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Keynote Speakers


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Ana Amador
Søren Brunak
Emilio Kropff
Ruth Nussinov
Sean I. O’Donoghue

Ana Amador, PhD Ana Amador, PhD
Dept. of Physics
University of Buenos Aires and IFIBA
National Research Council (CONICET)
Buenos Aires, Argentina

> Click here for biography <

Birdsong to study neural control and biomechanics in a learned sensorimotor task

Birdsong is a complex motor activity that emerges from the interaction between the peripheral system, the central nervous system and the environment. The similarities to human speech, both in production and learning, have positioned songbirds as unique animal models for studying this learned motor skill.

In this talk I will present a low dimensional dynamical system model of the vocal apparatus in which inputs could be related to physiological variables, being the output a synthetic song (SYN) that is a copy of the recorded birdsong (BOS). To go beyond sound comparison, we measured neural activity highly tuned to BOS and found that the patterns of response to BOS and SYN were remarkable similar. This work allowed to relate motor gestures and neural activity, making specific predictions on the timing of the neural activity. To study the dynamical emergence of this feature, we developed a neural model in which the variables were the average activities of different neural populations within the nuclei of the song system. This model was capable of reproducing the measured respiratory patterns and the specific timing of the neural activity. These results suggest that vocal production is controlled by a distributed recurrent network rather than by a top-down architecture.

Søren Brunak, PhD Søren Brunak, PhD
Professor, Research Director
Novo Nordisk Foundation Center for Protein Research
University of Copenhagen

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EMBO Lecture
Systematic Patterns in Millions of 20 Yearlong Individual Patient Disease Trajectories

Compared to the initial expectation human beings are gene-poor organisms. Many genes and pathways are likely to play a role in more than one disease, and numerous examples of gene pleiotropy and protein multi-functionality presumably await discovery. This situation contributes to the recent interest in clinical healthcare sector data and their accounts of fine-grained multi-morbidities. Patient record data remain a rather unexplored, but potentially rich data source for discovering correlations between diseases, drugs and genetic information in individual patients. A fundamental question in establishing biomarker-phenotype relationships is the basic definition of phenotypic categories. As an alternative to the conventional case-control, single disease model the talk will describe attempts to create phenotyoic categories and patient stratification based on longitudinal data covering long periods of time. We carry out temporal analysis of clinical data in a more life-course oriented fashion. We use data covering 6-7 million patients from Denmark collected over a 20 year period and use them to “condense” millions of individual trajectories into a smaller set of recurrent ones. This set of trajectories can be interpreted as re-defined phenotypes representing a temporal diseaseome as opposed to a static one computed from non-directional comorbidities only. A special case is represented by disease co-occurrences which are treatment provoked, e.g. adverse drug reactions. An important issue is to resolve whether specific adverse drug reactions relate to variation in the individual genome of a patient, to drug/environment cocktail effects, or both. From patient records ADR profiles of approved drugs can be constructed using drug-ADR networks, or alternatively patients can be stratified from their ADR profiles and compared. This type of work can potentially gain importance in projects involving population-wide genome sequencing in the future.

Emilio Kropff, PhD Emilio Kropff, PhD
Researcher at the National Research Council (CONICET)
Leloir Institute IIBBA
Buenos Aires, Argentina
Associate Researcher
Abdus Salam International Centre for Theoretical Physics (ICTP)
Triest, Italy

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Coding for running speed and computing displacement in the mammalian brain's GPS

The last decades have witnessed major discoveries concerning the brain mechanisms through which mammals compute their own location and orient in space. Hippocampal place cells provide maps that describe the position of the animal within a known environment, including a rich contextual description. Entorhinal grid cells provide instead a spatial map that is applied to all environments and is not altered by contextual variations. For this reason grid cells have been proposed to be the framework for an egocentric representation of location, where position is computed independently of contextual cues and based only on the animal's knowledge of its own movements. To achieve this, grid cells should receive information about orientation and speed of instantaneous movements. While neurons coding for the head orientation have been described in the entorhinal cortex, the entorhinal speed code has remained elusive for almost a decade. We present the Flintstone car, a new behavioral paradigm that allows the precise control of rat running speed. Using this device we have discovered a new functional entorhinal cell type: the speed cell. These neurons code for running speed in an instantaneous and linear way. The code is context-independent, allowing running speed to be decoded from the activity of a handful of speed cells even across environments. In addition, we found speed cells to be slightly ahead in time with respect to the actual running speed (~80 ms on average) and, consistently, we found grid cells to be ahead in time with respect to the actual position. Taken together, these observations point to entorhinal speed cells as a key component in the dynamic representation of self-location.

Ruth Nussinov, PhD Ruth Nussinov, PhD
Center for Cancer Research
National Cancer Institute
Maryland, United States

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A Mechanistic View of Oncogenic K-Ras Biology

Ras proteins are small GTPases that act as signal transducers between cell surface receptors and several intracellular signaling cascades. KRAS is among the most frequently mutated oncogenes in human tumors. Ras proteins consist of highly homologous catalytic domains, and flexible C-terminal hypervariable regions (HVRs) that differ significantly across Ras isoforms. We have been focusing on key mechanistic questions in oncogenic Ras biology from the structural and signaling standpoints. These include whether Ras’ disordered hypervariable region (HVR) has a role beyond membrane anchoring; Does Ras form dimers, and if so what is their structural landscape and how they help in activating Raf; What are Ras’ redundant pathways and importantly how to identify redundant pathways in cancer; What are the mechanisms of oncogenic mutations; Is RASSF5 - which links Ras and the MAPK pathway to the Hippo pathway - a tumor suppressor or activator as some experiments suggest, and what is the mechanism through which it works, and more. We believe that structural biology - computations and experiment – is uniquely able to tackle these fascinating and important questions.

Sean O’Donoghue, PhD Sean I. O’Donoghue, PhD
CSIRO & Garvan Institute of Medical Research
Sydney, Australia

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Data Visualization in Bioinformatics: Exploring the 'Dark' Proteome

The rapidly increasing volume and complexity of biological data calls for new approaches to help life scientists gain insight from these data, rather than being overwhelmed. To address this, the application of modern data visualization principles and methods will be critical, in combination with improved data management, machine learning, and statistics. I will illustrate the power of this 'BioVis' approach by presenting several bioinformatics resources that empower biologists by making complex data easier to access and use. This includes Aquaria (http://aquaria.ws), Minardo (http://minardo.org/snapshot), and Rondo (http://rondo.ws). I will showcase how these resources are being used to explore the known and unknown ('dark') proteome, generating new insights into human biology and health. I will also discuss VIZBI, an international initiative aimed at raising the global standard of bioinformatics software (http://vizbi.org/). Finally, I’ll discuss the use of visualization to create molecular and cellular-scale animations aimed at educating and inspiring the public about cutting-edge biomedical research (http://vizbi.org/plus).

  Ana Amador, PhD

Ana Amador is a research associate at CONICET (National Scientific and Technical Research Council, Argentina) and University of Buenos Aires, where she is also a teaching fellow (JTP). She received her B.Sc. and Ph.D. from the University of Buenos Aires (Argentina) in Physics, with intense interdisciplinary training components. Before finishing grad school, she took the course Neural Systems & Behavior at the Marine Biological Laboratory, Woods Hole (MA, USA), and other international courses at UCSD (USA) and ICTP, Trieste (Italy). Her Ph.D. research, under the supervision of Gabriel Mindlin, was focused on the biomechanics of birdsong, merging experimental work and mathematical modeling of the peripheral system. For her postdoc, she was awarded with the HFSPO cross-disciplinary fellowship (Human Frontier Science Program Organization) to work with Dan Margoliash at the Dept. of Organismal Biology & Anatomy, University of Chicago, USA. Since then, her line of research has been to integrate the central nervous system, the peripheral system and computational modeling in songbirds, an animal model for studying motor control and vocal learning.
  Søren Brunak, PhD

Søren Brunak, Ph.D., is professor of Disease Systems Biology at the University of Copenhagen and professor of Bioinformatics at the Technical University of Denmark. He is Research Director at the Novo Nordisk Foundation Center for Protein Research at the University of Copenhagen Medical School. He leads a research effort where molecular level systems biology data are combined with the analysis of phenotypic data from the healthcare sector, such as electronic patient records, registry information and biobank questionnaires. A major aim is to understand the network basis for comorbidities and discriminate between treatment related disease correlations and other comorbidities, thereby stratifying patients not only from their genotype, but also phenotypically based on the clinical descriptions in their medical records. Prof. Brunak started work within bioinformatics in the mid-1980ies, and was in 1993 the founding Director of the Center for Biological Sequence Analysis at DTU, which was formed as a multi-disciplinary research group of molecular biologists, biochemists, medical doctors, physicists, and computer scientists. The center offers a wide range of services at its web site, www.cbs.dtu.dk, including bioinformatics tools developed over the past 25 years.
  Emilio Kropff, PhD

Emilio Kropff graduated in Physics in the University of Buenos Aires, Argentina. He obtained his PhD in Cognitive Neuroscience at SISSA, Triest, Italy, working on computational models of memory function under the supervision of Alessandro Treves. For his postdoc he jumped to experimental work, studying entorhinal navigational circuits through in vivo electrophysiology recordings under the supervision of Edvard and May-Britt Moser (Nobel Prize awardees, 2014) in Trondheim, Norway. Back in Buenos Aires, he is focused on understanding the circuits that aid memory and navigation in the rodent brain through a multidisciplinary approach involving in vivo electrophysiology, optogenetics and computational models.
  Ruth Nussinov, PhD

Ruth Nussinov received her Ph.D. in 1977 from Rutgers University and did post-doctoral work in the Structural Chemistry Department of the Weizmann Institute.  Subsequently she was at the Chemistry Department at Berkeley, the Biochemistry Department at Harvard, and a visiting scientist at the NIH. In 1984 she joined the Department of Human Genetics, at the Medical School at Tel Aviv University. In 1985, she accepted a concurrent position at the National Cancer Institute of the NIH, Leidos Biomedical Research, where she is a Senior Principal Scientist and Principle Investigator heading the Computational Structural Biology Section at the NCI. She has authored over 500 scientific papers. She is the Editor-in-Chief in PLoS Computational Biology and Associate Editor and on the Editorial Boards of a number of journals. She is a frequent speaker in Domestic and International meetings, symposia and academic institutions, won several award and elected fellow of several societies. Her National Cancer Institute website gives further details. https://ccr.cancer.gov/ruth-nussinov.
  Seán I. O’Donoghue, PhD

Seán O’Donoghue (http://odonoghuelab.org/) is an Office of the Chief Executive Science Leader in Australia's Commonwealth Scientific and Industrial Research Organisation (CSIRO), Sydney. He is also Group Leader and Senior Faculty Member at the Garvan Institute of Medical Research in Sydney. He received his B.Sc. (Hons) and PhD in biophysics from the University of Sydney, Australia. Much of his career was spent in Heidelberg, Germany, where he worked in the Structural and Computational Biology programme at the European Molecular Biology Laboratory (EMBL), and also at Lion Bioscience AG - then the world's largest bioinformatics company - where he was Director of Scientific Visualization. His work has received many awards, including the Elsevier Grand Challenge (first prize), the Eureka Prize for Excellence in Interdisciplinary Scientific Research (finalist, 2015), the NSW Emerging Creative Talent Award (finalist, 2015), and the NSW iAward for Research and Development (first prize, 2015). His contributions have been recognised with a C. J. Martin Fellowship from the National Health & Medical Research Council of Australia, an Achievement Award from Lion Bioscience AG, and by being elected a Fellow of the Royal Society of Chemistry.