This led to graduate work in Computer Science, to his Ph.D. in Mathematics, and, by 1969, to an assistant professorship in Computer Science at The Pennsylvania State University (Penn State). At this time he still had no experience of practical computing or writing code.

In 1980, Miller was looking around for new challenges and applications of his computational knowledge. He found them through a most unexpected source. "My mother started sending me newspaper clippings about the beginnings of the Human Genome Project," he says. "This fascinated me, although I knew no biology at the time."

Soon after entering bioinformatics, Miller turned his attention from general sequence alignment algorithms to the specific problem of aligning long DNA sequences. "Most bioinformaticians spent the 1990s waiting for the human genome sequence," he said. "My question was: How soon would the second vertebrate genome come out, so I could try a genome-wide sequence alignment?" That second genome—of the mouse—was published in 2002. "I originally anticipated that we would have two vertebrate genomes by the time I reached retirement age in 2008. Instead, thanks to improvements in sequencing technology, we now have over forty."

He and his collaborators have now taken on a new challenge: sequencing the genomes and understanding the biology of rare, endangered, and even extinct species. He has published sequences of the nuclear genome of the woolly mammoth and the mitochondrial genome of the Tasmanian tiger (Thylacinus cynocephalus), which became extinct in 1936. Miller says he is hoping that similar sequencing techniques will help preserve endangered species from extinction. One of these is the so-called Tasmanian devil, a ferocious marsupial that is now under threat from a mysterious, contagious tumor: Devil Facial Tumor Disease. "We are sequencing two specimens, one with the disease and another that seems immune, and hope to use the differences to guide a breeding program," he says.

Miller acknowledges that he owes much of his success to "great" collaborators, from Gene Myers (Howard Hughes Medical Institute, USA) and David Lipman (National Cancer Biotechnology Information, USA) in the late 1980s to David Haussler (UCSC, USA) and Haussler’s colleagues Jim Kent and Tom Pringle. And it may be that great collaborators make each other. "Time and time again, Webb has made major contributions and taken little credit for himself, preferring to put younger researchers in the limelight, whether or not they were his students. I've never worked with a more generous collaborator," says Haussler.

In respect for his ISCB 2009 Accomplishment by a Senior Scientist Award, Miller offers his "10 Steps to Success in Bioinformatics" (click here).

This article is excerpted from the April 2009 issue of PLoS Computational Biology. To link to the full journal article please visit www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000375.

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2008 ISCB Accomplishment by a Senior Scientist Award Winner - David Haussler

Picture: 2008 ISCB ASSA Winner, David Haussler

"[David] Haussler’s group was one of the pioneers of machine learning in bioinformatics, introducing Hidden Markov Models for the statistical analysis of patterns in biological data," says Brunak. However, Haussler’s recent achievements have been more in the application of bioinformatics methods than in their development. Since 1999, he has been one of the principal figures in sequencing, and later analysing, the human genome and those of other mammals, and in mining this genomic information for insight into vertebrate evolutionary history.

Haussler originally trained as a mathematician. His first encounter with computational biology came in graduate school, at the University of Boulder in Colorado, where he had the good fortune to study for his Ph.D. under Andrzej Ehrenfeucht. "He taught me that I should never be constrained by disciplinary boundaries, and never be frightened to tackle big problems. The word ‘bioinformatics’ didn’t exist when I was a graduate student, but we were doing it."

Haussler’s first years as an independent investigator were devoted to studies in pattern recognition and machine learning, focusing on modelling the way the brain learns. He shifted from computational neuroscience back to bioinformatics when Anders Krogh joined him at Santa Cruz as a post-doc. "He [Anders] came to my lab to work on machine learning, but soon discovered that these methods could be applied to biological sequence analysis, to classifying proteins into families and recognising genes in fragments of DNA."

Late in 1999, Haussler was called by Eric Lander, one of the leaders of the public human genome sequencing project, and asked to apply his HMM methodology to identifying the genes in the then newly sequenced human DNA," he explains. At that time, the public project was in a "full-on race" with Celera to publish an initial working draft of the sequence.

Barely six months after Haussler joined the project, both teams were ready to release their first genome drafts. Haussler well recalls July 7, 2000, when the complete draft genome sequence was posted on the University of Santa Cruz’ Web server. "Seeing the waterfall of As, Gs, Cs, and Ts pouring off our server was an emotional moment," he says. "We were witnessing the product of more than three billion years of evolution, sequences passed down from the beginning of life to present-day humans." This excitement was shared by the worldwide scientific community; Internet traffic on the Santa Cruz server reached 0.5 terabytes per day then: a record that still stands.

Haussler has dedicated the first years of the new millennium to mapping and analysing that sequence. Other questions that have attracted Haussler’s attention include the analysis of hyper-conserved DNA sequences that remain virtually unchanged in divergent species, and the genetic changes that distinguish humans from apes. While most researchers in this field have concentrated on gene gain during evolution, Haussler and his team recently identified twenty-six genes that are well-established in the vertebrate lineage but that were lost in the latter stages of human evolution.

This article is excerpted from the July 2008 issue of PLoS Computational Biology. To link to the full journal article please visit www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000101.

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2007 ISCB Accomplishment by a Senior Scientist Award Winner - Temple Smith

Picture: 2007 ISCB ASSA Winner, Temple F. Smith

The International Society for Computational Biology is pleased to honor Temple F. Smith of Boston University with the 2007 ISCB Accomplishment by a Senior Scientist Award. The award recognizes senior members of the computational biology community who have made major contributions to the field through research, education, service, or a combination of the three.

"Professor Smith’s contributions go well beyond those for which he is best known," says Thomas Lengauer, chair of the ISCB Awards Committee. Lengauer continued, "He is a towering figure in bioinformatics, one of the founders of the discipline. In addition to starting GenBank and being the Smith of the Smith-Waterman algorithm, he has done seminal work on the entropy of the genetic code and on pattern-directed protein structure prediction." Other influential work includes research on gene prediction, molecular phylogenies, multiple sequence alignments and the analysis of sequence patterns." His results have had a tremendous impact on the field. And his BioMolecular Engineering Research Center at the Boston University College of Engineering is a superlative resource for a wide variety of endeavors."

Smith obtained his doctorate in nuclear physics from the University of Colorado in 1969 and was at NIH as a postdoctoral fellow with Stanislaw Ulam, T. T. Puck, and John R. Sadler, studying bacterial genetic regulation. He then took an appointment as professor of physics at Northern Michigan University, spending summers as a visiting staff member in applied mathematics and theoretical biology at Los Alamos Scientific Laboratory where he helped to organize GenBank.

Moving to Boston University in 1991, Smith became a professor in the departments of bioengineering and pharmacology and director of The BioMolecular Engineering Research Center (BMERC) . His center is currently working under NIH and NSF grants on activation of inflammation stress response pathways, cellularsignaling problems (with the Alliance for Cellular Signaling), the generation of automated models of protein folds, and the core genomics of the origin of eukaryotes.

A science writer at Boston University, Michael Seele, writes of how Smith and Michael Waterman came to write his only geology paper as follows:

"As the pair walked to lunch, they passed through the geology department lobby, where two large core samples on display stopped them in their tracks. Similar sequences of strata on different columns were connected by strings. Smith and Waterman immediately saw the columns as strands of DNA and the comparable strata as the short protein sequences they were trying to align. "We now faced the possibility that a geologist had solved the problem before us," Smith said. Resigned, Smith and Waterman visited the geology chairman and asked how the sequence alignment had been done. Their mood elevated when the chairman informed them that visual observation and string were as far as anyone had advanced with a solution. "Lo and behold! This was an unsolved problem in geology," Smith said. "This resulted in our first geology paper, basically written over the next couple of days." With a fresh perspective, the team returned to bioinformatics work and published the Smith-Waterman sequence alignment algorithm the following year. It remains one of the most referenced papers in molecular biology.

Of his award, Smith says, "I’m truly honored to join my longtime friend and colleague Mike Waterman, who preceded me in winning this award last year, as well as the distinguished company of previous winners."

The Accomplishment by a Senior Scientist Award will be presented in Vienna followed by a keynote address, titled "Computational Biology. What’s next?" to close the conference on July 25, 2007. To read additional biographical information and an abstract of Smith’s keynote address see www.iscb.org/ismbeccb2007/keynotespresentations/#smith.

Citation: Maisel M (2007) ISCB Honors Temple F. Smith and Eran Segal. PLoS Comput Biol 3(6): e128 doi:10.1371/journal.pcbi.0030128

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2006 ISCB Accomplishment by a Senior Scientist Award Winner - Michael Waterman

Picture: 2006 ISCB ASSA Winner, Michael S. Waterman

Dr. Michael S. Waterman, Professor of Biological Sciences, Computer Sciences, and Mathematics at the University of Southern California, is the 2006 recipient of the Senior Scientist Accomplishment Award of the International Society for Computational Biology (ISCB).

Waterman is best known as the developer, with Temple F. Smith, of the Smith-Waterman algorithm for determining the degree of similarity (homology) of amino acid sequences from DNA, RNA, or proteins. In their famous three-page paper in the Journal of Molecular Biology in 1981, Waterman and Smith changed the face of molecular biology and helped launch the bioinformatics revolution.

"Ever since, Mike Waterman has contributed work of prime importance in half a dozen fields of computational biology," says Professor Thomas Lengauer of the Max-Planck-Institut für Informatik and chair of the ISCB Awards Committee. "In addition to the Smith-Waterman algorithm and its follow-ons, Waterman introduced the dynamic programming approach to RNA structure prediction; and he supplied the mathematical, probabilistic, and statistical underpinning that supports BLAST and similar alignment search and evaluation tools. In 1988, he and Eric Lander derived the fundamental formulae to enable the correct assembly of genome sequences. His recent software for genome assembly, written with computational scientist Pavel Pevzner of UCSD and mathematician Haixu Tang of USC, promises to become the standard for the field."

Lengauer adds, "Waterman has had enormous impact on the fields of bioinformatics, computational genomics, and phylogeny, combining vision with technical depth, and his influence goes beyond research." Waterman has trained many prominent computational geneticists, has served on virtually all the panels and committees advising government and evaluating major grants and fellowships, and has generally guided the development of computational biology. "He wrote one of the first textbooks in this field." Lengauer says," and his latest text, Computational Genome Analysis: An Introduction, written with Richard C. Deonier and Simon Tavaré, is unique in successfully addressing the needs of students with very little background in either biology or computing. With Pavel Pevzner and Sorin Istrail, Waterman founded RECOMB, the conference on research in computational molecular biology, which held its tenth conference in April 2006."

Waterman is a founding editor of the Journal of Computational Biology and serves on the editorial boards of six other journals. He was named a Guggenheim Fellow (1995), was elected to the American Academy of Arts and Sciences (1995) and to the National Academy of Sciences (2001), and is a Fellow of AAAS and the Institute of Mathematical Statistics. In 2005, he was elected to the French Académie des Sciences. In addition to his posts as University Professor and USC Associates Chair in Natural Sciences, he is professor-at-large in the Keck Graduate Institute of Life Sciences and master of USC's Parkside International Residence College.

The Senior Scientist Achievement Award will be presented to Professor Waterman on August 10 at the ISCB annual meeting, Intelligent Systems for Molecular Biology, in Fortaleza, Brazil. Waterman will deliver the final keynote lecture, "Whole genome optical mapping," for the conference.

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