Leading Professional Society for Computational Biology and Bioinformatics
Connecting, Training, Empowering, Worldwide

Upcoming Conferences

A Global Community

  • ISCB Student Council

    dedicated to facilitating development for students and young researchers

  • Affiliated Groups

    The ISCB Affiliates program is designed to forge links between ISCB and regional non-profit membership groups, centers, institutes and networks that involve researchers from various institutions and/or organizations within a defined geographic region involved in the advancement of bioinformatics. Such groups have regular meetings either in person or online, and an organizing body in the form of a board of directors or steering committee. If you are interested in affiliating your regional membership group, center, institute or network with ISCB, please review these guidelines (.pdf) and submit your application using the online ISCB Affiliated Group Application form. Your exploratory questions to ISCB about the appropriateness of a potential future affiliation are also welcome by Diane E. Kovats, ISCB Executive Director (This email address is being protected from spambots. You need JavaScript enabled to view it.).

  • Communities of Special Interest

    topically-focused collaborative communities


  • ISCBconnect

    open dialogue and collaboration to solve problems and identify opportunities

  • ISCB Member Directory

    connect with ISCB worldwide

  • ISCB Innovation Forum

    a unique opportunity for industry

Professional Development, Training and Education

ISCBintel and Achievements


Live-steaming (and rebroadcast) of the ISMB/ECCB 2019 Distinguished Keynotes

ISCB proudly presents the live video-casting of the ISMB/ECCB 2019 keynote speakers. ISCB members who are unable to attend the flagship conference can watch the keynotes complimentary. Nonmembers can register for the ISMB/ECCB 2019 live broadcast for $250 USD.

Plan to Watch!

ISCB will be live broadcasting the keynotes daily at the scheduled program time and will re-broadcast the presentation at 6:00 PM CET. The ISCB Distinguished Keynote on Sunday, July 21 and presentation of the Accomplishments by a Senior Scientist Award and keynote will be broadcasted at its programmed time with no re-broadcast. Registration to this event gives access to both the live broadcast and the rebroadcast of the sessions.


Live Broadcast Schedule

Sunday, July 21, 6:30 pm - 7:30 pm CET

Nikolaus Rajewsky

Max-Delbrück-Centrum for Molecular Medicine in the Helmholtz Association
Berlin-Buch, Germany

Presentation Title: Principles of gene regulation in space and time by single-cell analyses.

Monday, July 22, 8:30 am - 9:30 am CET William Stafford Noble

William Stafford Noble

Department of Genome Sciences; Department of Computer Science and Engineering
University of Washington, Seattle, United States

Presentation Title: Traveling across spaces: the power of embedding genomic and proteomic data into a latent space

Rebroadcast time: 6:00 PM CET

Tuesday, July 23, 8:30 am - 9:30 am CET

Alexis Battle

Biomedical Engineering and Computer Science
John Hopkins University
Baltimore, United States

Presentation Title: Modeling the complex impact of common and rare genetic variation on gene expression

Rebroadcast time: 6:00 PM CET

Wednesday, July 24, 8:30 am - 9:30 am CET Christophe Dessimoz

Christophe Dessimoz

SNSF Professor, University of Lausanne, Switzerland
Associate Professor, University College London, United Kingdom
Group leader, Swiss Institute for Bioinformatics

Presentation Title: Challenges and rewards of benchmarking – how to cope with a biased, incomplete, or even entirely missing ground truth

Rebroadcast time: 6:00 PM CET

Thursday, July 25, 5:00 pm - 6:00 pm CET Bonnie Berger

Bonnie Berger

Simons Professor of Mathematics at MIT; Electrical Engineering and Computer Science
Massachusetts Institute of Technology
Cambridge, United States

Presentation Title: Biomedical Data Sharing and Analysis at Scale

COSI Tracks & Other Abstracts

COSI Organizer Information Page

  • Speaker Funding- $1000 per COSI day to support travel of invited speakers.  This can also be used to purchase additional registrations.
  • Registration Allowance of 3375 CHF.  This represents 5 full conference registrations at the member rate.  It is an allowance this year as some COSIs wanted the option to split up the registrations into two-day passes.   Steven will provide details in late March on how to access the registration. IMPORTANT: If you know who will receive complimentary or discounted registration please ensure the individual does not register until they receive instructions from Steven.  PLEASE provide your list of names and email to This email address is being protected from spambots. You need JavaScript enabled to view it. by May 15.
  • Attendee Commissions - At the end of the conference, ISCB will calculate the COSI commissions.  Commissions are based on the number of registrations that identified your group as their main COSI. *Reduced and complimentary registrations do not count towards COSI commission attendance numbers
  • Unrestricted use of escrow funds to support COSI track speakers or additional events
  • Full allocation of any sponsorship raised by COSI to COSI escrows

Abstract Submission Process
  • COSIs identify 2 or 3 Abstract Chairs (ACs) from within community to manage the review process. These names will be added to EasyChair as Track Chairs for each COSI.
  • COSI Area Chairs will be responsible for identifying a review / program committee to review the abstracts for both talk and poster presentation within their COSI. ACs will add these names to COSI track within EasyChair.
  • Each COSI is responsible for reviewing abstracts submitted to their area as either:
    • Poster only
    • Talk and poster (abstracts in this category if not accepted as a talk should be reviewed for a poster).
  • Ideally each abstract should have a minimum of two (2) reviews and ideally three (3).
  • COSI abstracts chairs are encouraged to quickly review the abstracts that are submitted to their COSI. If the abstract is not topical, please let Steven Leard (This email address is being protected from spambots. You need JavaScript enabled to view it.) know and he can transfer the abstract to the appropriate COSI suggested by your COSI. We recognize abstracts may cross COSI themes. In the event that an abstract could fit in multiple theme, it will be considered first to the COSI for which the author has designated submission. If not selected for oral, it may be considered for another COSI track.
  • COSI Area Chairs responsible for notifying acceptances for talks and posters within COSI track. (Sample acceptance below)
  • ISCB will write accepted presenters with a request to confirm participation (early and late submitters) and COSIs can search that status of presentation accepts at: https://www.iscb.org/cms_addon/conferences/ismbeccb2019/easychair/submitterdecisionreport
  • Selected Abstract talks will be presented by COSI track and run in parallel at the conference.
  • The length of a talks are in units of 20 minutes (should includes time for questions).  Oral presentation times for abstracts are announced by the COSI track organizers.
  • COSI Area Chairs responsible for reviewing Late Posters to their COSI (opens April 15, closes, May 15) within individual COSIs. *Acceptance notifications sent May 23.
  • COSI Area Chairs responsible for recommending top 3 posters (submitted as part of early submission process) to your COSI. Details to be sent to Poster Chairs (This email address is being protected from spambots. You need JavaScript enabled to view it.) by May 24 for consideration of ISMB poster prizes.
  • The poster display schedule is available at: https://www.iscb.org/ismbeccb2019-submit/abstracts#postersdisplay Poster numbers will be available by May 31, 2019.
Sample EasyChair Accept Letter:

ISMB/ECCB 2019 Acceptance Notification (adapt for acceptance of talk and/or poster)

Congratulations your submission has been accepted for a talk and/or poster at ISMB/ECCB 2019 as part of the XXX COSI.

  • COSIs will provide their detailed talk schedule in late May.- Posters will be presented as noted at: https://www.iscb.org/ismbeccb2019-submit/abstracts#postersdisplay
  • One author must be registered and present the talk and/or poster at the conference. You can register at https://www.iscb.org/ismbeccb2019-registration Early registration ends on June 20 so register early and save!
  • The submission presenter will receive an email by ISCB no later than May 10 requesting an online confirmation that the submission will be presented and confirming the name of the presenter. Please confirm your participation by May 17. If you have not received your confirmation request email by May 12 write This email address is being protected from spambots. You need JavaScript enabled to view it.
  • If you have an accepted talk or poster at ISMB/ECCB 2019 you will receive in a separate email an invitation to apply for a travel fellowship - You should expect the email no later than May 10.  Details on travel fellowships are available at: https://www.iscb.org/ismbeccb2019-general/travel-fellowship
  • Many talks at ISMB/ECCB 2019 are audio/video recorded for the purpose of developing an archival library of ISCB/ISMB presentations to share the history, growth and development of the science. Selections published on the ISCB website are presented as a synchronized audio and slide presentations for viewing. Before viewing presentations, individuals must electronically sign and agree that no part of any presentation will be downloaded, distributed, changed or altered in any manner and that the presentation offered is for information only. Please complete (no later than June 1, 2019) the permission form is available at: https://www.iscb.org/submissions/permissionForm/

Examples of recordings from are available at: https://www.iscb.org/iscb-multimedia

We suggest that you book your conference hotel as soon as possible - details are available at: https://www.iscb.org/hotels

Signed by:
XXX COSI organizers and email for contact about COSI program

Abstract Submission Keydates

Thursday, January 31, 2019

Call for Abstracts Opens

Thursday, April 4, 2019

ACs have Program Committee (Reviewers invited and added to EasyChair)

Thursday, April 11, 2019

Abstracts Submission Deadline

Monday, April 15, 2019

Late Poster Submissions Open

Wednesday, May 1, 2019

COSI Share Initial Talk and/or Poster Acceptances with Other COSIs to allow non-selected submissions to be offered for presentation by alternate COSIs.

Thursday, May 9, 2019

Talk and/or Poster Acceptance Notifications sent by COSI/Track ACs

Sunday, May 12, 2019

CAMDA Extended Abstracts Deadline

Wednesday, May 15, 2019

Late Poster Submissions Deadline

Thursday, May 23, 2019

Late Poster Acceptance Notifications sent by COSI/Track ACs

Thursday, May 23, 2019

CAMDA Acceptance Notification

Friday, May 24, 2019

Provide Poster Chairs (This email address is being protected from spambots. You need JavaScript enabled to view it.) top 3 best posters from COSI for consideration of ISMB poster prizes

Friday, May 31, 2018

Poster Presentation Numbers announced (ISMB/ECCB) Poster schedule available at:

Poster Prize Nominations from COSIs

COSIs, Thank you for nominating posters to be ultimately evaluated for overall conference poster prizes! Your work is important to help achieve ISCB’s goal of promoting excellence in the work of trainees. 

To ensure representation of all fields of research, we ask each COSI to nominate 3 abstracts to be evaluated during ISMB/ECCB for a total of 6 conference-wide poster prizes. (There are an additional prize for best posters in Structure and Function Prediction.)  

Please nominate posters based on their likelihood of describing important, standalone units of work and the clarity and flow of the written abstract.  Note: Exclude from consideration any poster that is not being presented by a trainee (student, postdoc, etc). No problem if this is not clear at this stage though. The final prizes may only be awarded for trainee presentations.

Nominations should be sent by May 24, 2019 to This email address is being protected from spambots. You need JavaScript enabled to view it.  When sending your nominees please include your COSI name + 2019 Poster Prize Nominations in the subject line. Please include the easychair assigned submission number and poster title for your nominees in the body of the email.

**Please notes poster only submissions to the General Computational Biology category are reviewed by the Poster Chairs.

Talk Times

Monday, July 22 / Tuesday, July 23 / Wednesday July 24

10:15 am - 10:20 am (welcome & start)
10:20 am - 10:40 am (Time Slot 1)
10:40 am - 11:00 am (Time Slot 2)
11:00 am - 11:20 am (Time Slot 3)
11:20 am - 11:40 am (Time Slot 4)
11:40 am - 12:00 pm (Time Slot 5)
12:00 am - 12:20 pm (Time Slot 6)
12:20 pm - 12:40 pm (Time Slot 7)
Lunch (and ISCB Town Hall (July 22), CompBio Ignite talks (July 23 and July 24)
2:00 pm - 2:20 pm (Time Slot 8)
2:20 pm - 2:40 pm (Time Slot 9)
2:40 pm - 3:00 pm (Time Slot 10)
3:00 pm - 3:20 pm (Time Slot 11)
3:20 pm - 3:40 pm (Time Slot 12)
3:40 pm - 4:00 pm (Time Slot 13)
4:40 pm - 5:00 pm (Time Slot 14)
5:00 pm - 5:20 pm (Time Slot 15)
5:20 pm - 5:40 pm (Time Slot 16)
5:40 pm - 6:00 pm (Time Slot 17)
Posters (6:00 pm - 8:00 pm)

Thursday, July 25

8:35 am - 8:40 am (welcome & start)
8:40 am - 9:00 am (Time Slot 1)
9:00 am - 9:20 am (Time Slot 2)
9:20 am - 9:40 am (Time Slot 3)
10:15 am - 10:20 am (re-start)
10:20 am - 10:40 am (Time Slot 4)
10:40 am - 11:00 am (Time Slot 5)
11:00 am - 11:20 am (Time Slot 6)
11:20 am - 11:40 am (Time Slot 7)
11:40 am - 12:00 pm (Time Slot 8)
12:00 pm - 12:20 pm (Time Slot 9)
12:20 pm - 12:40 pm (Time Slot 10)
Lunch / Career Fair / Poster session over lunch (COSIs wishing to do so -- notify This email address is being protected from spambots. You need JavaScript enabled to view it. if doing so.)
2:00 pm - 2:20 pm (Time Slot 11)
2:20 pm - 2:40 pm (Time Slot 12)
2:40 pm - 3:00 pm (Time Slot 13)
3:00 pm - 3:20 pm (Time Slot 14)
3:20 pm - 3:40 pm (Time Slot 15)
3:40 pm - 4:00 pm (Time Slot 16)
4:00 pm - 4:20 pm (Time Slot 17)
4:20 pm - 4:40 pm (Time Slot 18)
4:40 pm Grab and Go Break to: Closing Keynote (5:00 pm)
Awards and Closing (6:00 pm - 6:20 pm)

General FAQ

Q: Can I submit more than one abstract?
A: Yes, but although having the same person deliver more than one talk is permitted, it is not encouraged. Also, although a poster presenter may present two posters (one in Poster Session A and one in Poster Session B), we encourage labs to involve multiple presenters.

Q: Can previously accepted work be considered for a poster?
A: Yes, we do ask that you note the year the work was published and provide the Digital Object Identifier (DOI) during the submission process.

Q: What is the size for a poster?
A: Details are posted at: https://www.iscb.org/ismbeccb2019-submit/abstracts#postersize

Career Fair

Career Fair will take place Thursday, July 25th from 12:40pm - 2pm in the Exhibition Area.

Attending the Career Fair
  • Conference attendees participating in the Career Fair must upload their resume into the ISCB Career Center (https://careers.iscb.org/) resume repository and will have a 'Talent' ribbon on their conference badge.
    • Sign-up is allowed on-site to attend the Career Fair but attendees MUST stop by the ISCB Booth and sign up.
Recruiting at the Career Fair
  • Institutions/Exhibitors participating in the Career Fair will have a blue identifier on their exhibit booth/recruiter tables. Additional institutions that are recruiting will have a table in the Exhibit Hall near the Jobs Board.
    • Recruiters participating in the Career Fair will have available positions posted on the jobs board and/or additional opportunities at their tables and will have a 'Talents Seeker' ribbon on their conference badge.
  • Please stop by the ISCB booth to see Bel Hanson or email This email address is being protected from spambots. You need JavaScript enabled to view it. with any questions.

Career Fair Recruiters


Proceedings Reviewers

Sanne Abeln, Vrije Universiteit Amsterdam, Netherlands
Barbosa Da Silva Adriano, University of Luxembourg - LCSB, Luxembourg
Max Alekseyev, George Washington University, United States
Lars Arvestad, Stockholm University, Sweden
Ferhat Ay, La Jolla Institute, United States
Erman Ayday, Case Western Reserve University and Bilkent University, Turkey
Francisco Azuaje, Luxembourg Institute of Health (LIH), Luxembourg
Chris Bailey-Kellogg, Dartmouth College, United States
Irina Balaur, European Institute for Systems Biology and Medicine (EISBM), Lyon, France
Brunilda Balliu, Stanford University, United States
Peter Banda, University of Luxembourg, Luxembourg
Nuno Bandeira, University of California San Diego, United States
Vikas Bansal, University of California San Diego, United States
Yoseph Barash, University of Pennsylvania, United States
Adriano Barbosa, QMUL, United Kingdom
Jan Baumbach, Technical University of Munich, Germany
Gurkan Bebek, Case Western Reserve University, United States
Niko Beerenwinkel, ETH Zurich, Switzerland
Robert Beiko, Dalhousie University, Canada
Tim Beissbarth, University Medicine Göttingen, Germany
Asa Ben-Hur, Colorado State University, United States
Takis Benos, University of Pittsburgh, United States
Bonnie Berger, Massachusetts Institute of Technology, United States
Elsa Bernard, Institut Curie - Centre de recherche - BDD, France
Debswapna Bhattacharya, Auburn University, United States
Mathieu Blanchette, McGill University, Canada
Isabell Bludau, ETH Zurich, Switzerland
Nils Blüthgen, Charite, Germany
Sebastian Böcker, Friedrich Schiller University Jena, Germany
Valentina Boeva, Institut Cochin/INSERM/CNRS, France
Richard Bonneau, New York University, United States
Karsten Borgwardt, ETH Zurich, Switzerland
Christina Boucher, University of Florida, United States
Philip Bourne, University of Virginia, United States
Alan Boyle, University of Michigan, United States
Serdar Bozdag, Marquette University, United States
Edward Braun, Univeristy of Florida, United States
Michael R. Brent, wustl, United States
Jan Brezovsky, Faculty of Biology, Adam Mickiewicz University, Poland
Benedikt Brors, German Cancer Research Center (DKFZ), Germany
C.Titus Brown, University of California, Davis, United States
Tolga Can, Middle East Technical University, Turkey
João Carriço, Universidade de Lisboa, Portugal
Hannah Carter, University of California San Diego, United States
Mark Chaisson, University of Washington, United States
Nyasha Chambwe, Institute for Systems Biology, United States
Cedric Chauve, Simon Fraser University, Canada
Jake Chen, University of Alabama at Birmingham, United States
Jianlin Cheng, University of Missouri Columbia, United States
Rayan Chikhi, CNRS, France
Maria Chikina, Mount Sinai School of Medicine, United States
Leonid Chindelevitch, Simon Fraser University, Canada
Olivia Choudhury, IBM, United States
A. Ercument Cicek, Bilkent University, United States
Peter Clote, Department of Biology, Boston College; Computer Science, Ecole Polytechnique and Univ Paris-Sud XI, United States
Kevin Bretonnel Cohen, University of Colorado School of Medicine, United States
Phillip Compeau, Carnegie Mellon University, United States
Ana Conesa, Genomics of Gene Expression Lab, Spain
James Costello, University of Colorado Anschutz Medical Campus, United States
Mark Craven, University of Wisconsin-Madison, United States
Miklos Csuros, University of Montreal, Canada
Xuefeng Cui, Tsinghua University, China
Aedin Culhane, Dana-Farber Cancer Institute, Harvard School of Public Health, United States
Felipe da Veiga Leprevost, University of Michigan, United States
Thomas Dandekar, University of Würzburg, Germany
Susmita Datta, University of Florida, United States
Xavier de La Cruz, Vall d'Hebron Institute of Research (VHIR), Spain
Charlotte Deane, University of Oxford, United Kingdom
Viraj Deshpande, Illumina Inc., United States
Robin Dowell, University of Colorado Boulder, United States
Dannie Durand, Carnegie Mellon University, United States
Ingo Ebersberger, Goethe University, Germany
Mohammed El-Kebir, University of Illinois at Urbana-Champaign, United States
Nadia El-Mabrouk, University of Montreal, Canada
Eran Elhaik, The University of Sheffield, United Kingdom
Ray Enke, James Madison University, United States
Jason Ernst, University of California, Los Angeles, United States
Dirk Evers, Molecular Health GmbH, Germany
Gang Fang, Mount Sinai School of Medicine, United States
Piero Fariselli, University of Padova, Italy
Petko Fiziev, Illumina, United States
Anthony A. Fodor, UNC Charlotte, United States
Peter Freddolino, University of Michigan, United States
Iddo Friedberg, Iowa State University, United States
Caroline C. Friedel, Ludwig Maximilian University of Munich, Germany
Fabian Fröhlich, Harvard University, United States
Andreas Futschik, Department of Statistics, Johannes Kepler University Linz, Austria
Olivier Gevaert, Stanford University, United States
Dario Ghersi, University of Nebraska at Omaha, United States
Soumyabrata Ghosh, University of Luxembourg, Luxembourg
David Gibbs, Institute for Systems Biology, United States
David Gifford, Massachusetts Institute of Technology, United States
Jesse Gillis, Cold Spring Harbor Laboratory, United States
Anthony Gitter, University of Wisconsin-Madison, United States
David Gomez-Cabrero, Karolinska Institutet, Sweden
Graciela Gonzalez-Hernandez, Department of Epimediology, Biostatistics, and Informatics, Perelman School of Medicine, University of Pennsylvania, United States
Alexandra Graf, FH Campus Wien, Austria
Ananth Grama, Purdue University, United States
Casey Greene, University of Pennsylvania, United States
Ivo Grosse, Martin Luther University Halle-Wittenberg, Germany
Wei Gu, Luxembourg Centre For Systems Biomedicine (LCSB), Luxembourg
Alexey Gurevich, Center for Algorithmic Biotechnology, St. Petersburg State University (Saint Petersburg, Russia), Russia
Gamze Gursoy, Yale University, United States
Faraz Hach, University of British Columbia and Vancouver Prostate Centre, Canada
Matthew Hahn, Indiana University Bloomington, United States
Md Nafiz Hamid, Iowa State University, United States
Xiaoke Hao, Hebei University of Technology, China
Jan Hasenauer, Helmholtz Zentrum München, Germany
Sampsa Hautaniemi, University of Helsinki, Finland
Dominik Heider, Philipps-University of Marburg, Germany
Carl Herrmann, University Heidelberg, Germany
Winston Hide, Sheffield Institute for Translational Neuroscience, United Kingdom
Steven M. Hill, University of Cambridge, United Kingdom
Robert Hoehndorf, King Abdullah University of Science and Technology, Saudi Arabia
Ivo Hofacker, University of Vienna, Austria
Liisa Holm, University of Helsinki, Finland
Vasant Honavar, The Pennsylvania State University, United States
Jae Hoon-Sul, University of California, Los Angeles, United States
Farhad Hormozdiari, Program in Genetic Epidemiology and Statistical Genetics, Harvard University, United States
Fereydoun Hormozdiari, University of Washington, United States
Heng Huang, University of Pittsburgh, United States
Mathias Humbert, Swiss Data Science Center, ETH Zurich and EPFL, Switzerland
Trey Ideker, University of California San Diego, United States
Francesco Iorio, Wellcome Sanger Institute, United Kingdom
Zamin Iqbal, European Bioinformatics Institute, United Kingdom
Wataru Iwasaki, The University of Tokyo, Japan
Shantanu Jain, Northeastern University, United States
Lars Juhl Jensen, European Molecular Biology Laboratory, Denmark
Tao Jiang, University of California, Riverside, United States
Xiaoqian Jiang, UTHealth at Houston, United States
Andre Kahles, ETH Zurich, Switzerland
Tamer Kahveci, University of Florida, United States
Lukas Käll, KTH Royal Institute of Technology, Sweden
Emre Karakoc, University of Washington, Germany
John Kececiogu, University of Arizona, United States
Birte Kehr, Berlin Institute of Health / Charité - Universitätsmedizin Berlin, Germany
Sunduz Keles, University of Wisconsin-Madison, United States
Manolis Kellis, Massachusetts Institute of Technology, United States
Daisuke Kihara, Purdue University, United States
Miran Kim, University of Texas, Health Science Center at Houston, United States
Sun Kim, Seoul National University, South Korea
Larisa Kiseleva, OIST, Japan
David Knowles, University of Cambridge, United Kingdom
Ina Koch, Johann Wolfgang Goethe University Frankfurt am Main, Institute of Computer Science, Molecular Bioinformatics, Germany
Oliver Kohlbacher, University of Tübingen, Germany
Rachel Kolodny, US, Israel
Dmitry Korkin, Worcester Polytechnic Institute, United States
David Koslicki, Oregon State University, United States
Jovana Kovacevic, Faculty of Mathematics, University of Belgrade, Serbia
Mehmet Koyuturk, Case Western Reserve University, United States
Roland Krause, University of Luxembourg, Luxembourg
Smita Krishnaswamy, Yale University, United States
Hande Kucuk McGinty, University of Miami, United States
Volodymyr Kuleshov, Stanford University, United States
Anshul Kundaje, Stanford University, United States
Tsung-Ting Kuo, University of California San Diego, United States
Lukasz Kurgan, Virginia Commonwealth University, United States
Manuel Lafond, Université de Sherbrooke, Canada
Keren Lasker, Stanford University, United States
Robert Leaman, NCBI/NLM/NIH, United States
Kjong-Van Lehmann, ETH Zurich, Switzerland
Mark Leiserson, University of Maryland, United States
Sebastien Lemieux, IRIC / Université de Montréal, Canada
Jessica Li, University of California, Los Angeles, United States
Ming Li, Univ of Waterloo, Canada
Yong Li, Illumina Inc., United States
Yue Li, McGill University, Canada
Max Libbrecht, University of Washington Genome Sciences, United States
Olivier Lichtarge, Baylor College of Medicine, United States
Kui Lin, College of Life Sciences, Beijing Normal University, China
Yu-Chen Lo, Stanford University, United States
Stefano Lonardi, UC Riverside, United States
Zhiyong Lu, NCBI, United States
Gerton Lunter, University of Oxford, United Kingdom
Gang Luo, University of Washington, United States
Yves Lussier, University of Arizona, United States
Jian Ma, Carnegie Mellon University, United States
Shaun Mahony, The Pennsylvania State University, United States
Brad Malin, Vanderbilt University, United States
Serghei Mangul, University of California, Los Angeles, United States
Fabio Marroni, Università di Udine, Italy
Tobias Marschall, Saarland University / Max Planck Institute for Informatics, Germany
Pier Luigi Martelli, University of Bologna, Italy
Manja Marz, Uni Jena, Germany
David Mathews, University of Rochester, United States
David Matthews, University of Rochester, United States
Patrick May, Luxembourg Centre for Systems Biomedicine, Luxembourg
Paul Medvedev, The Pennsylvania State University, United States
Joao Meidanis, University of Campinas / Scylla Bioinformatics, Brazil
Renee Menezes, VU University Medical Centre, Netherlands
Vilas Menon, Columbia University, United States
Irmtraud Meyer, Max-Delbrück-Centrum für Molekulare Medizin (MDC), Berlin, and Free University, Berlin, Germany, Germany
Irmtraud M. Meyer, Max-Delbrück-Centrum für Molekulare Medizin (MDC), Berlin, and Free University, Berlin, Germany, Germany
Tom Michoel, Computational Biology Unit, Department of Informatics, University of Bergen, Norway
Tijana Milenkovic, University of Notre Dame, United States
Siavash Mirarab, The University of Texas at Austin, United States
Hosein Mohimani, Carnegie Melon University, United States
Yves Moreau, Katholieke Universiteit Leuven, Belgium
Bernard Moret, Ecole Polytechnique Fédérale de Lausanne, Switzerland
Alexandre Morozov, Rutgers University, United States
Quaid Morris, University of Toronto, Canada
Sach Mukherjee, DZNE, Germany
Sayan Mukherjee, Duke University, United States
T. M. Murali, Virginia Tech, United States
Robert F. Murphy, Lane Center for Computational Biology, Joint Carnegie Mellon University-University of Pittsburgh PhD. Program in Computational Biology, Depts. of Biol. Sciences, Biomed. Engineering & Machine Learning, United States
Shawn Murphy, Harvard University, United States
Chad Myers, University of Minnesota, United States
Niranjan Nagarajan, University of Maryland, Singapore
Luay Nakhleh, Rice University, United States
Leelavati Narlikar, National Chemical Laboratory, India
Kay Nieselt, Center for Bioinformatics Tübingen, University of Tübingen, Germany
William Stafford Noble, University of Washington, United States
Cecilia Noemi, University of Delaware, United States
Emmanuel Noutahi, InVivo AI, Canada
Ibrahim Numanagic, Massachusetts Institute of Technology, United States
Claire O'Donovan, EBI, United Kingdom
Layla Oesper, Carleton College, United States
Christine Orengo, University College London, United Kingdom
Yaron Orenstein, Ben-Gurion University, Israel
Hatice Osmanbeyoglu, University of Pittsburgh, United States
Aida Ouangraoua, Université de Sherbrooke, Canada
Gaurav Pandey, Mount Sinai School of Medicine, United States
Fabio Pardi, LIRMM - CNRS, France
Laxmi Parida, IBM, United States
Lee Parsons, University of Minnesota, United States
Srinivasan Parthasarathy, ohio state university, United States
Robert Patro, Stony Brook University, United States
Giulio Pavesi, University of Milan, Italy
Itsik Pe'Er, Columbia University, United States
Jian Peng, University of Illinois at Urbana-Champaign, United States
Sabine Peres, LRI Paris-Sud 11 University, France
Theodore Perkins, Ottawa Hospital Research Institute, Canada
Dmitri Pervouchine, Skolkovo Institute for Science and Technology, Russia
Thang Pham, VU University Medical Center, Netherlands
Alexander Pico, Gladstone Institutes, United States
Yann Ponty, CNRS/LIX, Polytechnique, France
M. Pop, University of Maryland, United States
Victoria Popic, Stanford University, United States
Natasa Przulj, Computer Science Department, United Kingdom
Teresa Przytycka, National Center of Biotechnology Information, NLM, NIH, United States
Simon Puglisi, University of Helsinki, Finland
Miguel Angel Pujana, IDIBELL, Spain
Tal Pupko, Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv 69978, Israel, Israel
Predrag Radivojac, Northeastern University, United States
Sven Rahmann, University of Duisburg-Essen, Germany
Huzefa Rangwala, George Mason University, United States
Ben Raphael, Princeton University, United States
Magnus Rattray, The University of Manchester, United Kingdom
Antonio Rausell, Institut Imagine - INSERM UMR-1163, France
Knut Reinert, FU Berlin, Germany
Vladimir Reinharz, Center for Soft and Living Matter, Institute for Basic Science, South Korea
Bernhard Renard, Robert Koch Institute, Germany
Boris Reva, Icahn School of Medicine at Mount Sinai, United States
Davide Risso, Cornell University, United States
Alberto Riva, Bioinformatics Core, ICBR, University of Florida, United States
Elena Rivas, Janelia Farm Research Campus, HHMI, United States
Manuel Rivas, Stanford University, United States
Marc Robinson-Rechavi, Universite de Lausanne, Switzerland
David Rocke, University of California, Davis, United States
Kirsten Roomp, LCSB, University of Luxembourg, Luxembourg
Anguraj Sadanandam, Institute of Cancer Research (ICR), United Kingdom
Surya Saha, Boyce Thompson Institute, United States
Leena Salmela, University of Helsinki, Finland
Javier Santoyo, Edinburgh Genomics, United Kingdom
Mansoor Saqi, NIHR Biomedical Research Centre, Guy's and St Thomas' NHS Foundation Trust and King's College London, United Kingdom
Venkata Satagopam, Luxembourg Centre For Systems Biomedicine (LCSB), University of Luxembourg, Luxembourg
Alexander Schoenhuth, Vrije Universiteit Amsterdam, Netherlands
Michael Schroeder, TU Dresden, Germany
Max Schubach, Berlin Institute of Health (BIH), Germany
Marcel Schulz, Goethe University, Germany
Veit Schwämmle, University of Southern Denmark, Denmark
Russell Schwartz, Carnegie Mellon University, United States
Maria Secrier, EMBL Heidelberg, Germany
Nigam Shah, Stanford University, United States
Mingfu Shao, Computational Biology Department, Carnegie Mellon University, United States
Hagit Shatkay, Dept. of Computer and Information Sciences, University of Delaware, United States
Tal Shay, Ben-Gurion University of the Negev, Israel
Nathan Sheffield, University of Virginia, United States
Li Shen, University of Pennsylvania, United States
Sean Simmons, Massachusetts Institute of Technology, United States
Saurabh Sinha, University of Illinois at Urbana-Champaign, United States
Johannes Soeding, MPI BPC, Germany
Giltae Song, Pusan National University, South Korea
Erik Sonnhammer, Stockholm University, Sweden
Alexis Stamatakis, Technical University of Munich, Germany
Maureen Stolzer, Carnegie Mellon University, United States
Jens Stoye, Bielefeld University, Germany
Pavel Sumazin, Baylor College of Medicine, United States
Krister Swenson, CNRS, Université de Montpellier, France
Wojciech Szpankowski, Purdue University, United States
Eric Tannier, INRIA, France
Oznur Tastan, Sabanci University, Turkey
Stefano Toppo, University of Padova, Italy
Ali Torkamani, Scripps Research Translational Institute, United States
Silvio Tosatto, University of Padova, Italy
Olivier Tremblay-Savard, University of Manitoba, Canada
Iosif Vaisman, George Mason University, United States
Alfonso Valencia, Barcelona Supercomputing Centre BSC, Spain
Fabio Vandin, University of Padova, Italy
Pierangelo Veltri, Laboratory of Bioinformatics, University of Catanzaro, Italy
Allegra Via, National Research Council of Italy (CNR) - Institute of Molecular Biology and Pathology (IBPM), Italy
Enrique Vidal, CRG, Spain
Martin Vingron, Max Planck Institut fuer molekulare Genetik, Germany
Slobodan Vucetic, Temple University, United States
Hao Wang, Carnegie Mellon University, United States
Joy Wang, University of Pittsburgh, United States
Wei Wang, University of California, Los Angeles, United States
Zhong Wang, Lawrence Berkeley National Lab; The Joint Genome Institute, United States
Tandy Warnow, the university of illinois at urbana-champaign, United States
Mark Wass, University of Kent, United Kingdom
Chaochun Wei, Shanghai Jiao Tong University, China
Zasha Weinberg, University of Leipzig, Germany, Germany
Joachim Weischenfeldt, Biotech Research & Innovation Centre (BRIC), Denmark
Bart Westerman, VU, Netherlands
Sebastian Will, University of Vienna, Austria
Phillip Wilmarth, Oregon Health and Science University, United States
Haim Wolfson, School of Computer Science, Tel Aviv University, Israel
Haim J. Wolfson, School of Computer Science, Tel Aviv University, Israel
David J. Wu, University of Virginia, United States
Yu-Wei Wu, Taipei Medical University, Taiwan
Yu Xia, McGill University, Canada
Jinbo Xu, Toyota Technological Institute at Chicago, United States
Makoto Yamada, RIKEN AIP, Japan
Esti Yeger-Lotem, Ben Gurion University, Israel
Peng Yu, Texas A&M University, United States
Noah Zaitlen, University of California San Francisco, United States
Haoyang Zeng, Massachusetts Institute of Technology, United States
Jianyang Zeng, Tsinghua University, China
Louxin Zhang, National University of Singapore, Singapore
Weixiong Zhang, Washington University in St. Louis, United States
Yang Zhang, CISPA Helmholtz Center for Information Security, Germany
Deyou Zheng, Albert Einstein College of Medicine, United States
Chengsheng Zhu, Rutgers University, United States
Ralf Zimmer, Ludwig Maximilian University of Munich, Germany
Marinka Zitnik, Stanford University, United States
Michal Ziv-Ukelson, Ben Gurion University of the Negev, Israel

Birds of a Feather (BoF) - ISMB/ECCB 2019

Interested in organizing a Birds of a Feather (BoFs) session at ISMB/ECCB? Learn more here: https://www.iscb.org/cms_addon/conferences/ismbeccb2019/bof/ (Complete your submission by June 15 to be included in the printed program. Submissions after June 15 will have details available online and on the conference app.)

The ISCB code of conduct

Room: Boston 1/2 Ground Floor) Tuesday July 23 (12:45 pm - 1:45 pm)


Lucia Peixoto and Casey Greene, Washington State University, University of Pennsylvania


In this session we will introduce ISCB members to the recently approved ISCB code of conduct and answer questions regarding this policy as well as received feedback for future policy updates. This is a joint session organized by the Junior PI COSI and the Equity Diversity and Inclusion task-force from ISCB.

Actionable ways to increase diversity in our community: Next steps for ISCB EDI TaskForce

Room: Boston 1/2 (Ground Floor) Wednesday, July 24 (12:45 pm - 1:45 pm)


Malvika Sharan, European Molecular Biology Laboratory, EMBL


In this session, I would facilitate the conversation beyond the fact that diversity is required, not only to improve inclusiveness but for the growth of a community/organization. The discussion will be catalyzed by a few proven solutions developed and adopted by ISCB and other big communities. We will aim to engage conference attendees in in a discussion that will help shape the next steps for ISCB Equality, Diversity and Inclusion (EDI) TaskForce.

Cancelled - Dos and Don’ts’ checklist for computational training

Room: Shanghai 1/2 (Ground Floor) Wednesday, July 24 (12:45 pm - 1:45 pm)


Sara El-Gebali, EMBL-EBI


There is a growing demand in various research fields for computational training and resources to work with open access data. Hence, trainers need to design their training materials as per the need of their audience who might be located in developed or developing countries. I would like to invite participants to create a comprehensive ‘Dos and Don’ts’ checklist when preparing for training sessions for different countries and audiences

Integrative queryable genomics with InterMine

Room: Shanghai 3/4 (Ground Floor) Wednesday, July 24 (12:45 pm - 1:45 pm)


Yo Yehudi, Department of Genetics, University of Cambridge


InterMine is an open source biological data integration warehouse which allows biologists and bioinformaticians to access integrated genomic data via web interfaces and APIs. Since there are now over 30 InterMine instances "in the wild", we invite all InterMiners at ISMB to come join us for a meet-and-greet and friendly chat amongst community members.

Welcome to BOSC (the Bioinformatics Open Source Conference)

Room: Delhi (Ground Floor) Wednesday, July 24 (12:45 pm - 1:45 pm)


Monica Munoz-Torres, BOSC


An opportunity to meet other BOSC community members and share your goals in attending BOSC and your suggestions about how we can make BOSC even better. Whether this is your first BOSC or your 20th, all are welcome!

Portable data analysis workflows with the CWL standards. CWL v1.1 update and community meetup

Room: Kairo 1/2 (Ground Floor) Wednesday, July 24 (12:45 pm - 1:45 pm)


Michael R. Crusoe, ELIXIR-NL & ELIXIR Interoperability Platform


Participants will learn about using the latest release of the Common Workflow Language standards (version 1.1) to create and run data analysis workflows in portable and interoperable manner. They can also share their experiences with writing and running CWL with each other. Computer system administrators, programmers, and operators are also welcome!

Bioinformaticians in Aging & Senescence Research

Room: Osaka / Samarkand (3rd Floor) Wednesday, July 24 (12:45 pm - 1:45 pm)


Georg Fuellen, Rostock University Medical Center


Senotherapeutic approaches are among the most promising approaches towards extending lifespan and healthspan, with huge potential societal and economic impact, but a precision medicine approach is needed. Towards establishing the biomarkers from omics and other data, bioinformatics on a large scale is needed, and this BoF is designed to come together and discuss projects and future meetings. You do not have to work on aging/senescence data at the moment; everybody is welcome!

Open Bioinformatics Foundation Board Meeting

Room: Delhi (Ground Floor) Thursday, July 25 (12:45 pm - 1:45 pm)


Heather Wiencko, OBF


The OBF has a public board meeting roughly once a year, in part to vote on important business issues, and in part to publicly discuss items relevant to the OBF community. This year we're choosing to hold it during BOSC, in the hope that members of the community will be able to attend. We expect to elect a new board member during this year's meeting, and other agenda items will be published in advance of the meeting on our website: https://news.open-bio.org/

Cytoscape Roadmap and Feedback

Room: Shanghai 3/4 (Ground Floor) Thursday, July 25 (12:45 pm - 1:45 pm)


Scooter Morris, University of California at San Francisco


The Cytoscape Consortium will be hosting an open public meeting for the community of users, app developers and scripter writers to learn about the latest features and to engage with core developers on the roadmap for the future. If you are new to Cytoscape or a long-time power user, you are welcome to join.

ISMB/ECCB 2019 - Tutorials

ISMB/ECCB 2019 features pre-conference tutorial sessions on Sunday, July 21, 2019 one day prior to the start of conference scientific program.

Tutorial attendees should register using the on-line registration system - pricing is available at https://www.iscb.org/ismbeccb2019-registration. Tutorial participants must be registered for the ISMB/ECCB conference to attend a tutorial. Attendees will receive a Tutorial Entry Pass (ticket) at the time they register on site

Tutorial FD1: Interpretability for deep learning models in computational biology

Sunday, July 21, 9:00 am - 6:00 pm

Room: Montreal (2nd Floor)

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Dr. María Rodríguez Martínez, IBM Research – Zürich.
Dr. Matteo Manica, IBM Research – Zürich.
Dr. Ali Oskooei, IBM Research – Zürich.
An-Phi Nguyen, IBM Research – Zürich.


The recent application of deep neural networks to long-standing problems such as the prediction of functional DNA sequences, the inference of protein-protein interactions or the detection of cancer cells in histopathology images has brought a break-through in performance and prediction power. However, high accuracy often comes at the price of loss of interpretability, i.e. many of these models are built as black-boxes that fail to provide new biological insights. This tutorial focuses on illustrating some of the recent advancements in the field of Interpretable Artificial Intelligence. We will show how explainable, smaller models can achieve similar levels of performance than cumbersome ones, while shedding light on the underlying biological principles driving model decisions.

We will demonstrate how to build and extract knowledge using interpretable approaches in two different domains of computational biology: the functional analysis of raw DNA sequencing data and drug sensitivity prediction models. The choice of these two applications is motivated by the availability of adequately large datasets that can support deep learning approaches and by their high relevance for personalized medicine. We will exploit both publicly available deep learning models as well as in-house developed models.

The tutorial is aimed to strike the right balance between theoretical input and practical exercises. The tutorial has been designed to provide the participants not only with the theory behind deep learning and interpretability, but also to offer a set of frameworks, tools and real-life examples that they can implement in their own projects.


This course is designed for everyone who would like to learn the basics of interpretability techniques for deep learning. The tutorial will provide a brief introduction to key concepts in deep learning, before exploring recent developments in the field of interpretability.


None, if participants just wish to listen. Those who would like to also participate in the hands-on exercises are required to provide their own laptop and should have a basic programming knowledge on Python and shell scripting. All the material for the lectures and hands-on exercises will be available prior the day of the tutorial for download.

Maximum Participants: 100

Schedule Overview
9:00 - 10:00 am Introduction to deep learning
  • Deep learning: What, why, how deep?
  • Activations functions
  • Cost functions
  • Backpropagation
  • Regularization
  • Optimization
10:00 - 11:00 am Common deep learning models
  • Multi-Layer Perceptron (MLP)
  • Auto-enconders (AE)
  • Convolutional Neural Networks (CNN)
  • Recurrent Neural Networks (RNN)
11:00-11:15 am Coffee Break
11:15-12:30 pm Interpretability in deep learning
  • Introduction to interpretability
  • A few techniques for interpretability
    • Backpropagation-like approaches
    • Perturbation-based approaches
    • Attention mechanisms
    • Surrogate Models
    • Other models
  • Discussion
2:00 - 3:00 pm CellTyper: interpretability on simple models. (Hands-on)
3:00 - 4:00 pm Understanding DeepBind: actionable interpretability? (Hands-on)
4:00 - 4:15 pm Coffee Break
4:15 - 5:00 pm PaccMann - Interpreting complex models: are model-agnostic interpretability methods the way to go? (Hands-on)
5:00 - 6:00 pm PaccMann - Built-in interpretability: attention-mechanisms to the rescue. (Hands-on)

Tutorial AM2: Recent Advances in Statistical Methods and Computational Algorithms for Single-Cell Omics Analysis

Sunday, July 21, 9:00 am - 1:00 pm

Room: Sydney (2nd Floor)


Rhonda Bacher, PhD Assistant Professor, Department of Biostatistics, University of Florida, United States
Yuchao Jiang, PhD Assistant Professor, Department of Biostatistics, University of North Carolina at Chapel Hill, United States
Jingshu Wang, PhD Postdoctoral fellow, Department of Statistics, University of Pennsylvania, United States


Single-cell genomics is the study of individual cells using omics approaches, which circumvents averaging artifacts associated with traditional bulk population data and yields new insights into cellular heterogeneity. The field has seen rapid development in both technologies and statistical methods and computational algorithms, leading to improved data analysis. This tutorial is focused on advanced statistical and computational methods that are recently developed for single-cell omics data. The first half of the tutorial will include a brief introduction, followed by “generalized” methods and workflows for scRNA-seq data, including data normalization, visualization, batch correction, and denoising. The second half of the tutorial will be on “specific” topics and applications in the single-cell domain, including pseudotime reconstruction, simultaneous measurements of single-cell transcriptomic and V(D)J profiles, multimodal alignment of single-cell transcriptomic and epigenomic data, as well as single-cell inference of tumor heterogeneity.

Website: https://github.com/rhondabacher/ISMB2019_SingleCellTutorial


This tutorial is intended for an audience with genomics/computational background, who are interested in cutting-edge developments of single-cell research, including both method development and application. Previous experiences in analyzing single-cell data are preferred. Advanced tools that are recently developed in the field will be taught from a high-level perspective.

Maximum Participants: 100

Schedule Overview
9:00 - 9:40 am Introduction: tutorial infrastructure setup; technologies for scRNA-seq data generation; types of analysis that can be carried out; data normalization, spike-ins, and technical artifacts (RB).
9:40 - 10:00 am Data visualization, including UMAP, t-SNE, etc. (YJ).
10:00 - 10:30 am Denoising, batch correction (JW).
10:30 am - 11:00 am Autoencoder and transfer learning for scRNA-seq (JW).
11:00 - 11:15 am Coffee Break
11:15 - 11:40 am Pseudotime reconstruction, cell ordering (RB).
11:40 - 12:00 am ScRNA-seq in immunology (VDJ, cell surface protein, RB).
12:00 - 12:30 pm Methods for scATAC-seq analysis and multimodal alignment of single-cell transcriptomic and epigenomic data (YJ).
12:30 - 1:00 pm Single-cell omics analysis in cancer, including assessing cancer heterogeneity and inferring tumor phylogeny by scRNA-seq, and profiling copy number changes by scDNA-seq (YJ).

RB: Rhonda Bacher. YJ: Yuchao Jiang. JW: Jingshu Wang

Tutorial AM3: Building a Distributed Knowledge Graph to Assist with Computational Drug Discovery

Sunday, July 21, 9:00 am - 1:00 pm

Room: Kairo 1/2 (Ground Floor)


Rabie Saidi, European Bioinformatics Institute (EMBL-EBI), Cambridge, United Kingdom
Maryam Abdollahyan, Queen Mary University of London, United Kingdom
Andrew Nightingale, European Bioinformatics Institute (EMBL-EBI), Cambridge, United Kingdom
Maria J Martin, European Bioinformatics Institute (EMBL-EBI), Cambridge, United Kingdom


Drug discovery pipelines are expensive in time and resources, which are wasted if a drug is rejected due to toxicities discovered in late stages. Computational investigation of the different entities (proteins, diseases, pathways, ...) that are involved in drug discovery could help provide a better understanding of the dynamics governing their relations and the downstream effects of targeting proteins with drugs. Using various data sources, including the UniProt Knowledgebase, disease ontologies, the DrugBank database and protein interactions and pathways data, we present data integration approaches to build a distributed knowledge graph (DKG) that will assist with computational discovery of drugs.

In this tutorial, the participants will be introduced to two emerging tools in the field of big data, namely the Apache Spark computing framework and the Apache Zeppelin interactive analytics framework. Spark can be used from within Zeppelin and coupled with other back-end languages and tools to provide deeper insights. Participants will also learn about data structures for representing knowledge graphs (GraphFrames) and building machine learning (ML) models.


Beginner or intermediate. This tutorial will be of broad interest to researchers from academia or industry who would like to apply an interactive analytics platform coupled with other back-end languages and tools to build machine learning models for analysis of drug-discovery-related data.

This tutorial is mainly a hands-on session using Apache Spark and Apache Zeppelin. Programming knowledge (e.g. Scala, Java, Python or similar) is required. Instructions on how to setup the environment will be provided in advance.

Attendees are required to provide their own laptop.

Maximum Participants: 40

Schedule Overview
9:00 - 9:05 am Introduction
9:05 - 9:35 am Overview:
  • Motivation
  • Challenges
  • Data Sources (e.g. UniProt, Disease Ontologies, DrugBank, Protein Interactions and Pathways Databases, etc.)
9:35 - 11:00 am Hands-on Session: Generating the DKG
  • Data Transformation with Apache Spark
  • Linking Data Sources
  • Building the DKG
11:00 - 11:15 am Coffee Break
11:15 - 12:25 pm Hands-on Session: Exploring the DKG
  • Interactive Analytics with Zeppelin
  • Visualising and Querying the DKG
12:25 - 12:50 pm Hands-on Session: Predictive Analytics
12:50 - 1:00 pm Perspectives + Q&A
  • Integrating Additional Resources
  • Relation to Other Drug Discovery Projects

Tutorial AM4: A Practical Introduction to Reproducible Computational Workflows

Sunday, July 21, 9:00 am - 1:00 pm

Room: Shanghai 1/2 (Ground Floor)

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Peter W. Rose, Director, Structural Bioinformatics Lab, San Diego Supercomputer Center, UC San Diego, United States
Tim Head, Project member Jupyter Hub & mybinder.org and Wild Tree Tech, Brugg, Switzerland
Fergus Boyles, Oxford Protein Informatics Group, Department of Statistics, University of Oxford, United Kingdom
Fergus Imrie, Oxford Protein Informatics Group, Department of Statistics, University of Oxford, United Kingdom


This hands-on tutorial teaches participants the key requirements and practical skills to setup a reproducible and reusable computational research environment. The tutorial is intended for Python and R users, and anyone interested in using Jupyter Notebooks, which supports over 50 programming languages. We will work through a few bioinformatics use cases step by step, including biological visualization and machine learning. We will then share the results using Binder (mybinder.org), a publicly hosted environment to run Jupyter Notebooks in a fully reproducible and interactive manner. We also cover collaborative development practices. After attending this workshop, participants should be able to set up their own projects by applying the principles and techniques learned and publish reproducible research protocols.


This course is designed for everyone who would like to gain hands-on experience in setting up reproducible computational environments to their own projects. Introductory level Python skills are required and R skills are optional.


Create a GitHub account
Install miniconda/anaconda
Attendees are required to provide their own laptop.

Maximum Participants: 40

Schedule Overview
9:00 - 9:30 am Introduction
  • Best practices for reproducible research
  • Run example from mybinder.org
9:30 - 9:45 am
Hands-on Session: Set up your Conda environment
9:45 - 10:15 am
Hands-on Session: Create and run Jupyter Notebooks
  • Jupyter Notebook/Lab basics
  • Visualize biological data using plugins (3D structures, sequences, networks)
10:15 - 11:00 am
Hands-on Session: Open-source your code and collaborate using GitHub
  • GitHub GUI
  • Command line
  • Merging, branching, and version control
11:00 - 11:15 am Coffee Break
11:15 - 11:45 pm
Hands-on Session: Make your code reproducible by anyone, anywhere
  • Share Jupyter Notebook or RStudio on mybinder.org
  • Share single Jupyter Notebook on Google Colaboratory
11:45 - 12:45 pm
Hands-on Session: Work on provided example projects or your own project
  • Show and tell of what you did
12:45 - 1:00 pm Wrap Up

Tutorial PM5: Biomarker discovery and machine learning in large pharmacogenomics datasets

Sunday, July 21, 2:00 pm - 6:00 pm

Room: Kairo 1/2 (Ground Floor)


Arvind Singh Mer, Princess Margaret Cancer Center, University of Toronto, Canada
Zhaleh Safikhani, Princess Margaret Cancer Center, University of Toronto, Canada
Petr Smirnov, Princess Margaret Cancer Center,Vector Institute, University of Toronto, Canada
Benjamin Haibe-Kains, Princess Margaret Cancer Center,Vector Institute,Ontario Institute for Cancer Research, University of Toronto, Canada


Over the past decade there has been an explosion in the availability of massive datasets combining drug screening with high-throughput molecular profiling in cancer model systems. These datasets have become a rich community resource which can be leveraged for biomarker discovery, in-silico validation, drug repurposing, drug method of action prediction, and to train statistical machine learning models for drug response prediction. However, this data poses unique challenges during analysis and requires methods that are robust to the noise inherent in the drug sensitivity assays. Furthermore, irreproducibility of some findings across studies strongly motivates integrative analysis across studies. Fortunately, tools have been developed implementing bioinformatics and machine learning methods designed specifically for the analysis of pre-clinical pharmacogenomics data.

In this tutorial, participants will become familiar with common preclinical cancer models (such as cell-line, patient derived xenografts and organoids) and publicly available large pharmacogenomics datasets. Next, in the hands on session, they will be introduced to the tools and packages published for analysis of these datasets, with a focus on tools written in R. Furthermore, after becoming familiar with the challenges posed by the noise in the pharmacological assays observed in high-throughput pharmacogenomics, participants will gain hands on experience using these datasets for the purpose of biomarker discovery and validation as well as building machine learning models predictive of drug response. A focus will be on translational research, validating discoveries from in vitro datasets using in vivo pharmacogenomic and clinical datasets. The hands on sessions will be conducted primarily in R and RStudio.


This tutorial is open to all participants who are interested in mining large cancer pharmacogenomic data for precision oncology. For hands-on sessions, some prior experience with the following is required:

  • Bioinformatics analysis using R
  • Knowledge of high throughput genomic data (gene expression, mutation etc.)
  • Familiarity with basic machine learning concepts

Participants are required to bring a laptop with R and RStudio installed. Installation instructions will be provided in the weeks preceding the tutorial.

Maximum Participants: 60

Schedule Overview
2:00 - 2:30 pm Introduction to high-throughput pharmacogenomics
  • Quick introductions: presenters & audience
  • Preclinical models in cancer: cell-lines, organoids, patient derived xenograft (PDXs), patient derived cells
  • Sensitivity and perturbation experiments in pharmacogenomics
    • Common experimental designs
2:30 - 3:00 pm Pharmacogenomics data-sets
  • Publically available in-vitro and in-vivo datasets
    • (CCLE, GDSC, L1000, PDX Encyclopedia)
  • Web Based Exploratory Resources
    • Cell Minder CDB, PharmacoDB
3:00 - 4:00 pm Hands-on Session: Tools for pharmacogenomics analysis
  • GDSCTools
  • GRCalculator
  • PharmacoGx
  • Xeva
4:00 - 4:15 am Coffee Break
4:15 - 4:40 pm Statistics and machine learning on pharmacogenomics data
  • Evaluating reproducibility and handling noise in pharmacogenomics data
  • Meta-analysis across studies
  • Applications of machine learning for drug ranking and predictive modeling
4:40 - 5:10 pm Hands-on Session: Finding anticancer drug biomarkers
  • Univariate biomarker discovery
  • Validating known biomarkers
  • Integrative analysis across in-vitro and in-vivo data
5:10 - 5:40 pm Hands-on Session: Machine learning using pharmacogenomics data
  • Building machine learning models to predict drug response
  • Personalized drug ranking
  • Testing models on clinical data
5:40 - 6:00 PM Q&A and Tutorial wrap up

Tutorial PM6: Visualization of Large Biological Data

Sunday, July 21, 2:00 pm - 6:00 pm

Room: Sydney (2nd Floor)


Prof. G. Elisabeta Marai, Ph.D., University of Illinois at Chicago, United States
Prof. Dr. Kay Nieselt, Center for Bioinformatics, University of Tübingen, Germany
Jun.-Prof. Dr. Michael Krone, Center for Bioinformatics, University of Tübingen, Germany


The aim of this tutorial is to familiarize the participants with modern visual analytics methodologies applied to biological data and to provide simple hands-on training. Questions such as what is data visualization, what is visual analytics, and how can large-scale biological data be visualized to gain insight will be addressed, so that hypotheses can be generated or explored and further targeted analyses can be defined. The tutorial will cover the basics that are necessary to create visualizations for biological data. This includes a general introduction to visualization, basics of visual design, and fundamentals of human color perception. Based on these generally applicable principles, various examples of visualizations and visual analysis tools for biological data that adhere to the aforementioned fundamentals and best practices will be presented and discussed. A specific focus will be laid on visualization approaches of large-scale (omics) data. Finally, attendees will have the opportunity to get first hands-on experience in creating their own interactive web-based visualization application using modern web technologies like HTML5, JavaScript, and D3.

Topics Include

  • Digital/Electronic visualization of data
  • Understanding color
  • Visual Design Principles
  • Examples of visualization of biological data
  • Challenges of large-scale biological data visualization
  • Introduction to web-based visualization for biological data

The tutorial is designed for anyone who has no or only little prior knowledge of data visualization and wants to learn the basics (beginner level). The course provides useful background material on data visualization principles, but the focus is on methods and tools for visualization of next-generation sequencing data, other omics data, and network data. Previous knowledge in programming is a plus for the hands-on part, but not required to participate. Attendees that want to participate actively in the hands-on should bring a laptop with a text editor and a modern web browser (passive participation is also possible).

Maximum Participants: 60

Schedule Overview
2:00 - 2:15 pm Welcome & Introduction to tutorial structure
2:15 - 2:45 pm What is (electronic) visualization - Understanding color
  • Color perception and luminance
  • Mapping data to color
2:45 - 3:30 pm Visual design principles
  • Tufte’s design principles
  • Shneiderman’s mantra
  • Small multiples etc.
3:30 - 4:00 pm Introduction to Biological Data Visualization
  • Topics in BioVis (including examples)
  • Visualization of sequences, macromolecules, omics data, biological networks
4:00 - 4:15 pm Coffee Break
4:15 - 4:45 pm Tools and Software for Biological Visualization
  • Specific tools for visualizing large-scale biological data
4:45 - 5:00 pm Introduction to HTML5 and JavaScript
  • Hands-on: basics web application development
5:00 - 6:00 pm Introduction to D3
  • Hands-on: generating a simple interactive, web-based visualization

Tutorial PM7: Tools for reproducible research

Sunday, July 21, 2:00 pm - 6:00 pm

Room: Shanghai 1/2 (Ground Floor)

Conda Cheat Sheet
Snakemake Live Demo
Snakemake Talk Slides
Tools for reproducible research

Johannes Koester - Group Leader, Institute of Human Genetics, University Hospital Essen, University of Duisburg-Essen
Bjoern Gruening - Bioinformatician, Uni-Freiburg, Freiburg Germany
Devon Ryan - Bioinformatician, Max Planck Institute for Immunobiology and Epigenetics, Freiburg Germany


The typical data analyst must simultaneously juggle multiple projects, each having its own duration and software requirements. As few analysts have any formal training on structuring or even writing the code necessary to perform an analysis, it is unsurprising that the iterative analytic process can produce a wide assortment of almost identically named files (e.g., “final_results.txt”, “final_results.version2.txt”, “final_results.really_final.txt”), all with unclear origins and produced with a hodge-podge of similarly poorly named scripts. The near impossibility of tracing a results file to the exact process that produced it creates untold difficulties both when it comes time to publish results as well as when planning subsequent experiments months or years later (afterall, which of the “final_results” files was really the “right one”?). These issues are further compounded by software paths and other similar assumptions being hard-coded into scripts, preventing easy analysis replication elsewhere. Performing analyses in a reproducible and traceable manner is clearly needed to combat such problems.

In this hands-on tutorial, we demonstrate how Conda can be used to deploy specific software versions easily, reproducibly, and without administrator credentials. Moreover, we demonstrate how Conda’s ability to create isolated software environments helps to avoid side-effects between different analyses or different steps of the same analysis. Attendees will also learn how to create conda recipes themselves, so they can contribute new packages to projects such as Bioconda. We further demonstrate how Snakemake can be used in combination with Conda and Containers to create reproducible analysis workflows and execute them on any platform from workstations to clusters and the cloud. Finally, using snakePipes as an example, we demonstrate how Conda and Snakemake can be used to define reproducible and flexible workflows for complex genomics analysis.


Beginners, Intermediates, Core-Facility Staff
Expected audience should have basic familiarity with python, git and the command line.


Laptops with Linux or MacOS
Pre-installed Miniconda - install via miniconda : https://conda.io/miniconda.html

Maximum Participants: 40

Schedule Overview

2:00 - 2:10 pm Installing conda and snakeMake
2:10 - 2:30 pm Intro to conda and bioconda (slides)
2:30 - 3:30 pm Hands-on Session: creating conda envs and installing packages from bioconda repo
  • This practical would require installing hisat, samtools and deeptools via bioconda
3:30 - 4:00 pm Hands-on Session: writing conda recipes
  • Topics in BioVis (including examples)
  • Visualization of sequences, macromolecules, omics data, biological networks
4:00 - 4:15 am Coffee Break
4:15 - 4:35 pm Intro to snakemake
  • Specific tools for visualizing large-scale biological data
4:35 - 6:00 Hands On Session: Writing a snakemake workflow wrapper for mapping, indexing and creating coverage files

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