Applied Knowledge Exchange Sessions - Saturday, July 11
New for 2015! The Applied Knowledge Exchange Sessions provide interactive educational and knowledge exchange opportunities. These sessions will be held on Saturday July 11 and a participation fee applies. Registration details and fees will be posted March 23.
AKES 01: Applied Knowledge Building networks for translation: how to use DREAM challenges and the Synapse platform as a research strategy
Morning Breaks: 10:15 - 10:45
Afternoon Breaks: 3:30 - 4:00
Time: 8:30 am – 5:30 pm (includes 2 coffee breaks and lunch break
Room: Wicklow Meeting Room 4
This session will explain the rationale behind running a DREAM Challenge, the steps involved from both sides of the process (organizers and participants), the lessons learned, and the potential uses of DREAM Challenges in education. Hands-on exercises with the Synapse platform will be featured.
- Understand crowdsourcing in the form of challenges as a new approach to research
- Learn the ins and outs of planning, implementing and analyzing a DREAM Challenge
- Get familiar with Synapse, Sage’s platform we use to run DREAM challenges
- Get hands-on experience as an organizer and as a DREAM participant using a toy example
Dream Challenges Background
In the last ten years both academic and commercially organized crowdsourcing efforts, often called Competitions or Challenges (Read More), have been used to evaluate the validity and rigor of scientific studies while fostering open innovation. Challenges enable an unbiased, double-blinded assessment of methods. The aggregated community predictions are robust and usually more accurate than the best performing algorithms – an effect known as the wisdom of crowds. DREAM (Dialogue for Reverse Engineering Assessment and Methods) Challenges are collaborative competitions that engage diverse communities, including statistics, machine learning and computational biology, to competitively solve a specific problem in biomedicine in a fixed time period. DREAM was founded in 2006 by Gustavo Stolovitzky and Andrea Califano, and directed by Dr. Stolovitzky since then. DREAM’s distributed community of Challenge organizers has launched 32 successful Competitions, that have led to over 100 publications using DREAM data, 25 journal articles, 1 PLOS ONE collection, 2 edited books and over 1,300 citations. DREAM has attracted the participation of over 8,000 Challenge “solvers” and evolved as a powerful approach to democratize data and accelerate research.
Since 2013, DREAM has partnered with Sage Bionetworks, to co-lead a new generation of Challenges that feature complex and/or massive data sets, including clinical, genetic and imaging data, that are hosted on Synapse, Sage’s open computational platform
Tools to Define and Analyse Logical Models of Cellular Networks
where DREAM Challenges take place. Synapse allows reproducibility of the research process by providing a collaborative environment to share data, code, results, and the analysis provenance linking these research services to one another. Users can interact with these services through the Synapse web portal or analytical clients (R, python, and command line). Synapse offers features such as real-time leaderboards, provenance tracking and community forums to incentivize continuous participation and enable teams to build upon one another’s work to evolve improved predictive models. Synapse’s IRB-approved Challenge environment permits the hosting of sensitive human data for DREAM Challenges, fosters broader participation of the research community and makes the results of DREAM Challenges (models, description and source code) available as an ongoing resource for open research.
In this tutorial we will cover all aspects related to the planning and implementation of a DREAM Challenge. We will explain the diverse aspects involved in setting up a Challenge: how to secure and curate Challenge data sets, develop and evaluate the value and rigor of Challenge questions, plan for the opening and marketing of Challenges, as well as run, score, and analyze the final results. We will also describe how to participate in a DREAM Challenge and the use of DREAM Challenges for education. We will discuss which predictive approaches seem to work well, and which type of Challenges are particularly difficult to solve and why this might be so. All throughout the tutorial, we will discuss general principles, use previous Challenges as illustrative examples, and provide “toy-data” to produce hands-on exercises in challenge organisation and participation. Hands-on demonstrations will take place using Synapse.
Gustavo Stolovitzky, Distinguished Research Staff Member and Director of the Translational Systems Biology and Nano-Biotechnology Program IBM Research; Adjunct Professor, Columbia University and at the Icahn School of Medicine, Mount Sinai, United States
Dr. Stolovitzky joined IBM Research in 1998 after being a postdoctoral researcher at the Center for Studies in Physics and Biology at The Rockefeller University. He received his PhD in Mechanical Engineering from Yale University (1994) and his M.Sc. in Physics from the University of Buenos Aires (1987). Dr. Stolovitzky has received Yale University’s Henry Prentiss Becton Prize award (1994), the HENAAC’s Pioneer Award for Great Minds in STEM (2013), the World Technology Awards (2013), and Master Inventor in IBM Research (2013). Dr. Stolovitzky is a Fellow of the NY Academy of Sciences, of the World Technology Network, of the American Physical Society and of the American Association for the Advancement of Sciences.
Gustavo has led many industry projects at IBM Research including the development of single molecule DNA sequencing methods (DNA Transistor Project), and the use of crowd-sourcing to improve the quality of industrial research in systems biology (IMPROVER project). He is also heavily involved in academic research. He founded and leads the DREAM Challenges. He is a co-chair of the “RECOMB/ISCB Systems and Regulatory Genomics with DREAM Challenges” conference series. His research spans from the fields of high-throughput biological-data analysis, to reverse engineering biological circuits, the mathematical modeling of biological processes and nano-biotechnology.
Julio Saez-Rodriguez, Group Leader, European Bioinformatics Institute, European Molecular Biology Laboratory (EMBL-EBI)
Julio studied Chemical Engineering at the Universities of Oviedo and Stuttgart, and obtained his PhD at the University of Magdeburg and the Max-Planck-Institute with E. D. Gilles. After this, he was a postdoctoral fellow at Harvard Medical School with Peter Sorger and Doug Lauffenburger at M.I.T., and a Scientific Coordinator of the NIH-NIGMS Cell Decision Process Centre. Since 2010 he is a group leader at the European Bioinformatics Institute (EMBL-EBI) , with a joint appointment in the EMBL Genome Biology Unit in Heidelberg, as well as a senior fellow at Wolfson College (Cambridge). He is an affiliated member of Sage-Bionetworks and a co-organizer of the DREAM initiative to catalyze the development of methods in systems biology. His main research interest is to develop and apply computational methods to acquire a functional understanding of signaling networks and their deregulation in disease, and to apply this knowledge to develop novel therapeutics.
Pablo Meyer, Team Leader, Research Staff Member, IBM Research
Pablo Meyer received a degree in Physics from the Universidad Nacional Autonoma de Mexico, Univeriste Paris-VII and his PhD in Biology from Rockefeller University (2005) studying with live imaging the protein interactions in the Drosophila circadian clock. He studied at Columbia University the live-imaging of metabolism during sporulation in Bacillus Subtillis. In 2010 he joined the IBM Computational Biology center at IBM Research where he is a DREAM challenges director and finds himself in the intersection between modelling, data analysis and wet lab. His most recent interests are in enzyme distribution in the cell in and their link to Metabolism/Cancer via high-throughput biological-data analysis and development of new experimental techniques.
Thea Norman, Director, Strategic Development, Sage Bionetworks, United States
Dr. Norman works closely in partnership with Dr. Gustavo Stolovitzky of IBM to oversee the running of the Sage-DREAM Challenges. DREAM Challenges foster a collaborative framework for researchers to rapidly evolve predictive disease models for tough problems in biology and medicine that would otherwise take years to produce. Dr. Norman also oversees the design and development of Sage Bionetworks BRIDGE platform. Prior to joining Sage Bionetworks, Dr. Norman spent 12 years as a science, alliance and business leader at two start-up biotechnology companies (Ironwood and Ambrx). Dr. Norman is a co-inventor on seven issued patents including that for the composition of Linzess (which Dr. Norman developed), a First in Class treatment for Irritable Bowel Syndrome. Dr. Norman holds a PhD in Chemistry from the University of California, Berkeley.
Brian Bot, Senior Scientist and Community Manager, Sage Bionetworks, United States
Brian is with Sage, a not-for-profit organization dedicated to exploring open source models in the advancement of biomedical research in Seattle, Washington. Previously, Brian worked in the Department of Biomedical Statistics and Informatics at the Mayo Clinic for 7 years. He has extensive experience in working with clinical and genomic data and has a passion for exploring innovative ways to make science more open and transparent. Brian’s current work involves implementation of strategies and technologies for making complex high dimensional genomic analyses more accessible. At its heart, this work is driven to re-envision how scientists can ensure reproducibility of their research results and communicate complex genomic science to one another and to the public at large. Brian has been an invited speaker at a number of national and international events about his experience in making science more open and transparent.
Maximum Attendees: 40
- The session will include a practical component, doing hands-on exercises with Synapse. Please bring your own laptop to participate in the hands-on exercises.
- This introductory level requires no previous experience with Challenges or Synapse although experience with R/Python is useful
Time: 8:30 am - 5:30 pm (includes 2 coffee breaks and lunch break)
Room: Wicklow Meeting Room 5
Cytoscape's real power lies in the ecosystem of community-developed apps. The most common types of apps provide access to third-party biological databases, customize data import for domain-specific data sets, and perform custom analyses and workflows. Browse the full collection at http://apps.cytoscape.org. During this workshop, we will demonstrate how to develop apps for Cytoscape, targeting individuals who want to take advantage of the network visualization and analysis capabilities of Cytoscape and extend it for custom use cases.
By the end of this workshop, you should be able to:
- Navigate the complete Cytoscape API
- Setup an app development environment and cycle
- Start your own app development project from scratch
- Edit and contribute to other open source Cytoscape app projects
John "Scooter" Morris, University of California San Francisco, United States
John "Scooter" Morris is the Executive Director of the Resource for Biocomputing, Visualization, and Informatics and an Adjunct Assistant Professor in the department of Pharmaceutical Chemistry at the University of California, San Francisco. Before finding his home in academia, he was a Distinguished Systems Architect at Genentech, Inc., where for 19 years, he participated in the joys and trials of life in industry. He received his Ph.D. in Medical Information Science from UCSF in 1990, and has bachelors degrees in Physics, Biology, and Computer Science from UC Irvine. Scooter is a member of the Cytoscape core development team, and author of several Cytoscape plugins, apps, and core features. In his "spare time" he is the Vice President for Conferences of the ACM Special Interest Group for Computers and Human Interaction (SIGCHI) and he is known to voluntarily jump off perfectly good boats near Alcatraz Island for a brisk swim to shore.
Maximum Attendees: 20
Delegate Requirements: No previous experience required
Time: 8:30 am – 12:30 pm (includes 1 coffee break)
Room: Liffey Meeting Room 3
Bioinformatics is the application of computational, mathematical and statistical techniques to solve problems in biology and medicine. Arguably the main research focus has so far been on the computational and statistical basis of the algorithms. Surprisingly much less effort has been placed on the quality of the design and implementation of these algorithms - even though clearly correct design and implementation of the underlying algorithm is at least as important as the algorithm itself. Incorrectly computed results may lead to wrong biological conclusions, and subsequently misguide downstream experiments. This problem is especially critical if these bioinformatics tools are to be used in a translational clinical setting. For example, given a whole exome sequencing analysis pipeline for identification of sequence variants, one must have high confidence that the resulting variant calls have high sensitivity and specificity. Although true positives can be distinguished from false positives easily through external validation, it is almost impossible to systematically distinguish false negatives from the vast amount of true negatives.
By its very nature, many bioinformatics programs are developed to organise and to analyse large and complex biological datasets. Many of these programs involve (1) processing large amount of data, and (2) invoking complex processing procedures to extract useful information. In particular, due to the rapid accumulation of high-throughput datasets and the increasing focus on systems-level biological modelling, the size and complexity of bioinformatics programs are growing rapidly. This poses a great challenge in developing a good testing strategy to ensure the reliability of the design and implementation of bioinformatics algorithms. Software testing involves defining test objectives, selecting some inputs of the software under test as test cases, executing the software with these test cases, and verifying testing results. A good testing strategy should actively reveal as many faults as possible using a selected set of test cases. Practically many key questions remained unanswered: How to design good test cases? How many test cases should be used? Can we estimate the statistical confidence of the correctness of a given software pipeline? We believe introducing and adapting state-of-the-art software testing and statistical techniques in bioinformatics is a critical step in improving the quality, reproducibility, and accountability of bioinformatics tools.
In this workshop, we aim to create an environment to engage bioinformatics software developers, managers of bioinformatics/genomic core facilities, researchers in reliability engineering and statisticians. We hope that cross pollination of these fields would yield interesting new insight and ideas that would open new research avenue related to bioinformatics quality assurance.
Dr Joshua Ho (Victor Chang Cardiac Research Institute, Sydney, Australia)
Dr Eleni Giannoulatou (Victor Chang Cardiac Research Institute, Sydney, Australia)
Dr. Joshua Ho, University of New South Wales, Australia
Dr Joshua Ho is Head of Bioinformatics and Systems Medicine Laboratory at the Victor Chang Cardiac Research Institute and a conjoint senior lecturer at the University of New South Wales, Australia. He was previously an Instructor in Medicine in the Division of Genetics at the Brigham and Women's Hospital and the Harvard Medical School, USA. Besides his research expertise in epigenomics and systems biology, he has a longstanding interest in adopting state-of-the-art software testing techniques to bioinformatics (Chen et al. 2009; Xie et al. 2010; Giannoulatou et al. 2014).
Dr. Christopher Yau, University of Oxford, United Kingdom
Dr Christopher Yau is Group Leader in Genomic Medicine at the Wellcome Trust Centre for Human Genetics, University of Oxford. He was previously a Lecturer in Statistics at Imperial College London and a Medical Research Council Research Fellow in Statistics at the University of Oxford. His main contributions to genomics have been through the development of widely used statistical tools for identifying DNA copy number alterations from array- or sequencing-based studies of constitutional or cancer genomes. More recently with the Oxford Biomedical Research Centre, as part of a Wellcome Trust Healthcare Innovation Challenge Fund programme, he has contributed to the translation of these bioinformatics tools into actual clinical healthcare and practice.
Dr. Eleni Giannoulatou, University of New South Wales Australia
Dr Eleni Giannoulatou is the senior postdoctoral scientist at the Bioinformatics and Systems Medicine Lab at the Victor Chang Cardiac Research Institute and a conjoint lecturer at the University of New South Wales, Australia. She was previously a postdoctoral researcher at the Weatherall Institute of Molecular Medicine and the Wellcome Trust Centre for Human Genetics in Oxford. Her research focuses on the development and application of statistical methodologies for analysis of modern genomic datasets arising from sequencing, microarray and other high-throughput genomic technologies, with application to human genetics, genome function and evolution.
Dr. Ruth Clifford, University of Oxford, United Kingdom
Dr Ruth Clifford is a clinical research fellow in Dr Anna Schuh’s molecular genetics research group at the University of Oxford. She has a specific interest in chronic lymphocytic leukaemia and focuses on defining high-risk genomics to aid treatment selection for this patient group where she is developing whole genome sequencing approaches to identify treatment response predictors.
Maximum Attendees: 50
- Please bring your own laptop to participate in the hands-on exercises.
- No specific prior knowledge is required on the topic.
Time: 8:30 am – 12:30 pm (includes 1 coffee break)
Room: Wicklow Meeting Room 3
Approximately 30,000 clinical trials are run each year across the world. Different market and regulatory forces are driving initiatives to publicly share individual-level data from these clinical trials. In the broader realm of advancement of science and betterment of human condition, there are several purported benefits for the sharing of clinical trial data. The scientific community or lay public can independently verify the published results of a clinical trial. Non-availability of original research data is known to be a significant barrier towards reproducibility. There may even be opportunity to evaluate new hypotheses that were not originally formulated in the studies, either by extending the analysis of data from a clinical trial or by combining data from different clinical trials. Multi-modal measurements are generated for each participant through different stages of the clinical trial process: physical characteristics (e.g. weight, blood pressure), medical history, clinical laboratory results (e.g. hemoglobin levels), imaging results (e.g., MRI), results of mechanistic studies employing core technologies such as ELISA, microarrays, flow cytometry and next-generation sequencing. The enormity of raw individual-level clinical and high-throughput assay data provide a tremendous opportunity for bioinformaticians to advance science, and perhaps even foster new techniques in clinical informatics. In this workshop, we will discuss the reasons for data sharing and the issues surrounding it, the various ways sharing is implemented, and showcase our experience in re-analysis of clinical trials data using open immunology studies data. We will also highlight our initial work on defining a minimum information guideline for clinical trials data release.
The workshop will comprise of the following four sections:
- Responsible sharing of clinical trials data
Discuss the global forces that are driving initiatives to publicly share individual-level clinical trials data, major issues in data-sharing such as patient privacy concerns and intellectual property rights, and the purported benefits of data sharing.
- Landscape of data-sharing initiatives
Enumerate the data-sharing mechanisms that pharmaceutical companies, government institutions and private foundations have implemented, and discuss the different flavors of data access policies that these organizations are adopting. Briefly discuss recent data sharing initiatives such as clinicalstudydatarequest.com, yoda.yale.edu and projectdatasphere.org.
- Minimum information about a clinical trial
Highlight the clinical trial data elements that, in our perspective, should be part of the data that is being shared, in order to realize the very purposes of data sharing. Discuss our initiative towards minimum information about a clinical trial guideline.
- A use-case for sharing and re-use of clinical trials data
Introduce ImmPort that warehouses clinical trials data in all areas of immunology that is generated primarily by investigators funded by the US National Institute of Allergy and Infectious Diseases (NIAID). With nearly 100 datasets now publicly available and hundreds of downloads per month, ImmPort is an important source for raw data and protocols from clinical trials, mechanistic studies, and novel methods for cellular and molecular measurements. Showcase, via case-studies, how researchers have reused the meta-data from clinical trials to generate new hypothesis and gain biomedical insight across multiple clinical studies.
The participants of the workshop will
- understand the reasons for public sharing of clinical trials data, and the issues surrounding it.
- become familiar with different data sharing initiatives and policies implemented by pharmaceutical companies, government institutions and private foundations, and
- gain practical introduction to accessing and re-using open clinical trials data.
Atul J. Butte, Chief of the Division of Systems Medicine, Stanford University School of Medicine
Atul J. Butte has been an innovative proponent of data mining of publicly available data resources, for the discovery of novel genome-phenome relationships, and for the creation of genomic data-driven nosologies. He has served on the AMIA Board of Directors and launched the first AMIA Summit on Translational Bioinformatics in 2008. He has delivered a large number of invited Keynote/Plenary talks at international conferences, hosted workshops and served as session chair in ‘Big Data’ conferences.
Ravi Shanker, Research Scientist, Stanford University School of Medicine
Ravi Shankar is a research scientist at the Stanford University School of Medicine. In the 17 years at Stanford, he has worked in the areas of automated clinical guideline-based care, annotation standards for biomedical investigations, and clinical trial management. Currently, Ravi is member of the scientific team of ImmPort, and is research staff in Dr. Atul Butte’s lab. Ravi is exploring methods to disseminate open clinical trial data in order to support cross-analysis of clinical trials and integration of clinical trial data with other open biomedical datasets. He has lead workshops on modeling and disseminating clinical trials data.
Sanchita Bhattacharya, Lead Data Scientist for ImmPort, Senior Researcher Stanford University School of Medicine
Sanchita Bhattacharya is actively involved in the area of bioinformatics for last fifteen years doing collaborative research as a computational research scientist with biologists in academia. Her research interest includes immunoinformatics with expertise in integrative analyses of multi parameter measurements, coupled with knowledge in statistical modeling and molecular biology.
Max Participants: 40
- Participants will need to install a specific version of R and few R packages on their laptops – this will be provided in advance of the AKES session.
Time: 1:30 pm – 5:30 pm (includes 1 coffee)
Room: Wicklow Meeting Room 3
Cyberinfrastructure (CI) is a powerful enabler for data-intensive biology. Although much investigation originates in organism-centered communities there are unifying similarities across types of datasets, algorithms, and overall goals. Despite these commonalities, communities often split across domains as independently-developed tools, un-shareable datasets, and un-communicated experience results in isolation and needless redundancy. This workshop demonstrates how CI originally developed for the U.S. plant science community (via. the iPlant Collaborative project) serves all life sciences (animals, plants, microbes, etc.) by allowing communities to leverage pre-built CI solutions and develop application-specific components to a customized endpoint. More the discussing tools, broadly applicable skills and lessons learned will be emphasized along three themes:
Scaling Data: The lifecycle of data necessitates interdisciplinary collaborations and team science approaches spanning multiple departments, institutes, and even continents. We will demonstrate how the Data Store utilizes IRODS technology to make sharing of large biological datasets routine.
Scaling Compute: Web-accessible tools and application interfaces for data analysis and management leverage federated data and consumption of resources from multiple providers such as NSF funded XSEDE, campus clusters, and commercial clouds. Communities can access an array of tools and services, and extend the CI to accommodate specific needs.
Hands-on demos will cover:
1) Discovery Environment - Web based interface to bioinformatics application and HPC using RNA-Seq tutorials as an exemplar workflow;
2) Atmosphere Cloud Compute –overview of the Atmosphere cloud, demo data visualization applications, and developer resources;
3) Science APIs - Web-based Application Programming Interfaces (APIs) to support automation and integration of tools and services in other applications and third party platforms including authentication, job management, and developer toolkit.
Scaling People: People are by definition a component of cyberinfrastructure; A discussion with panelists from several bioinformatics-related projects will focus on educational applications of CI, best practices in training, how to develop self-sustaining training efforts (through training trainers), and how collaborating with efforts such as the Software Carpentry and Data Carpentry organizations accelerate user capabilities.
- Understand when and why biologist should leverage cyberinfrastructure to extract maximum value from datasets, and deliver reproducible work
- Learn how to manage the lifecycle of data (including generation, metadata management, sharing, and post-publication access)
- Understand why all levels of users can benefit from web-platforms for data management and analysis
- Understand to take advantage of cloud computing by recognizing its value and its limitations
- Learn how APIs allow users to fully customize how they consume computation
- Learn how developers can scale their users and their software
- Understand how and why effective training and community building makes bioinformatics projects more successful
- Learn how to develop effective training in bioinformatics
Jason Williams, Cold Spring Harbor Laboratory, New York, United States
Jason Williams is the iPlant’s Education, Outreach, and Training Lead – Based out of Cold Spring Harbor Laboratory, Jason’s background is in plant molecular biology. For iPlant, Jason organizes, manages, and instructs more than a dozen annual bioinformatics workshops, conferences, and other events. He has been instructional staff at Cold Spring Harbor Laboratory's DNA Learning Center for the past 5 years, and been research staff at Cold Spring Harbor Laboratory for 5 years prior to that. Jason is also faculty at Yeshiva University – running a science immersion course at Yeshiva University High School for Girls. Jason has collaborated with The Genome Analysis Centre (Norwich, UK) as advisor to their scientific training programs, and currently serves on the Steering Committee of the Software Carpentry Foundation as Treasurer.
John Fonner, Texas Advanced Computing Center, University of Texas, Austin, United States
John’s interest lay in applying new technologies, hardware, and paradigms to genomic and biological problems in a way that is accessible to the average bench biologist. His Ph.D. work was in Biomedical Engineering, involving computational chemistry and binding interactions. In 2011 John joined the life sciences computing group at the Texas Advanced Computing Center and have served and led a number of projects, all centered around either developing tools and infrastructure to support life sciences research or training scientists to leverage advanced computing resources. John has been consistently involved in teaching and training for over 8 years, including university courses, 1-on-1 mentoring, consulting, workshops, and presentations. Staying on the "front lines" of teaching technology to scientists is critical to his work as domain researcher, and active programmer, and an experienced teacher.
Vicky Schneider: Leads 361° Scientific Training Division, The Genome Analysis Centre, Norwich, United Kingdom
David Clements: Training and Outreach Coordinator, Galaxy Project, John Hopkins University, Baltimore, United States
Maximum Attendees: 40
Delegate Requirements: No previous experience required
Time: 1:30 pm – 5:30 pm (includes 1 coffee break)
Room: Liffey Meeting Room 3
Working with the ISCB student council, the Junior PI group and COBE COSI, this session is focused on career development. Here, we focus on training and preparing the bioinformatics professional to successfully launch and build a career. This session will be of interest to a wide audience. For students and junior PIs, you will participate in topics and practical sessions that can help build your career. For senior faculty and other professionals, it will provide ways in which you can improve skills to mentor your students and professionals building their career.
1:30-2:30 Improving your elevator pitch
(organised by the ISCB Student Council)
Presented By: Mick Watson, Director of ARK-Genomics, The Roslin Institute, University of Edinburgh, UK
You’ve just bumped into the person who could decide your next career move. They are about to head to their next meeting and you have two minutes to convince them that your science is worthy. Can you do it?
In this session you will learn the theory behind how to deliver a great elevator pitch. You will then get the opportunity to put this theory to the test, honing and practicing your pitch with other audience members so that the next time you hop in an elevator, you will be ready.
2:30-3:30 Being judged: grants reviewers and journal editors.
(organised by the ISCB Junior Principal Investigators Initiative)
Presented By: Dr. Peter Rodgers, Features Editor, eLife, UK
Professor Carole Goble, School of Computer Science, University of Manchester, UK
This session will help shed light on how your science might be perceived and judged. We will hear perspectives from two people who can have a strong impact on the career path of a junior principal investigator: a journal editor and a grant reviewer.
A journal editor’s perspective. How do you write a cover letter? How do you rebut a review? How do you choose the right journal? How do you deal with the press? These questions will be answered by a journal editor who will provide insight into the judgements behind the editorial process and everything around publishing a high impact paper.
A grant reviewers perspective. What are grant reviewers looking for? What makes a grant stand out? In this session, we will be provided with a reviewer's perspective on first impressions about your grant submission and what makes for a winning grant.
3:30-4:00 Coffee break
4:00-4:30 - Witness a live interview for a faculty position.
(organised by the ISCB Junior Principal Investigators Initiative)
Presented By: Associate Professor Curtis Huttenhower, Department of Biostatistics, School of Public Health, Harvard University, USA
Professor Lawrence E. Hunter, Director of the Center for Computational Biology and of the Computational Bioscience Program, University of Colorado School of Medicine, USA
Ever wondered what it is like to interview for a faculty position? In this session, you will find out! One brave soul will participate in a “mock” faculty position interview, revealing to the audience the rigors of the interview process. Following the interview, the audience will be asked to participate in a critique of both the interviewee and interviewer.
4:30-5:30 - How to plan your career but also be aware of your opportunities.
(organised the COBE COSI)
Presented By: Professor Winston Hide, Department of Neuroscience Sheffield Institute of Translational Neuroscience, University of Sheffield
Professor Nickola Mulder, Institute of Infectious Disease and Molecular Medicine, UCT Faculty of Health Sciences, South Africa
Dr Cath Brooksbank, Head of the EBI Training Programme, European Bionformatics Institute, UK
Many people - across the entire career spectrum, from students to PIs - are uncertain about the future and what they want to do next. Some are happy simply to take the next opportunity that comes their way; others like to plan. But even those who know what they want to do may find that their plans don’t always work out - the circumstances of life often get in the way, changing the course of their careers (the best-laid plans of mice and men often go astray!).
This session will feature talks from a diverse group of successful bioinformatics individuals, who will illustrate how much of their journey was planned versus how much was the work of serendipity, and will suggest elements of the journey over which you can take some measure of control. Planning tips also include topics such as “How does one learn the best way to teach?”, “How does one learn the way to manage budget, staff, a lab, etc?”, etc.
Jeroen de Ridder – Assistant Professor, Delft Bioinformatics Lab, Delft University of Technology, the Netherlands
Geoff Macintyre, Cancer Research UK Cambridge Institute, University of Cambridge, United Kingdom
Venkata P. Satagopam Research Scientist, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Luxembourg
Manuel Corpas, Project Leader, The Genome Analysis Centre, Norwich Research Park, Norwich, United Kingdom
Yana Bromberg, Assistant Professor, School of Environmental and Biological Sciences, Rutgers University, New Brunswick, NJ, United States
Maximum Attendees: 50
Delegate Requirements: No previous experience required