ISCB Excellent Student and Postdoctoral Paper Highlight Award

The Excellent Student and Postdoctoral Paper Highlight Award was created to celebrate the achievements of Student and Postdoc members throughout their training even during the years they are not able to attend ISCBs flagship conference, ISMB.   

The winner will receive:

• One (1) year complimentary ISCB membership
• An invitation to present the awarded work as a highlights talk at ISMB 2022 with complimentary meeting registration

How to Submit Your Paper for Consideration

Are you an ISCB Member in good standing?  

Did you submit your research to a peer review journal and get accepted?

If you have answered yes to both of the above questions, you are eligible for consideration.  Simply submit your paper using the online submission portal below.  If your paper was accepted but not yet available online, please submit a copy along with the submission.  In addition to the paper, be prepared to submit a set of 2 to 3 statements of support for each paper to be submitted.

Submission Requirements
a. First (or co-first) author on the paper being reviewed. 
b. A current ISCB member in good standing at the time of submission and acceptance.
c. A student at an accredited degree-granting institution/postdoctoral researcher at the time of initial manuscript submission.

Self nominations will be accepted for this award.

Submit your Paper 

For all submission questions, please reach out to This email address is being protected from spambots. You need JavaScript enabled to view it..

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ISCB Mentored Computational Biology Programming

The ISCB Mentored Computational Biology Programming Award was created to provide up to two students with a fellowship to learn scientific programming and software engineering.

The winning submission will receive a cash award of $2000 USD and will be announced at ISMB/ECCB 2021.

SUBMISSIONS

How to Submit:

The mentee should submit a work proposal via the link below to include brief proposal (similar to a grant proposal) that is no more than 6 pages.  The proposal should clearly state the goals of the project, the timetable for development, the tools (language, libraries, etc..) that were used, a brief architectural overview and clear deliverables.  Make sure to submit the project along with support letter from your mentors.

*Special consideration will be given to mentor-mentee collaborations across disparate geographic regions, and to mentees from low-income countries*

Mentee/Mentor Eligibility Requirements:

• Student mentee needs to be a current ISCB member.
• Mentors need sufficient software development experience.
• If the student’s existing supervisor is to be a mentor, an additional co-mentor is mandatory.  

Submission Requirements:

• The projects can be part of the graduate project of the applicant.
• The project should include a timetable & be finite: no more than 3 months.  

Submissions Closed.  Check back for updates.

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2018 Outstanding Contribution to ISCB: 
Russ Altman

The Outstanding Contributions to ISCB Award was introduced in 2015 to recognize Society members who have made lasting and beneficial contributions through their leadership, service, and educational work, or a combination of these areas. Russ Altman, Kenneth Fong Professor and Professor of Bioengineering, of Genetics, of Medicine (General Medicine Discipline), of Biomedical Data Science, and, by courtesy, of Computer Science, is the 2018 winner of the Outstanding Contributions to ISCB Award and was recognized at the 2018 Intelligent Systems for Molecular Biology (ISMB) meeting in Chicago, Illinois held on July 6 - 10, 2018.

Altman’s years of dedicated service to ISCB began when he attended the very first ISMB meeting in 1993. As a brand new faculty member, he remembered how he felt at home at ISMB, surrounded by a community of scientists also interested in computational biology and bioinformatics. Altman’s enthusiasm at this first ISMB meeting led him to help organize the next ISMB meeting. He recalled, “It became clear that there was no obvious “host” for ISMB 1994, so I volunteered to host it at Stanford, where we had a lovely meeting with a couple of hundred people. We had some extra money after paying our bills, so we wanted to send the money to wherever ISMB 1995 was going to be (UK). For the first few years, this is how ISMB worked—the organizers from one year would send the leftover funds as a seed for the next ISMB. There was no organization, and as the size of the leftover check increased, we started getting nervous and realized we needed to create a legal entity.  ”ISCB was born at ISMB 1997 in Halkidiki, Greece, where organizers of former ISMB meetings and others sat at dinner on the beach and planned the society and figured out how to incorporate it. Altman has warm recollections of that historic gathering and said, “There are pictures of that great dinner and group, and I treasure the memory of that meeting.”

Altman has enjoyed serving ISCB at all levels since its inception, from work on the Publications Committee and as a conference organizer, to his tenure on the ISCB Board of Directors (1997-2005) and as ISCB President (2002-2005). Altman’s early work on the Publications Committee included applying for PubMED to index the ISMB proceedings, which was a critical step in helping ISCB members receive academic credit for their conference papers. Altman also helped negotiate the agreement to have Bioinformatics named as an official ISCB journal. Beyond ISMB, Altman has been an organizer of the Pacific Symposium on Biocomputing, and has facilitated the relationship between this conference and ISCB.

As computational biology and bioinformatics have grown into stand-alone fields, Altman has made many critical scientific contributions through his research. Altman and his research group have developed numerous computational tools that address problems in basic biology and medicine, with a particular interest in understanding drug responses. His work has included studies of structure-function relationships in macromolecules, understanding RNA structure and folding, and assessing drug responses at the molecular, cellular, organismal, and population levels.

Altman believes that it is critical to bring awareness to the greater scientific community that computational biologists and bioinformaticians are more than just great collaborators, but they also lead major research projects. He considers service to ISCB as a way established PIs, junior faculty, and trainees can help bring about this awareness to advance the field. Altman considers ISCB to be a community that provides both valuable service opportunities and sources of mentorship and collaboration for scientists.

Altman’s dedication to the field computational biology has been recognized by his election as an ISCB Fellow (2010), as well as with numerous other honors, including election as a member of the National Academy of Medicine (formerly the Institute of Medicine, 2009) and a Fellow of the American Association for the Advancement of Science (2014). Altman has also worked as an editor and reviewer for numerous scientific journals, including serving as Co-Editor-in-Chief of the Annual Review of Biomedical Data Science.

Altman’s many years of service to ISCB have been critical to the very formation and evolution of the Society from its infancy as a small meeting to the globally recognized professional organization that it is today.
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Full bibliographical articles profiling the award recipients please see the ISMB 2018 focus issue of the ISCB newsletter as well as the ISCB Society Pages in PLOS Computational Biology and OUP Bioinformatics.  Later this year, articles will be publish in F1000 Research ISCB Community Journal.

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2018 ISCB Innovator Award M. Madan Babu

2018 ISCB Innovator Award: M. Madan Babu

The ISCB Innovator Award recognizes an ISCB scientist who is within two decades of having completed his or her graduate degree and has consistently made outstanding contributions to the field of computational biology. The 2018 winner is Dr. M. Madan Babu, Programme Leader at the MRC Laboratory of Molecular Biology, Cambridge, UK. Madan received his award and delivered a keynote presentation at the 2018 International Conference on Intelligent Systems for Molecular Biology in Chicago, Illinois,  held on July 6-10, 2018.

M. MADAN BABU: PEERING INTO THE REALM OF REGULATION

M. Madan Babu is the head of the Regulatory Genomics and Systems Biology group at the MRC Laboratory of Molecular Biology, Cambridge, UK. His work focuses on understanding how cellular systems are regulated at different scales (molecular, systems, and genomic levels) and how this impacts genome evolution.

Madan grew up in Chennai, India and developed early interests in computer science and biotechnology. As a young child, he has vivid memories of his father bringing home a personal computer, and soon after he became interested in learning to program. He also remembers when his family first started using the internet, and recalled, “In the mid-90’s, we started having access to the Internet. This made a big difference in the days where access to information beyond textbooks was not readily available; so thanks to my father I had these opportunities early in my life.” Madan discovered biotechnology as a high school student, and attributes his lifelong interest in biology to the impact of his biology teacher, Dr. M.C. Aruna, who discussed foundational biological concepts with him, including how genetic information can be used to understand living systems. Madan went on to pursue a Bachelor of Technology (Biotechnology) degree at Anna University, Center for Biotechnology in Chennai, India. He first became of aware of computational biology during his first year undergraduate research internship, at which time he was exposed to the work of Cyrus Chothia and Arthur Lesk in a course on protein structure. He became fascinated with this research area and then delved into seminal papers on computational genomics, protein engineering, and structural bioinformatics. As an intern, Madan pursued undergraduate research under the guidance of Prof. Balaram and Prof. K. Sankran, and saw this a key turning point in his career path. He recollected, “We started applying methods from computer science to study protein sequences and structures. For the first time, I experienced how to define a scientific problem, develop computational methods to solve it, and write up and defend the findings for publication. This really got me excited and that was when I decided that I would like to pursue a career in computational biology.”

Madan recognizes that his interest in computational biology was fostered by his ability to access publicly-available protein and genomic data on his own computer, as well as the open access he had to lecture materials, methods and algorithms from computational biologists spanning the globe. He said, “I cannot forget the day when I wrote an email to RCSB from India and received a 5-part CD-ROM with coordinate data for all protein structures. Being able to look at protein structures using RASMOL from home and writing FORTRAN programs to analyze structures as an undergraduate student was one of the most exciting experiences that really captured my interest in the field.” Madan left India in 2001 to pursue his PhD in computational genomics at the MRC Laboratory of Molecular Biology and Trinity College, University of Cambridge, UK under the guidance of Dr. Sarah Teichmann. His PhD research explored various aspects of gene regulatory networks, and marked the beginning of a very fruitful mentorship under Teichmann. Madan carried out his postdoctoral training at the National Center for Biotechnology Information, NIH in Bethesda, MD, USA under the guidance of Dr. L. Aravind, during which time he learned the importance of having broad interests in diverse subject areas as well as critically analyzing the complexity of biological systems at every possible level of detail. After a brief but extremely productive postdoctoral fellowship, Madan became a group leader at the age of 26 of the Regulatory Genomics and Systems Biology Group at the MRC Laboratory of Molecular Biology in 2006. As a PI, he has come to appreciate how his team of scientists can work together to tackle scientific questions on a much larger scale and shed new light on long-standing, fundamental questions. He said, “One of the things that I really enjoy about the field of computational biology is that you really integrate knowledge from various disciplines-- biology, statistics, computer science, mathematics, physics and chemistry. This means our lab is an amalgamation of people across disciplines that are really passionate about using interdisciplinary approaches to solve the problems they are working on.”

Madan’s group currently focuses on several areas of research, including studies on G-protein coupled receptors (GPCRs), a protein family involved in almost every aspect of human physiology and targeted by numerous drugs. Madan’s group is also using a combination of computational and experimental approaches to discover which parts of unstructured protein regions are functional and understand what makes them functional. His group is interested in applying developments in statistical learning and advances in large-scale genome sequencing to better understand natural variation in the human population as well as gain insight into how genomic variation impact rare and common diseases.

Madan is greatly honored to be selected as the recipient of the 2018 ISCB Innovator Award. He is grateful for his academic mentors and colleagues, including Sarah Teichmann, L. Avarind, Cyrus Chothia, Michael Levitt, Veronica Van Heyningen, Eugene Koonin, Stephen Michnick, Richard Kriwacki, Uri Alon, Arthur Lesk, Alexey Murzin, Julian Gough, Daniela Rhodes, Gebhard Schertler, Peter Wright, Keith Dunker, Janet Thornton, Tom Blundell and Venki Ramakrishnan, who have inspired him through their work and/or provided him valuable advice at various stages of his career. He is also appreciative of his past and present group members, and the MRC Laboratory of Molecular Biology for the freedom to develop new skills and take risks in pursuing research that pushes scientific boundaries. Last but not least, he is grateful to his parents, sister, wife and 2-year old son for their love, support and inspiration.
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Full bibliographical articles profiling the award recipients please see the ISMB 2018 focus issue of the ISCB newsletter as well as the ISCB Society Pages in PLOS Computational Biology and OUP Bioinformatics.  Later this year, articles will be publish in F1000 Research ISCB Community Journal.

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2018 Overton Prize Winner: Cole Trapnell

2018 ISCB Overton Prize: Cole Trapnell

Each year the International Society for Computational Biology (ISCB) recognizes the achievements of an early to mid-career scientist with the Overton Prize. This prize honors the untimely death of Dr. G. Christian Overton, a respected computational biologist and founding ISCB Board member. The Overton Prize recognizes independent investigators who are in the early to middle phases of their careers and are selected because of their significant contributions to computational biology through research, teaching, and service. ISCB is pleased to recognize Dr. Cole Trapnell, Assistant Professor of Genome Sciences at the University of Washington as the 2018 winner of the Overton Prize. Trapnell presented a keynote presentation at the 2018 International Conference on Intelligent Systems for Molecular Biology in Chicago, Illinois, held from July 6-10, 2018.

COLE TRAPNELL: BUILDING BRIDGES TO THE LAB BENCH

Cole Trapnell’s earliest interest in science began at home. He was born in Cheverly, MD and spent his childhood living in College Park, right near the University of Maryland. His father, Bruce Trapnell, is a physician scientist, and Cole has fond memories of accompanying his father to the lab. Beyond the handson experiences of doing restriction digests with his dad as young child, Trapnell most appreciates how his father encouraged him to think scientifically. He recalled, “One time we were playing a board game, and I remarked that because the last dice roll was a six, the next one wouldn’t be. My dad decided to correct my thinking, so the next thing I knew, we were flipping a penny 1,000 times to estimate the probability distribution of getting heads vs. tails. I still have the plot that we drew by hand on 1mm graph paper.”

Trapnell was first interested in physics and abstract mathematics and was drawn to how these fields tackled complex ideas in terms of “first principles.” He began learning programming as a high school student and worked as a student engineer on a robotics project for the US Army. Trapnell honed his coding skills as an undergraduate by working for a startup that developed software for the areas of retail stock, futures and foreign currency trading, and he learned how to develop tools that can do complex calculations with large amounts of data in real time. He completed a dual BS degree in computer science and mathematics at the University of Maryland, College Park in 2005 and then began his PhD in computer science there as well. Trapnell thought he would work on problems in supercomputing, but then he took Steven Salzberg’s class on bioinformatics. This brought his attention to the emergence of “next-generation” sequencing technology, and he realized the potential for high throughput computing to handle this sequence data.

Trapnell’s PhD research focused on sequence alignment, and he adapted the Bowtie algorithm developed by Ben Langmead into a program called TopHat that could handle transcriptomic data. During this time, Trapnell moved to the University of California, Berkeley, where his wife was pursuing her PhD in mathematics, and he started working with Lior Pachter, who became his co-advisor with Salzberg at UMD. As Trapnell developed TopHat and the companion tool, Cufflinks, he tested them with datasets from Barbara Wold’s lab, and he began to develop an appreciation for biological questions, especially in gene regulation. Trapnell was drawn to doing bench research, and his labmate Rob Bradley encouraged him to take that leap. He recalled, “Rob Bradley convinced me that to become a really good biologist, I should learn to do experiments. Rob, who trained as a biophysicist, had gone off to do a postdoc at the bench. I followed suit and joined John Rinn’s lab (at Harvard University), where I worked to both do experiments and analyze them myself.” Trapnell’s time in Rinn’s lab not only helped him get his hands dirty doing bench research, but gave him the unique perspective of working under a scientist who pioneered the field of long noncoding RNAs.

Trapnell’s postdoctoral training opened his eyes to the realities of experimental biology and he acknowledges that these experiences have made him a better computational biologist. While Cufflinks could help him predict which individual splice isoforms may be elevated under certain disease conditions, he came to realize how hard it can be to validate these observations at the lab bench: a specific antibody may not exist for a western blot or technical difficulties may make it difficult to knock down a gene isoform in a particular model system. Trapnell had to adjust to the different culture associated with working in a wet lab. He recounted, “Computational people are often mystified and frustrated by how often their experiments fail. I like to tell them a story of my own frustration: A little while after starting my wet lab postdoc training, I was complaining to my labmate, Dave Hendrickson, that my experiments were constantly failing. He asked me how long I’d been at it, and I told him about six months. He said, “Well, give it another six months.” I thought he meant I would get better at doing experiments but what he actually said next was, “It’ll hurt less when they don’t work.” This was a tremendously eye opening thing for me,  because he was trying to tell me that being an effective experimentalist means anticipating failure, planning for it, designing controls that can detect it, and parallelizing work within projects so that you can make progress in one direction even when you’re stuck in another. There are similar cultural differences that experimentalists encounter when learning to program.” As a PI, Trapnell is supportive of students and trainees that want to gain both experimental and computational experience, but he wants to them to learn to understand the culture of these two realms and not just acquire the necessary skills to do experiments or develop algorithms.

Throughout his training, Trapnell has valued the guidance of his mentors. His current lab is positioned between the labs of Stan Fields and Bob Waterson, both leaders in the field of genomics, and they been invaluable advisors to Trapnell. He said, “Despite their fame and their busy lives, both go way out of their way to advise me on how to bring my research and lab to its potential.” All of his mentors have inspired Trapnell to build a lab culture that encourages open, inspiring and rigorous science. As he established his own lab at the University of Washington, he has started to think differently as a PI and said, “I am continually faced with the question: What do I think is the most important scientific contribution I can make?” Shifting his mindset has been a challenge, but he is still broadly interested in gene regulation, especially gaining a more quantitative understanding of the epigenome. Trapnell considers the advances in single-cell measurements as critical to quantifying aspects of gene regulation, and his team is developing tools for single-cell measurements of gene expression, chromatin accessibility, and other features of the molecular state of the genome. Much of this work is in collaboration with Jay Shendure, whose lab specializes in molecular biotechnology development. Trapnell is keen on this collaboration: “Jay and I have very different approaches but share a common goal to transform our understanding of development and disease using single-cell technologies. Our collaboration has been fantastically productive and fun so far, and there’s a lot more to come.”

Trapnell is deeply honored to selected for the Overton Prize, and said, “I feel strongly that my success is at least as much a product of my being in the right place at the right time with the right collaborators as from any choices I made. I have been repeatedly given great opportunities and I’ve tried to make the best use of them, but I would have gotten nowhere if not for the generous help and creativity of a long list of mentors, collaborators and colleagues.”
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Full bibliographical articles profiling the award recipients please see the ISMB 2018 focus issue of the ISCB newsletter as well as the ISCB Society Pages in PLOS Computational Biology and OUP Bioinformatics.  Later this year, articles will be publish in F1000 Research ISCB Community Journal.

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2018 ISCB Accomplishment by a Senior Scientist Award Ruth Nussinov

2018 ISCB Accomplishment by a Senior Scientist Award: Ruth Nussinov

Christiana N. Fogg¹, Diane Kovats ^2*, Ron Shamir<sup>3

1</sup> Freelance Writer, Kensington, Maryland, United States of America,
² International Society for Computational Biology,
³ Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel
^* This email address is being protected from spambots. You need JavaScript enabled to view it.

Each year, the International Society for Computational Biology (ISCB) recognizes a leader in the fields computational biology and bioinformatics with the Accomplishments by a Senior Scientist Award. This is the highest award bestowed by ISCB in recognition of a scientist’s significant research, education, and service contributions. Ruth Nussinov, Senior Principal Scientist and Principal Investigator at the National Cancer Institute, National Institutes of Health and Professor Emeritus in the Department of Human Molecular Genetics & Biochemistry, School of Medicine at Tel Aviv University, Israel, was honored as the 2018 winner of the Accomplishment by a Senior Scientist Award. She received her award and presented a keynote address at ISCB’s premiere annual meeting, the 2018 Intelligent Systems for Molecular Biology (ISMB) conference in Chicago, Illinois,  held on July 6–10, 2018.

RUTH NUSSINOV: IN SEARCH OF BIOLOGICAL SIGNIFICANCE

Ruth Nussinov is a computational biologist with research interests that have touched every aspect of the field, from her PhD research on RNA secondary structure prediction to her visionary work on DNA sequence analysis, to proposing that all protein (and other biomacromolecules) conformations preexist and that all dynamic proteins are allosteric, to her current studies focused on Ras signaling in cancer. Nussinov’s deep intellectual curiosity has guided her research interests throughout her career.

Nussinov was raised in Rehovot, Israel, and attributes her early interest in science to watching her father conduct pioneering agricultural research that focused on adapting crops to the Israeli climate [1,2]. Nussinov’s father, Shmuel Hurwitz, was born in Minsk, Russia, and studied chemistry at Moscow University but later immigrated to Palestine (present day Israel) after his arrest for Zionist activities. It was here he discovered the great need for agricultural research. He pursued these studies at Berlin University but left Nazi Germany after his graduation in 1933 to found the Agricultural Research Station in Rehovot. Hurwitz was a founding member of the Faculty of Agriculture at the Hebrew University and was recognized for his significant contributions to advancing Israel agriculture with the 1957 Israeli Prize. As a child, Nussinov often joined her father on trips to his field sites, and his devotion to research and intense work ethic influenced her deeply and shaped how she approaches her work.

Nussinov also attributes her success as a scientist to the unwavering support from her husband, Shmuel Nussinov. They married just after she completed her service in the Israeli Army, during which time he was pursuing his graduate studies in particle physics at the Weizmann Institute. Her husband’s research advisor moved to the University of Washington, so Nussinov continued her undergraduate studies there (in microbiology) and went on to pursue her master’s degree in biochemistry at Rutgers University while her husband pursued postdoctoral research at Princeton University. They returned to Israel when Shmuel Nussinov joined the faculty at Tel Aviv University. When they came back to the United States several years later for his sabbatical, Ruth Nussinov enrolled in a PhD program in biochemistry at Rutgers and was mentored by a newly arrived assistant professor named George Pieczenik who had just come from Cambridge (United Kingdom). Nussinov recalled, “He said, ‘You know Ruth, Fred Sanger has just developed a DNA sequencing method and consequently there will be RNA sequences, and we will need an algorithm for the prediction of the secondary structure of RNA.’” She ran with this idea and worked tirelessly to develop the foundational Nussinov dynamic programming algorithm that is still in use today [3]. Nussinov’s PhD research has driven her career long search for questions that tackle issues of biological significance. She worked relatively independently on her project and was able to graduate in two years, and this early autonomy was critical to shaping her career path as an independent researcher.

Nussinov and her family returned to Israel, and she pursued postdoctoral studies in the Structural Chemistry Department of the Weizmann Institute and made several seminal contributions to DNA sequence analysis. She also worked as a visiting scientist in the Chemistry Department at the University of California, Berkeley, and in the Biochemistry Department at Harvard University. In spite of her impressive body of work and concept driven approach to scientific inquiry, Nussinov faced difficulties in securing a position at Tel Aviv University in the mid 1980s due to her husband’s existing position at the university and her unconventional, independent career path [4]. In 1985, Nussinov was finally appointed as an associate professor at Tel Aviv University and also became affiliated with the National Cancer Institute (NCI)/National Institutes of Health (NIH). During these early years, she credits her husband for giving her valuable advice about handling criticism from manuscript reviewers. He urged her to trust in her work and to reflect on and revise her manuscripts and resubmit them, as publications matter to the progress of a junior and unknown scientist [2].

One of Nussinov’s most profound contributions to the field is the “conformational selection and population shift” model of molecular recognition [5 9]. She and her colleagues first proposed this model in 1999 as an alternative paradigm to the “induced fit” model of protein–protein interactions. The induced fit model hypothesizes that conformational changes to a protein occur in a stepwise fashion upon binding to a ligand. In contrast, the conformational selection model portends that unbound molecules exist in all possible structural conformations, but some unbound higher energy conformations preferentially associate with a binding partner and cause a shift in equilibrium that favors this conformation. This model can explain numerous interactions observed for protein–ligand, RNA–ligand, protein–protein, protein–DNA, and protein–RNA interactions and can explain mechanisms of biological regulation, including oncogenic signaling. Nussinov is currently focused on the Ras protein and its interactions with effectors, with a particular interest in KRAS driven adenocarcinomas. She observed that self as sociation of GTP dependent K Ras dimers at different interfaces regulates which effectors bind to the dimers, which can alter downstream activity [10]. Nussinov and her team have also described the critical role of calmod ulin selectively binding to the GTP bound K Ras4B onco genic isoform, which promotes the initiation and progres sion of adenocarcinomas due to full activation of PI3Kα/Akt signaling in addition to the mitogen activated protein kinase (MAPK) pathway. These mechanistic insights are critical to developing better cancer drugs, and this work was recognized in the “Best of the AACR Journals Collec tion 2015.” Nussinov is also starting to explore interac tions between the human proteome and pathogens, given the growing appreciation of the microbiome on human health. Nussinov’s impact to the fields of computational biology and bioinformatics is notable. She has published more than 500 articles and has been ranked as a Highly Cited Researcher (ranking among the top 3,000 researchers or 1% across all fields according to Thomson Reuters Essen tial Science Indicators, http://highlycited.com/ December 2015) with more than 43,000 citations to date. Nussinov has also given over 300 invited talks and continues to maintain an active speaker schedule.

Nussinov serves as the Editor in Chief of PLOS Computational Biology, and she has also served as an editor and reviewer for numerous leading journals. Her scientific contributions have been recognized through her election as a Fellow of the Biophysical Society (2011) and an ISCB Fellow (2013). Nussinov has been a devoted mentor and advisor to graduate students and trainees throughout her career, and she has mentored dozens of PhD students, including numerous women. She has tried to model her mentorship to how she was trained, and she said, “I very much encourage independence and like for students to suggest a problem to study.”

Nussinov has always felt a close connection with ISCB, and her recognition with the 2018 ISCB Accomplishments by a Senior Scientist Award is a fitting tribute to her contributions to ISCB and to computational biology in general. She said, “I feel that’s where I belong and that’s where I want to be. I care very much about the development and sustainability and contribution of computational biology to all biological, chemical, and physical sciences.”

References
http://en.hafakulta.agri.huji.ac.il/people/shmuel hurwitz

Nussinov, Ruth. “TrendsTalk An Interview with Ruth Nussinov.” (2017) 761 763.

Nussinov, Ruth, et al. “Algorithms for loop matchings.” SIAM Journal on Applied mathematics (1978) 35.1: 68 82.

Shehu, Amarda. “Computational biologist in profile: Ruth Nussinov.” ACM SIGBioinformatics Record 3.3 (2013) 12 14.

Tsai CJ, Kumar S, Ma B, Nussinov R. “Folding funnels, binding funnels, and protein function.” Protein Sci. (1999) 8: 1181 90.

Ma B, Kumar S, Tsai CJ, Nussinov R. “Folding funnels and binding mechanisms.” Protein Eng. (1999) 12: 713 20.

Tsai CJ, Ma B, Nussinov R. Folding and binding cascades: shifts in energy landscapes. Proc Natl Acad Sci U S A. (1999) 96: 9970 72.

Ma B, Shatsky M, Wolfson HJ, Nussinov R. Multiple diverse ligands binding at a single protein site: a matter of pre existing populations. Protein Sci. (2002) 11: 184 97.

Boehr, David D., Ruth Nussinov, and Peter E. Wright. “The role of dynamic conformational ensembles in biomolecular recognition.” Nature Chemical Biology (2009) 5.11: 789.

Nussinov R, Tsai CJ, Jang H. Oncogenic Ras Isoforms Signaling Specificity at the Membrane. Cancer Res. 2018 Feb 1;78(3):593 602.
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Full bibliographical articles profiling the award recipients please see the ISMB 2018 focus issue of the ISCB newsletter as well as the ISCB Society Pages in PLOS Computational Biology and OUP Bioinformatics.  Later this year, articles will be publish in F1000 Research ISCB Community Journal.

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ISCB Student Wikipedia Competition

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Picture: 2012 Accomplishment By A Senior Scientist Award Prize Winner, Gunnar von Heijne. Photo by Max Brouwer

2012 ISCB Accomplishment by a Senior Scientist Award Winner - Gunnar von Heijne

Perhaps it all began with the French lessons. As a a young PhD student in theoretical physics at the Royal Institute of Technology (KTH) in Stockholm, Gunnar von Heijne decided, on whim, to brush up on his rusty, schoolboy French. He took a few lessons and also subscribed to the French popular science magazine La Recherche.

Flicking through its pages, he came across a short article on protein secretion and the signal hypothesis, the mechanism that describes the way secretory proteins cross a membrane.

At the time, the late-1970s, very little was known about this process, but some ideas were beginning to emerge. For example, it was thought that a so-called signal peptide---a short chain of amino acids---at the end of the protein carried the signal that determined how the proteins are transported out of the cell.

The article confused him, however. It showed a diagram of a hydrophobic signal peptide squeezing through the similarly hydrophobic membrane. "That didn't make sense to me. The hydrophobic peptide ought to become anchored in the membrane,"he says.

The puzzle piqued his interest. He solved it by calculating the energetics of a polypeptide chain passing through lipid bilayer, which he published in 1979. This work by a theoretician created ripples in a field dominated by experimentalists.

And so began the career for which he now receives the Accomplishment by a Senior Scientist Award from the International Society for Computational Biology (ISCB). "Gunnar is one of the big stars of our field,"says Burkhard Rost, president of the ISCB. "He is one of the few who completely change the field using computational methods."Polypeptide energetics was only the start, however.

By the early 1980s, molecular biologists had begun to determine the sequence of amino acids in the signal peptides from different proteins. However, little had been done to study the properties of signal peptide sequences as a group.

von Heijne changed this. He began comparing the sequences, looking for recurring patterns that might help to identify them. "I looked at 20 to 30 signal peptides. Once you did that, some clear patterns emerged that had not been seen before,"he says.

He found that small, uncharged amino acids tended to occupy certain positions in signal peptide chains, the -3 and -1 positions. It is at this site that the signal peptide is later cleaved from the protein once it has passed through a biomembrane. This pattern has since become known as the (-3, -1)--rule.

"Nowadays you would say this was a very trivial bioinformatics study,"he says modestly. However, this was an important discovery and von Heijne's paper has since become one of the most highly cited in the field.

He then used the newly discovered patterns to make predictions about proteins. For example, it became possible to create an algorithm that would take a protein sequence and predict whether it had a signal peptide at the end.

Initially, that was not very useful. When molecular biologists sequenced a gene or messenger RNA, they generally knew what they were working on; whether it would have a signal peptide on the end or not.

But that changed when sequencing became faster and biologists started to sequence things they didn't know much about. "The algorithms have continually improved and are now extremely useful,"he says.

Secretory proteins have to move across a lipid bilayer through a molecular machine called a translocon. The signal peptide guides the ribosome that makes the protein, towards the translocon. This triggers the opening of this protein-conducting channel through the membrane.

But other types of protein only make the journey partway, becoming embedded half in and half out of the membrane. These so-called membrane proteins use the same translocon machinery as the secretory proteins. "So it was a natural step to start looking at these membrane proteins next,"says von Heijne.

The part of the protein that ends up in the membrane is very different to the parts outside exposed to water. This transmembrane section must be much more hydrophobic. So the trick to predicting which parts of a protein become embedded in the membrane is to look for the segments that are most hydrophobic.

Once you know the transmembrane segments, an interesting problem is to determine how the protein becomes woven into the membrane. For example, if it has four hydrophobic sections, there are two ways in which it can be arranged in the membrane: with the termini pointing either in or out. But which orientation should the protein take?
"We discovered a very simple principle that determines this,"he says. The regions that connect the transmembrane segments contain positively charged amino acids, which give them an electric potential. The simple principle is that the segments with the greatest number of positive charges end up inside the membrane, an idea that has since become known as the "positive inside rule".

"This is very important work and provides some of the best data on membrane proteins,"says Alfonso Valencia, chair of the ISCB awards committee.

In the late 1980s, von Heijne began to realise that he could gain significant insight into these and other problems by doing experiments rather than just theory work. So he set up his own lab. "I trained as a chemist so I wasn't a complete novice in a wet lab,"he says.

This first idea was to see whether it was possible to make proteins that inserted "upside-down"into the membrane. He could show that by changing the location of the positively charged amino acids in a protein, it is possible to make it take up the opposite orientation.

This link between his theoretical and practical work has been important for him. Bioinformatics studies often throw up patterns that may or may not have biological relevance. "The only way to determine whether they are important is to do the experiments,"he says.

"It's hard to overstate the significance of von Heijne's work. Membranes and transmembrane proteins are the gates and gatekeepers to our cells; they determine what gets in and what stays out,"explains Rost. "That's why around two-thirds of drugs target membrane proteins."Understanding the structure of transmembrane proteins provides crucial insight into how cells work and is also useful for future drug development. "That's why the methods developed by Gunnar are so important,"says Rost.

To continue his work, von Heijne set up the Stockholm Bioinformatics Centre at the beginning of the millennium. And today, von Heijne runs the Centre for Biomembrane Research in Stockholm, where he has brought together computational, modelling, and experimental groups. Few places can boast the same breadth of experience under one roof.

Throughout this time, von Heijne has maintained an impressive work--life balance as a scientist, a husband, and a father. He says that's been possible, at least in part, because he was working in a new field with few competitors. "I never felt stressed that we'd be scooped. I work hard but not crazily ."Others clearly admire his positive approach, which he combines with a relaxed attitude. "He also looks ten years younger than he has any right to!"says one envious colleague.

For a while in the 1980s, he spent half his time working as a science journalist for the Swedish National Radio. "You decide on Monday what you broadcast on Friday so there is immediate feedback, which has a good pulse to it,"he says.

But for von Heijne, doing science is more satisfying than reporting it. "Radio stories have a short half life; they're on air, then they're gone,"he says. "The rewards in science are greater and longer lasting."It's surprising how far schoolboy French can take you.

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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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2017 Outstanding Contribution to ISCB: 
Fran Lewitter

The Outstanding Contributions to ISCB Award was launched in 2015 to recognize individuals who have made lasting and valuable contributions to the Society through their leadership, service, and educational work, or a combination of these areas. Fran Lewitter is the 2017 winner of the Outstanding Contributions to ISCB Award and will be recognized at the 2017 Intelligent Systems for Molecular Biology (ISMB)/European Conference on Computational Biology meeting in Prague, Czech Republic being held from July 21-25, 2017.

Fran Lewitter completed her PhD in Human Genetics and Statistical Genetics at the University of Colorado Boulder. After completing postdoctoral work in Genetic Epidemiology at Harvard Medical School, she worked on the first five years of the GenBank project.  Lewitter then worked in the Biology Department at Brandeis University in a number of capacities, including supporting molecular biology computing and being involved with their Genetic Counseling program. In 1994, she joined the Whitehead Institute for Biomedical Research in Cambridge MA. to run a bioinformatics core facility. For twenty years, she worked with and trained basic biomedical researchers who were doing sequencing or were using bioinformatics to gain a deeper understanding of different biological questions.  She was later named the Founding Director of Bioinformatics and Research Computing and was given a larger staff as the demand for bioinformatics information grew in the late 1990s and early 2000s.

Lewitter’s first encounter with ISCB occurred when she attended ISMB 2001 in Copenhagen, Denmark, followed by a one-day satellite meeting, Workshop on Education in Bioinformatics (WEB). At the time, Whitehead did not have a large bioinformatics community, and she was in search of peers who were running bioinformatics core facilities and teaching bioinformatics to biologists.  “One thing that attracted me to go [to ISMB] was the one day workshop on education and bioinformatics, since I was so heavily involved in educating people. I went to every meeting since then.” At ISMB 2002 in Edmonton, Lewitter helped organize an informal gathering of bioinformatics core facility managers, and this unique gathering spurred the organization of a mailing list, which became an invaluable resource for Lewitter and her peers as they faced challenges and questions unique to running a core facility.

Since her early encounters with ISCB, Lewitter has become a tireless advocate for bioinformatics education and training on behalf of ISCB. As a core facility director, she has offered her unique academic perspective and voice through her service on the ISCB Education Committee and as a member of the Board from 2008- 2017.  Lewitter recognized the growing demand for bioinformatics training early in her involvement with ISCB, and she worked to strengthen ISCB’s role in supporting bioinformatics education and training by promoting the inclusion of bioinformatics education content in the main conference programs. To this end, she has organized Workshops on Education in Bioinformatics (WEB) at ISMB meetings since 2009, and she has helped build ISCB community activities including the CoBE COSI (Computational Biology Education Community of Special Interest).  Lewitter’s leadership of the ISCB Education Committee helped unite the global bioinformatics education community through shared objectives and brought greater awareness of the committee’s work through tutorials and training opportunities offered at ISCB conferences. Lewitter recognizes that one of the most critical aspects of training is “to introduce biologists to bioinformatics vocabulary whether or not they would be using the primary bioinformatics tools.” This fosters better collaborations between bioinformatics experts and bench scientists and is necessary to facilitate the ongoing integration of bioinformatics into all aspects of biology.

Lewitter has been instrumental in bringing together ISCB and GOBLET (the Global Organization for Bioinformatics Learning, Education and Training) and coordinating activities by which these two organizations work together to further bioinformatics training on a global scale. She has advocated for the development and maintenance of bioinformatics education resources on ISCB webpages, and these electronic resources are valuable tools used by the global bioinformatics education community.

Lewitter has valued her membership in ISCB for providing her opportunities to “get to know innovative people.” She has especially appreciated meeting other core facility directors and managers. Lewitter said, “ It’s gratifying to hear I am doing the right thing, or other people have ideas that can help me or I can help them. It is good to talk to other people about issues of running a core facility, what courses to teach or what tools are the best to teach?” Despite having retired from Whitehead Institute three years ago, she enjoys her continued involvement in ISCB activities.  She is also heartened by the rising generation of ISCB members who are involved with the ISCB Student Council. Lewitter hopes ISCB will continue to grow and thrive and is grateful for being recognized for her steadfast efforts to promote and further bioinformatics education.

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2017 ISCB Innovator Award Aviv Regev

2017 ISCB Innovator Award: Aviv Regev

2017 marks the second year of the ISCB Innovator Award, which recognizes an ISCB scientist who is within two decades of having completed his or her graduate degree and has consistently made outstanding contributions to the field.  The 2017 winner is Dr. Aviv Regev, Professor of Biology at the Massachusetts Institute of Technology (MIT), a Core Member and Chair of the Faculty of the Broad Institute of MIT and Harvard, and an HHMI Investigator. Regev will receive her award and deliver a keynote address during ISMB/ECCB 2017 in Prague, Czech Republic (July 21 - July 25, 2017).

AVIV REGEV:  SEEING CELLS AS LIFE’S SMALLEST CIRCUITS

Aviv Regev first pursued her studies in a unique interdisciplinary program at Tel Aviv University, where she planned to focus on math and computer science¹.  But she discovered her interest in biology in the classroom of evolutionary biologist Eva Jablonka. Regev said, “I found biology because of her – in my first year as an undergrad, I took a genetics course with her in what is now called the ‘flipped classroom’ style.  It was all abstract and inferential, and I was hooked.”

Before starting her PhD thesis at Tel Aviv University, Regev began to really think about cells as computers, particularly how they are comprised of circuits. Regev’s deep interest in this concept started at a conference where new approaches for modeling concurrent computation were featured, and she immediately considered this as a way to model cell circuitry.  She was able to develop her ideas into a PhD project under the mentorship of Udi Shapiro and Eva Jablonka, and she recalled, “No one was working on this type of project. I did, however, have the great fortune to find Udi, who listened to my idea. He thought it was important. He didn’t want to work on it himself – but he wanted me to be able to work on it.”

Regev completed her PhD in 2002 and was selected to be a Bauer Fellow at the Center for Genomics Research at Harvard University, which gave her an intellectual community, as well as freedom and funding to build a small independent research group.  She continued to pursue her interest in modeling cell circuits using gene expression and genomic data, and she developed with her colleagues several widely used algorithms and computational tools, including Module Networks and Synergy.  She received early support from Andrew Murray at Harvard University, who shared Regev’s view that it was critical to deeply understand both theory and experiments.

In 2006, Regev was given a joint faculty appointment at MIT and the Broad Institute, and she started applying her cell circuit modeling algorithms to understanding different cell types, particularly cells of the immune system.  Once again, Regev struck out on an independent line of research.  She recalled, “Many people were not focused on circuits.  But that was OK.  I wanted to build and be part of a community that would open a new direction.” Eric Lander at Broad – a longtime supporter of female and young scientists with leadership potential -- stood behind and supported Regev’s independent scientific vision at this critical point in her career.

Regev’s independent research program has blossomed since she founded her lab, and she has applied her interest in how cellular circuits function and rewire to a wide range of biological questions, including how immune cells rapidly respond and differentiate, how hematopoietic stem cells develop into different blood cells, and how evolutionary changes occur over millions of years.  She is both a computational biologist with keen instincts about how to extract insight from data, and an experimental biologist with the ability to create new methods and deploy cutting edge technology to address fundamental questions.

Regev continues to be drawn to seemingly intractable problems, such as biological scenarios with a massive number of hypothetical combinations or interactions, and making them into manageable problems by using sampling approaches.  Her work on cells of the immune system reflects this focus, and she recalls one of her most unexpected findings emerged in 2012 while working with collaborators on applying single-cell RNA-seq to the analysis of dendritic cells.  In contrast to present day technology, which enables the profiling of thousands of cells quickly and cheaply, this study only looked at 18 cells and required a tremendous effort.  Regev recalled, “What we found was surprising in two ways.  First, we were examining just one cell type which we thought was well-defined, so we did not expect to find major differences in gene expression between the cells – yet we saw 1,000-fold differences, from which we could recover regulatory molecules that accounted for this variation. Second, we discovered surprising patterns in alternative splicing – some cells preferentially used one isoform, others used another. We had been expecting the cells to use both.  This added up to a bigger surprise: we weren’t really looking at one group of cells. We were looking at two subgroups, which we now know represent different developmental programs.  A great deal of my work now focuses on understanding heterogeneity of this type – defining and understanding cells at a much higher resolution than we could before.”

Regev has passed along her love of science through her mentorship of postdocs, graduate students, and undergraduates, and outside of the lab she has maintained an intense teaching load and worked to overhaul the undergraduate genetics course to include quantitative content.  She is grateful to her mentors who gave her freedom to pursue her own scientific interests and this has guided her style of mentorship. She said, “Today, when I see a person with an idea,  I don’t care about career stage -- maybe they’re a grad student or an undergrad; maybe they are a seasoned staff scientist. I care about who they are. Do they show the seeds of independence, vision, and leadership? And what is their idea? If it’s challenging in entirely new ways, and can transform the world, it should be grown. As I mentor my students and postdocs, I try to let them spread their own wings – to be their colleague and collaborator.”

At Broad, Regev was recently appointed Chair of the Faculty, and in this role she has been focusing on initiatives to strengthen and build communities around computational biology and advance software engineering approaches to biological data analysis.  She has served the greater computational biology community in many ways through work on numerous advisory boards, journal editorial boards, and program committees for conferences. Regev has been a reviewing editor for eLife since its inception, and more recently a senior editor with a major responsibility for computational biology, genomics and theory papers.

Regev is gratified by her selection for the 2017 ISCB Innovator Award, and she said, “Biology is such a data science now, and ISCB is the community that made that happen – so it is especially exciting and gratifying to be receiving such an honor from peers in this community.”

1 www.hhmi.org/scientists/aviv-regev

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