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Outstanding Contributions
to ISCB Award
Scott Markel, PhD

2024 Outstanding Contributions Award: Scott Markel, PhD


Scott Markel, PhD,BIOVIA R&D Software Engineering Director, Biosciences & Scientific Informatics, Dassault Systèmes

Scott Markel, Ph.D., is an R&D Software Engineering Director in Dassault Systèmes’ BIOVIA Biosciences & Scientific Informatics group. In this role he is responsible for Discovery Studio and Pipeline Pilot’s scientific functionality. He is a former member of the Executive Committee and Board of Directors of the International Society for Computational Biology. Scott is on the editorial board of PLOS Computational Biology, co-editing the popular Ten Simple Rules series. He co-authored Sequence Analysis in a Nutshell: A Guide to Common Tools and Databases and co-edited In Silico Technology in Drug Target Identification and Validation.


ISCB will present the Accomplishments by a Senior Scientist Award, Overton Prize, Innovator Award and Outstanding Contributions to ISCB Award, at ISMB 2024 (www.iscb.org/ismb2024), which will take place in Montreal, Quebec, Canada, July 12-16, 2024.

Full bibliographical articles profiling the award recipients will be available in the ISMB 2024 focus issue of the ISCB newsletter later this year, as well as the ISCB Society Pages in OUP Bioinformatics.

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Teresa Attwood, PhD, Professor, the Department of Computer Science and School of Biological Sciences at the University of Manchester - Recipient of the ISCB Outstanding Contributions Award

2021 ISCB Outstanding
Contributions Award:
Teresa Attwood, PhD

2021 ISCB Outstanding Contributions Award: Teresa Attwood, PhD

Teresa Attwood, PhD, Professor, the Department of Computer Science and School of Biological Sciences at the University of Manchester

The Outstanding Contributions to ISCB Award recognizes an ISCB member for outstanding service contributions toward the betterment of ISCB through exemplary leadership, education, and service. The 2021 recipient of the Outstanding Contributions to ISCB Award is Teresa Attwood.

Teresa Attwood is a Professor of Bioinformatics in the Department of Computer Science and School of Biological Sciences at the University of Manchester and a visiting fellow at the European Bioinformatics Institute (EMBL-EBI).

A visionary within the field, she saw early on the power of bioinformatics education from the beginning. Teresa Attwood coauthored (with Paul Higgs) one of the first books in bioinformatics, which became a reference in Universities worldwide. Teresa was quick to recognize that ISCB was ideally situated to lead the global promotion for a strong bioinformatics education.

Teresa Attwood has been a champion of the bioinformatics education community where she has been instrumental in putting in place ISCB platforms that allow the education community to highlight their work and which raise the awareness of ISCB as a leader in bioinformatics education globally.

A longstanding and involved ISCB member, Teresa Attwood continued to further bioinformatics education on behalf of the global bioinformatics community and ISCB through many years of service. In 2001 she joined Phil Bourne’s ISCB Education Working Group to define the topic areas in a complete bioinformatics curriculum and identify the available learning resources. This group was the precursor of the creation of the ISCB Education Committee (2002).

Attwood was instrumental in launching the Global Organization for Bioinformatics Learning, Education and Training (GOBLET, 2012) as a network of global training organizations and individuals. Understanding the need to link GOBLET with ISCB, Terri worked with Fran Lewitter on the ISCB Education Committee Leadership Task Force (Summer 2016) to align the missions of GOBLET with those of ISCB and the emerging Education COSI, thereby ensuring the two organizations work in harmony towards their respective goals.

Teresa Attwood is being recognized for her many years of significant contributions to both ISCB and the broad bioinformatics and bio-curation communities.

 

ISCB will present the Accomplishments by a Senior Scientist Award, Overton Prize, Innovator Award and Outstanding Contributions to ISCB Award, at ISMB/ECCB 2021 (https://www.iscb.org/ismbeccb2021), which will take place in virtually, July 26-30, 2021.

Full bibliographical articles profiling the award recipients will be available in the ISMB/ECCB 2021 focus issue of the ISCB newsletter later this year, as well as the ISCB Society Pages in OUP Bioinformatics, and F1000 Research ISCB Community Journal.

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Ben Raphael, PhD, Professor, Department of Computer Science, Lewis-Sigler Institute, Princeton University, New Jersey, United States - Recipient of ISCB Innovator Award
2021 ISCB Innovator Award:
Ben Raphael, PhD

2021 ISCB Innovator Award:  Ben Raphael, PhD


Ben Raphael, PhD, Professor, Department of Computer Science, Lewis-Sigler Institute, Princeton University, New Jersey, United States

The year 2016 marked the launch of the ISCB Innovator Award, which is given to a leading scientist who is within two decades of receiving the PhD degree, has consistently made outstanding contributions to the field, and continues to forge new directions. Ben Raphael is the 2021 recipient of the ISCB Innovator Award.

Ben Raphael received an S.B. in Mathematics from MIT, a Ph.D. in Mathematics from the University of California, San Diego (UCSD), and completed postdoctoral training in Bioinformatics and Computer Science at UCSD.

Ben Raphael is a Professor of Computer Science at Princeton University. His research focuses on the design of combinatorial and statistical algorithms for the interpretation of biological data. Recent areas of emphasis include cancer evolution, network/pathway analysis of genetic variants, and structural variation in human and cancer genomes.

His group’s algorithms have been used in multiple projects from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC). He co-led the TCGA Pancreatic Adenocarcinoma project and the network analysis in the ICGC Pan-Cancer Analysis of Whole Genomes (PCAWG).

Ben is considered by many to be the leader in algorithmic computational cancer biology. He is the recipient of the Alfred P. Sloan Research Fellowship, the NSF CAREER award, and a Career Award at the Scientific Interface from the Burroughs Wellcome Fund. His papers cover a range of topics in computational cancer biology. These include the problems of separating genomic mixtures of cancer cells according to the mutations present in their genomes; analyzing temporal progression of mutations in cancer; identifying recurrent copy number aberrations; and discovering important sets of mutations across cohorts of cancer patients according to a statistical signal of anti-correlation, or mutual exclusivity, between mutations in the set. Several of Ben’s algorithms -- including his THetA and AncesTree algorithms for analyzing mixtures of cancer cells, his Dendrix and Multi-Dendrix algorithms for analyzing mutually exclusive mutations, and his HotNet algorithm (RECOMB 2010, Nature Genetics 2015) for network analysis of cancer mutations -- have become standards by which other research groups benchmark their algorithms. Ben’s computational approach to discover important cancer mutations using mutual exclusivity has inspired many other groups to work on this problem.
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ISCB will present the Accomplishments by a Senior Scientist Award, Overton Prize, Innovator Award and Outstanding Contributions to ISCB Award, at ISMB/ECCB 2021 (https://www.iscb.org/ismbeccb2021), which will take place in virtually, July 26-30, 2021.

Full bibliographical articles profiling the award recipients will be available in the ISMB/ECCB 2021 focus issue of the ISCB newsletter later this year, as well as the ISCB Society Pages in OUP Bioinformatics, and F1000 Research ISCB Community Journal.

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Peer Bork, PhD Director, EMBL Heidelberg (Scientific Activities), Germany- Recipient of ISCB Accomplishments by a Senior Scientist Award
2021 ISCB Accomplishments
by a Senior Scientist Award:
Peer Bork, PhD

2021 ISCB Accomplishments by a Senior Scientist Award: Peer Bork, PhD


Peer Bork, PhD, Director, EMBL Heidelberg (Scientific Activities), Germany

The Accomplishments by a Senior Scientist Award recognizes a member of the computational biology community who is more than two decades post-degree and has made major contributions to the field of computational biology. Peer Bork is being honored as the 2021 recipient of this award.­­

Peer Bork has been at EMBL since 1991, head of Units since 2001; the current strategic head of Bioinformatics at EMBL Heidelberg since 2011 and an ERC Advanced Investigator. Bork received his PhD in biochemistry in 1990 and his habilitation in theoretical biophysics in 1995.

His group, the Bork group, focus on gaining insights into the functioning of biological systems and their evolution by comparative analysis and integration of complex molecular data. Together with other groups at EMBL, they hope to establish interaction maps between chemical compounds and microbes, individually and in communities using advanced multi-omics approaches, with application for human (e.g. individualized diet) or planetary health (e.g. pesticide response biomarkers).

Peer Bork has made tremendous contributions to bioinformatics on a plethora of fronts within the field. This includes his early work on protein domains (leading to the SMART database), genome analysis of higher eukaryotes (leading to authorships on the human, mouse, and rat genome papers), work on one of the most used methods for analysis of mutation data (PolyPhen), large-scale phylogeny (leading to iToL), inventing several of the method for inferring gene/protein networks (leading to the STRING database), analysis of drugs and adverse reactions (leading to STITCH and SIDER) and most recently pioneering microbiome research.

In addition to the research as evidenced in his impressive list of over 590 publications, he has had immense impact also as a mentor. The majority of his many postdocs over the years have moved on to become successful group leaders themselves.


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ISCB will present the Accomplishments by a Senior Scientist Award, Overton Prize, Innovator Award and Outstanding Contributions to ISCB Award, at ISMB/ECCB 2021 (https://www.iscb.org/ismbeccb2021), which will take place in virtually, July 26-30, 2021.

Full bibliographical articles profiling the award recipients will be available in the ISMB/ECCB 2021 focus issue of the ISCB newsletter later this year, as well as the ISCB Society Pages in OUP Bioinformatics, and F1000 Research ISCB Community Journal.

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Barbara Engelhardt, PhD, Associate Professor at Princeton University, New Jersey, United States - Recipient of the ISCB Overton Prize

2021 Overton Prize Winner:
Barbara Engelhardt, PhD

2021 ISCB Overton Prize: Barbara Engelhardt, PhD

Barbara Engelhardt, PhD, Associate Professor at Princeton University, New Jersey, United States

The Overton Prize recognizes the research, education, and service accomplishments of early to mid-career scientists who are emerging leaders in computational biology and bioinformatics. The Overton Prize was instituted in 2001 to honor the untimely loss of G. Christian Overton, a leading bioinformatics researcher and a founding member of the ISCB Board of Directors. Barbara Engelhardt is being recognized as the 2021 recipient of the Overton Prize.
 
Barbara Engelhardt joined the Princeton Computer Science Department in 2014 from Duke University, where she had been an assistant professor in Biostatistics and Bioinformatics and Statistical Sciences.  She graduated from Stanford University and received her Ph.D. from the University of California, Berkeley.

Barbara Engelhardt’s research is in developing statistical models and machine learning methods for the analysis of biomedical data, with a focus on studying complex associations, time-series, sequential decision-making, and predicting the effects of perturbations in human cohorts, single cell data, and hospital patient data. In the field of single cell genomics, dimension reduction is a pressing problem and she has contributed a scalable and robust approach to dimension reduction using a Gaussian process latent variable model (GPLVM) with t-distributed residuals. Her group also developed approaches to determine the specific set of genes that differentiate particular types of cellular pathology images using machine learning methods like convolutional autoencoders and sparse canonical correlation analysis. Her research has a reputation for producing rigorous and creative statistical approaches for the analysis of complex biomedical data.

As part of the Genotype-Tissue Expression (GTEx) Consortium, Dr. Engelhardt performed key analyses to identify regulatory DNA variation that is linked to distal gene expression changes (“trans-eQTLs”). In the context of this large scale experimental effort, she determined trans-eQTLs across 49 human tissues and 838 individuals. Notable results include a confirmation of the greater tissue specificity of trans-eQTL versus mutations that are nearby the gene they regulate. Based on her expertise and creativity she has contributed numerous novel machine learning and statistics methods to important projects from genomics, population genetics, and human genetics.
 
Barbara Engelhardt has been an outspoken advocate for women and under-represented groups in the sciences. She has used her voice to advocate on behalf of these groups both through traditional means and on social media. Notably, Dr. Engelhardt's research group, housed in a computer science department, currently includes five women graduate students and postdocs and she has served as a mentor, both formally and informally for many women and individuals from under-represented groups, proving Dr. Engelhardt's status as a leader in the field of computational biology and bioinformatics.

 

ISCB will present the Accomplishments by a Senior Scientist Award, Overton Prize, Innovator Award and Outstanding Contributions to ISCB Award, at ISMB/ECCB 2021 (https://www.iscb.org/ismbeccb2021), which will take place in virtually, July 26-30, 2021.

Full bibliographical articles profiling the award recipients will be available in the ISMB/ECCB 2021 focus issue of the ISCB newsletter later this year, as well as the ISCB Society Pages in OUP Bioinformatics, and F1000 Research ISCB Community Journal.

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Xiaole Shirley Liu, PhD, Dana-Farber Cancer Institute, 2020 Recipient of ISCB Innovator Award

2020 ISCB Innovator Award
Xiaole Shirley Liu, PhD

2020 ISCB Innovator Award: Xiaole Shirley Liu, PhD


From Basic Genomics to the Cancer Moonshot

Xiaole Shirley Liu, PhD
, Professor, Biostatistics, Harvard T.H. Chan School of Public Health; Co-director, Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute

X. Shirley Liu grew up in Tianjin, China and her elder brother sparked her interest in biology at an early age. She transferred from Peking University during her freshman year to pursue her undergraduate degree at Smith College in the United States. Liu was working towards a degree in biochemistry when she took a basic computer literacy course. From that class, Liu became drawn to computer programming and quickly immersed herself in computer science courses in her junior year. In summer 1996 , she had a transformative experience, she recalled, “ At the recommendations of my advisors Jeanne Powell and Steven Williams, I went to a University of Washington summer workshop in bioengineering and visited several universities in the West Coast. The visit to Stanford helped me realize how I could combine computer science and biology.” Liu graduated summa com laude from Smith College in 1997 with a double major in biochemistry and computer science. She pursued a Ph D in the nascent f ield of biomedical informatics, with a minor in computer science, at Stanford University. At the time, Pat Brown and Ron Davis’ laboratories developed DNA microarrays to study gene expression, transcription regulation, and protein- DNA interactions. Under the guidance of her PhD advisors Douglas Brutlag and Jun Liu, she developed algorithms for finding protein- DNA binding motifs ( Bio Prospector, MDscan, and Motif Regressor) from co- expressed gene clusters and chromatin-immunoprecipitation microarrays (Ch IP- chip).

Liu accepted a faculty position right after PhD and became an assistant professor in the Department of Biostatistics and Computational Biology in the Dana- Farber Cancer Institute/ Harvard School of Public Health in 2003 . She recalled, “I was very lucky to collaborate with many wonderful colleagues at Harvard, especially with Myles Brown early in my faculty career. We share research interests in gene regulation and both believe the power of technology. Myles showed me how to use technologies cost effectively to tackle interesting biological problems, how to be open- minded when data lead us to unexpected results, and how to understand the mechanisms underlying our observations.” They developed numerous algorithms and tools (MAT, MACS, Cistrome, LISA, and MAESTRO) to model transcription factor binding and chromatin dynamics that are important to understand gene regulation in development and diseases. Liu and Brown continue to be close collaborators and have published around 70 papers together. As a member of the ENCODE consortium, Shirley Liu's Lab continued to maintain and update these algorithms and tools, which have helped many other scientists adopt new genomics technologies and generate hypotheses.

Liu became drawn to translational cancer research in 2012 after reading the Pulitzer Prize winning book, The Emperor of All Maladies, by Siddhartha Mukherjee. She had just been tenured and wanted to broaden her research areas and take more risks in her projects. Liu developed new methods (MAGe CK) to design and analyze genome- wide CRISPR/ Cas 9 knockout screens. Her team used computational approaches integrating large- scale compound and genetic screens, as well as functional genomics profiles from cancer cell lines and tumor cohorts, to refine our understanding of hormone receptor therapies, epigenetic inhibitors, gamma secretase inhibitors, receptor tyrosine kinase inhibitors, and immune checkpoint inhibitors in different cancers. She also developed novel algorithms TIMER and TRUST to comprehensively characterize tumor- infiltrating immune cells and immune receptor repertoires in over 10,000 tumors from The Cancer Genome Atlas. Liu continues to make significant contributions to cancer gene regulation. Liu is the principal investigator of the Cancer Immunologic Data Commons, a part of the NCI Cancer Moonshot project that aims to develop better cancer immunotherapy biomarkers and optimize treatment strategies.

Liu considers her role as a mentor to be a critical part of her job. She said, “I want trainees to explore projects that build on their interests and previous expertise and combine that with my lab’s knowledge on gene regulation. This helps each  trainee to develop a unique identity.” She has already mentored 18 trainees who have moved on to tenure track faculty positions and continues to welcome a diverse array of trainees with computational and experimental expertise.

Liu is a highly cited researcher with a prodigious publication record that includes more than 200 papers published by her group, many of them in high- profile journals and highly cited. Liu has served on the editorial boards of leading genomic and computational biology journals throughout her career.

She has also served on a number of conference organizing committees and study sections. She received the Sloan Research Fellowship (2008), has been a Breast Cancer Research Foundation Investigator (2017) , and became a Fellow of ISCB (2019). Liu’ s open access resources were recognized with the Benjamin Franklin Award for Open Access in the Life Sciences in 2020 .

Liu feels deeply honored to be recognized with the ISCB Innovator Award, especially as it comes from her peers in computational biology. She is inspired to continue pursuing projects that advance our understanding of basic biology and can be translated into clinical benefits to cancer patients.

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ISCB will present the Accomplishments by a Senior Scientist Award, Overton Prize, Innovator Award and Outstanding Contributions to ISCB Award, at ISMB 2020 (www.iscb.org/ismb2020), which will take place in Montreal, Quebec, Canada, July 12-16, 2020 where, in addition, Peng, Liu, and Salzberg will present keynote addresses during the conference.

Full bibliographical articles profiling the award recipients will be available in the ISMB 2020 focus issue of the ISCB newsletter later this year, as well as the ISCB Society Pages in OUP Bioinformatics, and F1000 Research ISCB Community Journal.

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Judith Blake, PhD, The Jackson Laboratory, 2020 Recipient of the ISCB Outstanding Contributions Award

Outstanding Contributions
to ISCB Award
Judith Blake, PhD

2020 Outstanding Contributions Award: Judith Blake, PhD


Judith Blake, PhD, Professor, The Jackson Laboratory

Science and Service Intertwined

Judith Blake has spent most of her career at the Jackson Laboratory in Bar Harbor, ME developing bioinformatics systems for integrating genetic, genomic, and phenotypic information and working to make data from different genomes more accessible for genomics and genetics research. Early in Blake’ s career at the Jackson Laboratory, she became a principal investigator with the Mouse Genome Informatics (MGI) project, a widely used international open access database resource for the laboratory mouse, providing integrated genetic, genomic, and biological data to facilitate the study of human health and disease. Blake’ s work on the MGI led to her interest in bio-ontologies. During the 1998 ISMB meeting, she and other colleagues working on genome projects in different model organisms recognized a need for open access bio-ontologies, which are controlled structured vocabularies for molecular biology that support the comparison of data across different genomes. She is one of the founding principal investigators and one of current leaders of the Gene Ontology (GO) Consortium group. Together with her research team, she has spent many years contributing to development of bio- ontology systems and to supporting integration of functional genomics data for mouse, in particular, within MGI and the GO project.

Beyond Blake’ s contributions to the bioinformatics and data curation communities, she has served ISCB in many ways.

She recalls attending the first ISMB meeting at the National Library of Medicine in Bethesda, MD in 1993, which led to the eventual formation of ISCB. Blake said, “Here I found a community of investigators actively engaged in creating new tools and approaches to computational scientific investigations. My colleagues in ISCB shared my excitement as new innovations were developed to understand molecular systems and data.” She has come to appreciate how ISCB brings together scientists from academia, industry, and technology in an open and supportive environment that fosters the building of new tools to advance the understanding of biological systems. Blake has served on the ISCB Board of Directors and chaired the ISCB Public Affairs and Policy committee, as well as working on other program and review committees. She has also represented ISCB on the Federation of American Societies for Experimental Biology (FASEB) Board of Directors.

Blake sees many benefits in pursuing scientific service opportunities and said, “I encourage young scientists and trainees to engage in those ISCB activities that match their passions. The opportunity to support their colleagues and to engage in a scientific network will both enhance the interactions of a global network of scientists but will also bring new insights to their own scientific investigations.”
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ISCB will present the Accomplishments by a Senior Scientist Award, Overton Prize, Innovator Award and Outstanding Contributions to ISCB Award, at ISMB 2020 (www.iscb.org/ismb2020), which will take place in Montreal, Quebec, Canada, July 12-16, 2020 where, in addition, Peng, Liu, and Salzberg will present keynote addresses during the conference.

Full bibliographical articles profiling the award recipients will be available in the ISMB 2020 focus issue of the ISCB newsletter later this year, as well as the ISCB Society Pages in OUP Bioinformatics, and F1000 Research ISCB Community Journal.

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Jian Peng, PhD,  University of Illinois at Urbana-Champaign, 2020 Recipient of the ISCB Overton Prize

2020 Overton Prize Winner:
Jian Peng, PhD

2020 ISCB Overton Prize: Jian Peng, PhD

Jian Peng, PhD, Assistant Professor, Department of Computer Science, College of Medicine (by courtesy), Institute of Genomic Biology (affiliate)
Cancer Center at Illinois (affiliate), National Center of Supercomputing and Applications (affiliate), University of Illinois at Urbana-Champaign

A Lifelong Love of the Sequence- Structure- Function Relationship

Jian Peng grew up in Yichang, Hubei Province, China to parents who were both university professors.  His earliest memories include taking pleasure in his t time spent reading from his parents’ home l library, even when he could not fully comprehend the content of some the books. He recalled, “My parents were college professors, who always gave me the freedom to choose what I Iiked to do.” Peng was 10 years old when his parents gave him his first personal computer. and he was quickly drawn to computer programming. He spent many hours teaching himself to program and read programming books on C/ C++, Windows, and data structures. In high school, Peng became interested in chemistry, but he returned to his early interest in computer programming while pursuing his bachelor’ s and master’ s degrees in computer science at Wuhan University. As an undergraduate, Peng became deeply interested in mathematical logic and i ts applications to programming languages and wanted to pursue this topic in graduate school. He said, “ I didn’t find many places to study this topic. I was fortunate to meet with Professor Jinbo Xu, who was giving a bioinformatics talk at Tsinghua University and kindly showed me several fascinating papers, including his seminal work on the protein side chain packing problem.  He suggested that I spend time reading textbooks on machine learning (ML), as he believed that ML would become a very useful tool in computational biology when more data become available.”

Peng went on to complete his PhD in 2013 at the Toyota Technological Institute at Chicago under Xu, where his research focused on protein structure prediction and modeling using ML methods. These methods, which are known as Raptor X and are still widely used today, have excelled at alignments of hard targets. Peng then joined Bonnie Berger’ s lab as a postdoc and expanded his research scope to include systems biology and functional genomics.

He recalled, “We have had a great time working on a variety of problems, including structural bioinformatics, compressive genomics, systems biology, and disease genomics. I also really appreciated my time in the lab of (the late) Susan Lindquist, where I learned a lot from experimental and wet lab biologists and found ways to help address important problems in neurodegenerative diseases using my computational skills.” He is deeply appreciative of his mentorship under Xu, Berger, and Lindquist not just for the areas of research he worked on with them but also for the lessons he learned in conducting experiments correctly and with rigor.

In 2015 , Peng was appointed as an assistant professor in the Department of Computer Science, and affiliated with the College of Medicine, at the University of Illinois at Urbana-Champaign. Peng's perspective in identifying new research topics has evolved with his maturation as an academic. As a student, he was more drawn to problems that he thought were highly interesting, or he was swayed by the “coolness” of a method. Now Peng appreciates that his research interests must also address important scientific problems, and he feels i t is critical to convey this concept to his trainees as they apply their knowledge in computation and biology to solve problems that deeply interest them.

Through his research experiences, Peng has learned that scientists are often surprised by unexpected findings. He said, “ What I’ve learned in these years from successes and failures is how capable (and incapable) computational methods can be. Like many artificial intelligence/ ML researchers, I was initially focused on developing powerful ML models for problems with large datasets, which hopefully can provide us new biological insights. However, in many important problems, such as those related to protein function and design, disease mutations studies, and functional genomics, the effective sample sizes are much smaller than what we expect for ML.”  Peng's research has always been driven by understanding the sequence- structure- function relationship. Currently, Peng’s research has shifted directions towards using biological insights for developing advanced machine learning models. Like Bayesian methods, he uses known biological insights to serve as the “structural” prior to constrain ML models and generate new hypotheses in line with existing knowledge. Two recent notable projects in this line are the Deep Contact algorithm for protein contact map prediction and the Mashup algorithm (with Berger and Cho) for heterogeneous biological network data integration.

He is interested in understanding the functional and structural consequences of protein mutations. Peng appreciates the importance of this area in terms of designing proteins with better and more biologically relevant functions, but also improving the annotation of missense mutations in human genomes for gaining insights in molecular mechanisms of human diseases.

Peng is greatly humbled and honored to receive the 2020 ISCB Overton Prize as it is a recognition from his peers within the ISCB community, and he shares his gratitude with the mentors, students and collaborators that have brought his work to fruition.
 

ISCB will present the Accomplishments by a Senior Scientist Award, Overton Prize, Innovator Award and Outstanding Contributions to ISCB Award, at ISMB 2020 (www.iscb.org/ismb2020), which will take place in Montreal, Quebec, Canada, July 12-16, 2020 where, in addition, Peng, Liu, and Salzberg will present keynote addresses during the conference.

Full bibliographical articles profiling the award recipients will be available in the ISMB 2020 focus issue of the ISCB newsletter later this year, as well as the ISCB Society Pages in OUP Bioinformatics, and F1000 Research ISCB Community Journal.

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Steven L. Salzberg, PhD -  Johns Hopkins University School of Medicine, 2020 Recipient of ISCB Accomplishments by a Senior Scientist Award

2020 ISCB Accomplishments
by a Senior Scientist Award:
Steven L. Salzberg, PhD

2020 ISCB Accomplishments by a Senior Scientist Award: Steven L. Salzberg, PhD


Steven L. Salzberg, PhD, Bloomberg Distinguished Professor, Professor of Biomedical Engineering, Computer Science, and Biostatistics; Director, Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine

A Journey between Industry and Academia

Steven Salzberg grew up in Columbia, SC.

Throughout his childhood and young adulthood, he was always interested in science and deeply enjoyed reading science fiction. Salzberg was also fascinated by astronomy and considered studying physics. As an undergraduate at Yale University in the 1970's, he explored several majors and thought he had settled on English Literature but added Computer Science as a second major upon taking an introductory computer programming class. He recalled, “ This is the kind of math I thought I would really like to study,” and he was soon captivated by artificial intelligence (AI) and natural language processing. At the advice of his undergraduate advisor, Salzberg spent a year after graduation gaining more programming experience by working at a local power company in South Carolina, where he worked on an IBM mainframe and used self- t raining courses to learn COBOL and IBM assembler. Salzberg said,  "It was a very boring sort of application, but I was still interested in programming. I liked the idea I could work on something technical, and within a short period of time, I would have results that would do what I intended.”

Salzberg returned to Yale and completed his M.S. in computer science. He then joined a startup in Boston during the first blush of AI, although this and many other AI startups failed in the late 1980's due to lack of computing power and other technical limitations.

One of Salzberg’s advisors at the startup was AI pioneer Bill Woods, who held an adjunct appointment at Harvard University and later became Salzberg’s graduate advisor in the Department of Computer Science. Salzberg had managed to avoid taking any biology classes as an undergraduate, but he heard about the Human Genome Project (HGP) while he was in graduate school in the late 1980's. He said, “The Human Genome Project sounded like the most exciting thing in all of science at the time, and I wanted to be a part of that.” While completing his PhD project in machine learning, he started sitting in on biology classes, including a course by the late Stephen Jay Gould, and reading on his own to learn about genomics and genetics. He was determined to figure out a way to using his computing knowledge to get involved in the HGP.

Salzburg continued doing research in machine learning as he started in his first academic position at Johns Hopkins University. He was still curious about genomics and recalled going to a talk in the early 1990's by Temple Smith about sequence differences between exons and introns. It dawned on Salzberg that he could use machine learning to distinguish exons from introns, which could be used as a strategy for gene finding. This became Salzberg’s entrance into genomics.

During this time, Salzberg was also introduced to Nobel Laureate Hamilton Smith, a notable microbiologist who discovered type I I restriction enzymes. Salzberg recalled, “[Smith] had a secret passion for computer programming. He wanted to talk to computer scientists who were interested in genomics -- that was me. And I was interested in learning more about genomics.” Salzberg and Smith began working together to understand how computer programs could be made for tasks like gene  finding. Smith had also started collaborating with J. Craig Venter, and in 1997, both Smith and Salzberg began working at Venter’s non-profit research institute, The Institute for Genomic Research (TIGR).

Salzberg became the Director of Bioinformatics at TIGR and developed with his colleague Art Delcher the GLIMMER gene finder, a software system still used today to identify coding regions in bacteria, archaea and viruses. In the early 2000's, the first Mycobacterium tuberculosis genomes were being sequenced by both TIGR and The Sanger Center. This led Salzberg and his colleagues to develop MUMmer, a system that could be used to compare large genomes. He also got involved in the HGP through the development of a gene finder that could analyze the human genome and, with his colleague Mihaela Pertea, also built other eukaryotic gene finders for plant, fungus, and parasite genomes. Salzberg and his colleagues were called upon by the FBI after the 2001 anthrax attacks to analyze the genome of the anthrax bacteria, and that work identified genetic mutations that eventually pinpointed the source of the bacteria to a biodefense lab in Fort Detrick, Maryland. In 2003, Salzberg co-founded the Influenza Genome Sequencing project with David Lipman, which involved the sequencing and analysis of thousands of influenza isolates.

Salzberg then moved to the University of Maryland, College Park in 2005 , where he was the Horvitz Professor of Computer Science. He returned to JHU in 2011 , where he is currently the Bloomberg Distinguished Professor of Biomedical Engineering,

Computer Science, and Biostatistics and the Director of the Center for Computational Biology in the Whiting School of Engineering. As next- generation sequencing ( NGS) technology developed, Salzberg’s research interests shifted toward developing algorithms for large- scale genome assembly and sequence alignment, including the development of the open- source Tuxedo suite of programs (Bowtie, Tophat and Cufflinks).

Salzberg’s current interests include the development of an improved human gene catalog and assembly and annotation of an Ashkenazi human reference genome. Recent technical advances have made this undertaking feasible, and the research community has desperately needed other reference genomes beyond the only publicly available genome, GRCh 38 . Salzberg is also working with colleagues on developing methods for using shotgun sequencing as a diagnostic tool for infectious diseases. They have tested their techniques on biopsy materials from patients with difficult-to-diagnose brain infections and on samples collected from eye infections, and the technology has the potential to work on a much broad range of infections.

Salzberg has trained numerous students and postdoctoral fellows throughout his time in academia and at TIGR, and he has focused on matching highly motivated individuals with projects that get them excited. Like many computational biologists, Salzberg is continually in search of interesting data associated with problems that matter, whether they involve the nature of the human genome, human health and disease, or any of a much broader range of microbial, plant, and animal genomes. Salzberg’s body of work includes more than 300 publications, including many highly cited manuscripts. His contributions have been recognized through his election as a member of the American Academy of Arts and Sciences, a Fellow of the American Association for the Advancement of Science (AAAS), a Fellow of the International Society for Computational Biology (ISCB), and a member of the Board of Scientific Counselors of the National Library of Medicine at NIH. All of Salzberg’ s bioinformatics systems have been released as free, open-source software, and he won the 2013 Benjamin Franklin Award for Open Science for his advocacy of open- source software and of open sharing of genome sequence data. Salzberg is also a contributor to Forbes magazine and writes a widely read column that debunks pseudoscience and explains scientific and medical findings with honesty and clarity.

Salzberg is greatly honored to be the 2020 recipient of ISCB’ s Accomplishments by a Senior Scientist award. He has always felt at home at ISMB meetings since their inception and is touched by this award since it is bestowed upon him by his computational biology colleagues.
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ISCB will present the Accomplishments by a Senior Scientist Award, Overton Prize, Innovator Award and Outstanding Contributions to ISCB Award, at ISMB 2020 (www.iscb.org/ismb2020), which will take place in Montreal, Quebec, Canada, July 12-16, 2020 where, in addition, Peng, Liu, and Salzberg will present keynote addresses during the conference.

Full bibliographical articles profiling the award recipients will be available in the ISMB 2020 focus issue of the ISCB newsletter later this year, as well as the ISCB Society Pages in OUP Bioinformatics, and F1000 Research ISCB Community Journal.

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2019 ISCB Art in Science Competition


Disassembled Tessellation - Dr. Kliment Olechnovic, Department of Bioinformatics, Life Sciences Center, Vilnius University, Lithuania
 

Dr. Kliment Olechnovic
Department of Bioinformatics, Life Sciences Center
Vilnius University
Lithuania

Disassembled Tessellation