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


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    open dialogue and collaboration to solve problems and identify opportunities

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    connect with ISCB worldwide

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    a unique opportunity for industry

Professional Development, Training and Education

ISCBintel and Achievements


Bioinformatics as the main protagonist of the microbiome field

Speaker: Dr. Daniel Almonacid

The human microbiome, the microorganisms that live in and on the human body, is one of the most diverse ecosystems on Earth. Our mission at uBiome is to advance the science of the microbiome and make useful products that improve human life. The company’s technological platform is based on the largest microbial dataset in the world (over 300,000 samples), allowing us unprecedented coverage of the microbial diversity across multiple sites of the human body. Using nucleotide sequencing, including our own approach called Precision Sequencing TM, bioinformatics, and machine learning methods, we are developing precision medicine solutions based on microbiome information, empowering doctors, patients, and citizen scientists to improve their quality of life.

Our current portfolio goes from tools for citizens scientists to study their own microbial communities (Explorer TM), to screening tests that can inform doctors of conditions associated with intestinal health (SmartGut TM) and vaginal health (SmartJane TM). The information generated with these analyses allow us continuous improvement of these products.  Additionally, we continually monitor the scientific literature to add new targets as well as novel correlations in our tests. Moreover, the sequencing information combined with the metadata collected from patients has allowed us to discover novel correlations between the microbiome and host conditions, some of which we have been able to understand mechanistically. This knowledge has presented uBiome with the opportunity to in silico design and test drugs that target the microbiome (drugs for bugs), drugs that are naturally produced by the microbiota to modulate the host (drugs from bugs), in addition to identifying and testing potential live biotherapeutics for different health conditions (bugs as drugs).

In this talk I will provide an overview of the work that we are currently doing at uBiome, emphasizing the use of reproducible approaches (both in the laboratory and bioinformatics).  This talk will also highlight the road that uBiome is taking from the research and implementation of clinical tests, toward the development of therapeutics products, having bioinformatics as the main protagonist.

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links in this page: Bioinformatics EducationDevelopment and application of tools for microbiome studies | Integrative approaches for RNA biology | Precision Medicine | Workshop on Docker | UCSC Genome Browser Workshop | Higher Understanding with Lower Dimensions

Special Sessions at GLBIO 2019

Many of the sessions listed below will consider submissions for contributed talks, including full papers in addition to our regular track. All such papers should be submitted through EasyChair, by the relevant GLBIO 2019 submission deadline. Please contact the organizer of the individual sessions for more information. 

Bioinformatics Education

Accepting abstracts only for oral presentations through EasyChair.
The GLBIO 2019 Special Session on Bioinformatics Education seeks to create a platform for presentation and discussion on the topic of bioinformatics education broadly defined.  The session will mix invited talks from leaders in bioinformatics education with contributed talks and posters from the community.  The intention is to provide a broad representation of perspectives, goals, and topics engaging the bioinformatics education community.  The session is soliciting short abstracts for proposed talks or posters.  Topics of interest include but are not limited to

  • bioinformatics curriculum development for bioinformatics professionals, life scientists, healthcare professionals, K-12 students, or other communities
  • education policy and practices
  • pedagogical strategies or experiences
  • community education resources
  • outreach and diversity efforts
  • case studies in bioinformatics education

The session will conclude with a Panel Discussion and Community Forum organized around the theme of identifying the aims for Bioinformatics Education community over the next five years.

Organizer(s): This email address is being protected from spambots. You need JavaScript enabled to view it.
Web page: https://qubeshub.org/community/groups/glbioedu

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Development and Application of Tools for Microbiome Studies

Accepting abstracts only for oral presentations through EasyChair.
Microbiome research is a rapidly growing area of science. Over the last decade, the number of microbiome sequencing studies has expanded enormously, exploring the intricate communities of microbes within soil, water, the built environment, and the human body, amongst others. There is a need to ensure that adequate expertise and infrastructure is in place to meet the challenge of analyzing the data generated as well as a robust and reliable framework for interpreting the data. This session will cover (1) different computational and statistical methods for analyzing microbiome data sets, and (2) investigations of microbiomes uncovering new insight into functions and dynamics.

Organizers:This email address is being protected from spambots. You need JavaScript enabled to view it. and This email address is being protected from spambots. You need JavaScript enabled to view it.
Website: https://microbiome.wisc.edu/events/glbio2019/

Integrative approaches for RNA biology

Accepting full papers and abstracts for oral presentations through EasyChair.
Post-transcriptional processes play a key role in eukaryotic gene regulation, yet it is not well understood how such processes contribute to the level of functional RNAs within the cell. Such regulation is orchestrated through a variety of mechanisms acting on all aspects of RNA metabolism, including pre-mRNA splicing, stability, polyadenylation, localization, editing, modification, and translation. The diversity of these mechanisms as well as the the increase in RNA-related high-throughput sequencing approaches highlight the need for research into new computational tools addressing post-transcriptional gene regulation.

This session focuses on research findings and methods related to the sequence and structure of RNA as well as its post-transcriptional gene regulation. These include but are not limited to the analysis of transcriptomics and protein-RNA interaction datasets, novel methods for interpretation of single-cell transcriptomes and approaches for RNA structure prediction. The session comprises of invited and selected talks, as well as a workshop on analyses of RNA splicing from high-throughput transcriptome-wide sequencing, and identification of protein/RNA binding sites from CLIP-seq data. The audience is expected to have a basic understanding and experience with computational biology, but not to be experts on RNA biology or the current computational and experimental approaches used in RNA research.

Organizer(s): This email address is being protected from spambots. You need JavaScript enabled to view it. and This email address is being protected from spambots. You need JavaScript enabled to view it.
Website: http://www.iupui.edu/~jangalab/rss_glbio19/

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Precision Medicine

Accepting abstracts only for oral presentations through EasyChair.
Advances in computing have led to a data-driven revolution in biology and promise to guide progress in precision medicine. This session will explore the spectrum of challenges and opportunities in precision medicine, including genomics, electronic health record analytics, and drug discovery. Confirmed speakers apply systems approaches to disease, biomarker, and other complex trait prediction by building computational models that leverage and integrate similarity in genetic, transcriptomic and other omics-level data. The intended audience for this session includes those interested in integrative genomics, statistical modeling, machine learning, and human population genetics applications in medicine.

Organizers: This email address is being protected from spambots. You need JavaScript enabled to view it., This email address is being protected from spambots. You need JavaScript enabled to view it., and This email address is being protected from spambots. You need JavaScript enabled to view it.
Website: http://glbio19-precisionmedicine.strikingly.com/

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Workshop on Docker

Half-day Tutorial.  Will not accept submissions.
This workshop aims to be the next step in reproducibility for computational biologists and will focus on using and developing software containers. We will review best practices for practicing reproducible research and teach participants how to use Docker, a popular software for containerization (which can also be used by Singularity, another commonly used containerization platform). Using containers can help overcome the many interoperability and dependency issues often encountered when distributing or installing software. Docker images used conjunction with continuous integration is considered to be a possible solution for the reproducibility crisis plaguing research at large. Similar to a Carpentries workshop, a majority of the proposed workshop will be hands-on live-coding. Workshop attendees are expected to have familiarity with the Unix shell and git/github, bring their own laptops, and follow along with the training.

Organizers: This email address is being protected from spambots. You need JavaScript enabled to view it.
Website: https://uw-madison-datascience.github.io/2019-05-19-glbio-docker/

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UCSC Genome Browser Workshop

Half-day Tutorial.  Will not accept submissions.
As the flood of data from high-throughput sequencing threatens to overwhelm scientists with data generated within individual labs and distributed on the web, visualization becomes even more important.  The UCSC Genome Browser has developed tools that assist in understanding the import of data and provides a platform to view data from multiple sources together.  The endpoint of a data pipeline need not be statistical or tabular.  A potent visualization tool such as the Browser can add an important dimension to data analysis.

This UCSC Genome Browser workshop will offer a tour through recent data releases and new features.  New data include a pre-computed CRISPR guides track on human, mouse and other genome assemblies, a mapping of transcript-specific GTEx expression data, a Gene Interactions track which collects data from multiple curated databases and from data-mining of the literature, and gnomAD.  Recently added features include multi-region mode, which allows for display of exons only or of any regions specified by the user, whether contiguous in the genome or not and Track Collections, which allows co-configuration of multiple tracks and new data formats for loading your data (interation and barChart).

Organizers:  This email address is being protected from spambots. You need JavaScript enabled to view it. and This email address is being protected from spambots. You need JavaScript enabled to view it.
Website: https://users.soe.ucsc.edu/~kuhn/workshops/glbio2019/ 


Higher Understanding with Lower Dimensions
Tutorial on Dimensionality Reduction Methods for Biomedical Data
Student Run Event

Evening Tutorial.  Will not accept submissions.
Many real-world datasets are high-dimensional in their raw form but have low-dimensional structure, groupings, or representations. Dimensionality reduction methods have been applied to various biomedical datasets with the aim of cancer subtype extraction from mutational signatures, genotype-to-phenotype mapping, gene regulatory program identification, unsupervised multi-omics data integration, and cell differentiation trajectory visualization. This workshop will provide an opportunity to explore a handful of powerful dimensionality reduction methods: matrix factorization, PCA/LDA/GDA, t-SNE and UMAP, diffusion map, and autoencoders. All demos and exercises will use real biomedical datasets from single cell RNA-seq, Hi-C, and de-identified medical records.

Organizers: Brittany Baur, Erika Da-Inn Lee, Xiaotong Liu and Henry Neil Ward
Website: https://dimension-reduction.github.io/

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Gold Sponsors

Bronze Sponsors

Copper Sponsors

General Sponsors

Lunch N' Learn Exhibitors


Click thumbnail to view pdf of Exhibitors map

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ISCB Town Hall

Topic: ISCB Town Hall
Date: Sunday, July 8 (12:45 PM - 1:45 PM)
Room: Columbus IJ

Join us at the ISCB Town Hall meeting on Sunday, July 8, from 12:45 PM - 1:45 PM to learn more about the latest programs, initiatives, and conferences. This is also your chance to help shape the future of ISCB by providing feedback and suggestions. The Town Hall will close with a celebration of achievement with the announcement of the Student Council Symposium award winners.


Top Reading Papers 2016 - 2017 - RECOMB/ISCB Conference on Regulatory and Systems Genomics, with DREAM Challenges

As selected at RECOMB/ISCB Regulatory systems Genomics 2017
(Papers are listed alphabetically by title.  Due to a draw, this year's list contains 11 papers.)

A prior-based integrative framework for functional transcriptional regulatory network inference, Siahpirani A, Roy S. Nucleic Acids Res 45(4):e21

chromVAR: inferring transcription-factor-associated accessibility from single-cell epigenomic data, Schep AN, Wu B, Buenrostro JD, Greenleaf WJ. Nat Methods 14(10):975-978

Denoising genome-wide histone ChIP-seq with convolutional neural networks, Koh PW, Pierson E, Kundaje A. Bioinformatics 33(14):i225-i233

Genome-scale high-resolution mapping of activating and repressive nucleotides in regulatory regions, Ernst J, Melnikov A, Zhang X, Wang L, Rogov P, Mikkelsen T, Kellis M. Nat Biotechnol 34(11):1180-1190

Genome-Wide Association between Transcription Factor Expression and Chromatin Accessibility Reveals Regulators of Chromatin Accessibility, Lamparter D, Marbach D, Rueedi R, Bergmann S, Kutalik Z. PLoS Comput Biol 13(1):e1005311

Identification of novel prostate cancer drivers using RegNetDriver: a framework for integration of genetic and epigenetic alterations with tissue-specific regulatory network, Dhingra P, Martinez-Fundichely A, Berger A, Huang FW, Forbes AN, Liu EM, Liu D, Sboner A, Tamayo P, Rickman DS, Rubin MA, Khurana E. Genome Biol 18:141

Is a super-enhancer greater than the sum of its parts?, Dukler N, Gulko B, Huang YF, Siepel A. Nat Genet 49:2-3

Quantifying the impact of non-coding variants on transcription factor-DNA binding, Zhao J, Li D, Seo J, Allen AS, Gordan R. Res Comput Mol Biol 10229:336-352

Reconstruction of enhancer-target networks in 935 samples of human primary cells, tissues and cell lines, Cao Q, Anyansi C, Hu X, Xu L, Xiong L, Tang W, Mok MTS, Cheng C, Fan X, Gerstein M, Cheng ASL, Yip KY. Nat Genet 49(10):1428-1436

SMiLE-seq identifies binding motifs of single and dimeric transcription factors, Isakova A, Groux R, Imbeault M, Rainer P, Alpern D, Dainese R, Ambrosini G, Trono D, Bucher P, Deplancke B. Nat Methods 14(3):316-322

Transcription factor family-specific DNA shape readout revealed by quantitative specificity models, Yang L, Orenstein Y, Jolma A, Yin Y, Taipale J, Shamir R, Rohs R. Mol Syst Biol 13(2):910


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Links within this page:
Plane | Train | Bus | Car

Whether you live across the Hudson or across the Atlantic, getting to NYC is easy. If you’re coming from outside the United States, check this page for visa information.

See below for the best ways to reach the five boroughs from anywhere in the world.

By plane If you’re coming from far away, you’ll probably want to fly into one of the New York City area’s major airports. There are a number of hotels conveniently located near the City’s airports.

By Plane

Below, you'll find a list of NYC-area airports, along with the best ways to get from those airports to Manhattan. There are more than a hundred air carriers traveling to NYC from all over the country and the world, including American Airlines, Delta, JetBlue and United.

Air travelers to New York City may arrive at John F. Kennedy International Airport (JFK) or LaGuardia Airport (LGA), both in Queens, or Newark Liberty International Airport (EWR) in neighboring New Jersey. LaGuardia primarily serves domestic destinations, and also offers flights to select Canadian and Caribbean destinations. Kennedy and Newark both serve domestic and international destinations. Visitors can reach Manhattan from all three airports by using taxis, buses, subways and/or commuter trains. Other metropolitan-area airports include Stewart International Airport (SWF), Westchester County Airport (HPN) and MacArthur Airport (ISP). For those interested, there are a number of hotels conveniently located near the City's airports.

John F. Kennedy International Airport (JFK)
Jamaica, Queens, NY 11430

New York's largest airport serves more than 80 airlines, most of which are international. It is approximately 15 miles from Midtown Manhattan. Here's how to get to Midtown Manhattan from JFK:

  • Taxi: $52.50 flat fare (non-metered), plus bridge and tunnel tolls and gratuity; 30 to 60 minutes to Midtown Manhattan, depending on traffic and road conditions. For more information, call 212-NYC-TAXI or visit the Taxi and Limousine Commission website.
  • AirTrain JFK: $5 (children under 5 are free); AirTrain links the airport to the subway and Long Island Rail Road. AirTrain also offers free service between points in the airport.
  • Subway: one ride (in addition to AirTrain fare) from the A subway stop at the Howard Beach/JFK Airport station or the E, J or Z subway stop at the Sutphin Blvd./Archer Ave./JFK Airport station; 60 to 75 minutes to Midtown Manhattan.
  • Long Island Rail Road (LIRR): $7.25–$10 (children under 5 are free), depending on time of day (in addition to AirTrain fare) for the trip between LIRR's Jamaica Station and Penn Station; on Saturday and Sunday, the fare is $4.25. The trip is 20 minutes to Midtown Manhattan (not including AirTrain ride).
  • City bus: For details, visit tripplanner.mta.info.
  • Shuttle bus: NYC Airporter, Go Airlink NYC and SuperShuttle.
  • Private car service: See this list of providers.
  • Car rental: Companies at JFK include Avis, Budget, Dollar, Enterprise, Hertz and National.

LaGuardia Airport (LGA)
Jackson Heights, Queens, NY 11371

This is New York's second-largest airport, with nearly 20 airlines serving mostly domestic destinations, as well as Canada and the Caribbean, from four passenger terminals. LaGuardia is on the northern shore of Queens, directly across the East River (about 8 miles from Midtown Manhattan). Here's how to get to Midtown Manhattan from LaGuardia:

Newark Liberty International Airport (EWR)
Newark, NJ 07114

Newark Airport, with more than 30 airlines (many of which are international), is across the Hudson River from New York City—16 miles from Midtown Manhattan. Here's how to get to Midtown Manhattan from Newark Liberty:

  • Taxi: Traveling to Manhattan, metered fare; approximately $50 to $75, plus bridge and tunnel tolls and gratuity; 45 to 60 minutes to Midtown Manhattan. During weekday rush hours (6–9am and 4–7pm) and on weekends (Saturday–Sunday, noon–8pm), there is a $5 surcharge for travel to anywhere in New York State except Staten Island. When traveling to the airport from Midtown Manhattan, service is via New York City’s regulated yellow taxis. Metered fares range $69–$75, plus a $17.50 surcharge in addition to tolls and gratuity.
  • AirTrain Newark: Costs vary by destination. AirTrain links to the airport via NJ Transit and Amtrak's Newark (or EWR) train station; 45 to 90 minutes to Midtown Manhattan, requiring a transfer from the AirTrain line to the NJ Transit line (be sure to keep your ticket after using it to exit the AirTrain station, as it is also used for the NJ Transit fare) or Amtrak. AirTrain also offers free service between points in within the airport complex, including hotels and parking. Look for signs marked “Monorail/AirTrain Link” (do not follow signs for Ground Transportation).
  • Shuttle bus: NYC Airporter, Go Airlink NYC, Olympia Airport Express and SuperShuttle.
  • Private car and limousine service: Dial 7, Carmel and Uber.
  • Car rental: Companies at Newark include Avis, Budget, Dollar, Enterprise, Hertz and National.

Stewart International Airport (SWF)
New Windsor, NY 12553

Stewart International Airport is 60 miles north of New York City. Here's how to get to Midtown Manhattan from Stewart:

  • Bus/train: Leprechaun Lines runs a $1 shuttle bus on their Newburgh-Beacon-Stewart commuter line, which connects to the Beacon train station. There, use Metro-North Railroad for direct service to Grand Central Terminal ($16 off-peak, $21.25 peak); 70 to 90 minutes to Midtown Manhattan.

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By Train

New York City has two main rail stations in Midtown: Grand Central Terminal (on the east side) and Penn Station (on the west side). Each is also served by numerous bus and subway lines. Grand Central is served by Metro-North Railroad, which goes to NYC suburbs in New York and Connecticut. Penn Station is served by the following: Long Island Rail Road, a commuter railroad serving Long Island; Amtrak, the US national passenger railroad, serving many points throughout the country; and NJ Transit, a commuter line serving points in New Jersey.

  • Rail Terminals
    • Grand Central Terminal
      Park Avenue and East 42nd Street (between Lexington and Vanderbilt Avenues)
      Grand Central is the main terminal for Metro-North Railroad services. Subway lines here include the 4, 5, 6, 7 and S (shuttle between Grand Central and Times Square). For MTA bus details, visit tripplanner.mta.info.

      Aside from being a transit hub, Grand Central is also a landmark and an attraction unto itself. The Main Concourse boasts an immense 88,000 square feet of space, and on sunny days is bathed in light from its giant arching windows. Grand Central's 12-story ceiling is painted with stars and gilded zodiac constellations. Not only might Grand Central be the globe's most beautiful train station, the 49-acre terminal is also one of the world's largest. There are numerous shops of all varieties here, including an Apple Store, MAC Cosmetics and Tumi. The dining concourse on the lower level features a wide selection of eateries, and in Grand Central Market, fresh and prepared foods—ranging from baked goods to gourmet teas—are available.
    • Penn Station
      Seventh to Eighth Avenues, between West 31st and West 33rd Streets
      Penn Station is the main terminal for Long Island Rail Road, and a terminal for Amtrak and NJ Transit. Subway lines here include the 1, 2, 3, A, C and E. For MTA bus details, visit tripplanner.mta.info.

      Penn Station's main concourse features information booths, restaurants, waiting rooms and public restrooms to accommodate the thousands of passengers who pass through the terminal each day. In 2016, the new West End Concourse will open providing additional access to the station from 8th avenue. Car rental offices are nearby.
  • Rail Services
    • Amtrak
      800-872-7245, 212-630-6400
      Amtrak is the national passenger railroad of the United States. New York City's Penn Station is their busiest station in the nation, serving hundreds of thousands of passengers each year. The company offers numerous packages and deals, including special passes allowing international visitors to make multiple stops throughout the country.
    • Long Island Rail Road (LIRR)
      This commuter railroad operates out of Penn Station and serves 124 stations in Nassau County, Suffolk County, Queens, Brooklyn and Manhattan, transporting some 81 million customers each year. Destinations include the Belmont Park racetrack, Citi Field, Jones Beach, the Hamptons and Montauk.
    • Metro-North Railroad
      212-532-4900, 877-690-5114
      The second-largest commuter train line in the United States, Metro-North operates out of Grand Central Terminal. The historic roots of the operation go back to 1832, when the enterprise was known as the New York & Harlem Railroad, a horsecar line in Lower Manhattan. Today, with 775 miles of track, Metro-North goes to 121 stations (in seven New York State counties—Dutchess, Putnam, Westchester, Rockland, Orange, Bronx and New York (Manhattan)—and Connecticut's New Haven and Fairfield counties).
    • NJ Transit
      973-275-5555, TTY 800-772-2287
      This rail system features 12 lines in three divisions (Hoboken, Newark and the Atlantic City Rail Line) with frequent service throughout New Jersey (Atlantic City and the Jersey Shore are popular stops) and New York (Rockland and Orange counties)—and, of course, into and out of New York City via Penn Station. For schedules and fares, visit the NJ Transit website.
    • PATH (Port Authority Trans Hudson)
      The PATH provides rapid transit between several stops in New York City, along with locations in Newark, Harrison, Jersey City and Hoboken in New Jersey. Air travelers can connect to the PATH from Newark Liberty International Airport. The service operates from the Penn Station in Newark (not the same as Manhattan's Penn Station) to Lower and Midtown Manhattan. The PATH's 33rd Street station (on Sixth Avenue, in Herald Square) in Manhattan is one avenue from Amtrak, Long Island Rail Road and NJ Transit trains at Penn Station.

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By Bus

There are a number of affordable, convenient bus lines that travel to New York City from around the United States and parts of Canada. These include BoltBus, Megabus and Greyhound.

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By Car

Use Google Maps for driving directions to New York City. Also, make sure you know where to park: you may want to use an app like SpotHero to find and compare parking spots and locations.

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RSG and DREAM General Questions

Bel Hanson, Conference Manager
Tel: 1-315-767-5568

Source: NYC The Official Guide

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Ross Cagan, PhD

Ross Cagan, PhD
Senior Associate Dean for the Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, USA

Aravinda Chakravarti, PhD
Professor of Medicine, Pediatrics, Molecular Biology & Genetics, and Biostatistics and Neuroscience, New York University School of Medicine, USA
Aravinda-Chakravarti, PhD
Itai Yanai, PhD Itai Yanai, PhD
Director, Institute for Computational Medicine
Professor, Biochemistry and Molecular Pharmacology
New York University, School of Medicine, USA

Peter Kharchenko, PhD
Assistant Professor of Biomedical Informatics, Harvard University, USA

Peter Kharchenko, PhD
Daphne Koller, PhD

Daphne Koller, PhD
Stanford University, USA

Xiaole Shirley Liu, PhD
Professor of Statistics, Biostatistics, and Computational Biology, Harvard University, Dana-Farber Cancer Institute, USA

Xiaole Shirley Liu, PhD
Miriam Merad, PhD

Miriam Merad, PhD
Icahn School of Medicine at Mount Sinai, USA

Ana Pombo, PhD
Berlin Institute for Medical Systems Biology, at the Max Delbrueck Center, Germany

Ana Pombo, PhD
Bing Ren, PhD

Bing Ren, PhD
Professor of Cellular and Molecular Medicine, UC San Diego, USA

Adam Siepel, PhD
Professor, Watson School of Biological Sciences
Chair, Simons Center for Quantitative Biology
Cold Spring Harbor Laboratory, USA
Adam Siepel, PhD

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Keynote Bios

Ross Cagan, PhDRoss Cagan, PhD
Senior Associate Dean for the Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, USA

Ross L. Cagan, PhD, is Professor of the Department of Developmental and Regenerative Biology and Director of the Center for Personalized Cancer Therapeutics. He is also Senior Editor of Disease Models and Mechanisms and co-founder of Medros Inc.

Dr. Cagan's laboratory focuses on the use of Drosophila to address disease mechanisms and therapeutics, primarily for cancer. Their work helped validate vandetanib as a therapeutic for Medullary Thyroid Carcinoma, combined Drosophila genetics and medicinal chemistry to develop a new generation of lead compounds that emphasize "balanced polypharmacology", and identified novel mechanisms that direct transformed cells into the first steps towards metastasis.

Combining these basic research approaches, Dr. Cagan has established the Center for Personalized Cancer Therapeutics, in which new tools including 'personalized Drosophila avatars' are developed and used to screen for personalized drug cocktails. Working with co-directors Marshall Posner and Eric Schadt, the CPCT is designed to treat patients with drug combinations that best address the tumor's complexities.

A key challenge in many diseases including cancer and neurodegenerative diseases is their complexity. Genomic changes and interactions within a whole body setting can lead to emergent properties that present significant therapeutic challenges. In our DREAM challenge, the community has worked to develop new approaches to developing therapeutic candidates that embrace complexity.

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Aravinda-Chakravarti, PhDAravinda Chakravarti, PhD
Professor of Medicine, Pediatrics, Molecular Biology & Genetics, and Biostatistics and Neuroscience, New York University School of Medicine, USA

Dr. Aravinda Chakravarti is Professor of Medicine, Pediatrics, Molecular Biology & Genetics, and Biostatistics and Neuroscience at the New York University School of Medicine, and inaugural Director of its Center for Human Genetics and Genomics. He was the 2008 President of the American Society of Human Genetics, and has been elected to the U.S. National Academy of Science, the U.S. National Academy of Medicine, the Indian National Academy of Sciences, and the Indian Academy of Sciences. He has been a key participant and architect of the Human Genome, HapMap, and 1000 Genomes project. His research is aimed at genome-scale analysis of humans and computational analysis of gene variation and function to understand the molecular genetic basis of complex human disease. For his contributions to human genetics and genomics he was awarded the William Allan Award in 2013 by the American Society of Human Genetics.  Aravinda Chakravarti received his doctoral degree in human genetics in 1979 and started his faculty career at the University of Pittsburgh (1980–1993), was the James H. Jewell Professor of Genetics at Case Western Reserve University (1994-2000), and the inaugural Director and Henry J. Knott Professor of the McKusick-Nathans Institute of Genetic Medicine at Johns Hopkins (2000-2007). He is one of the founding Editors-in-Chief of Genome Research and Annual Reviews of Genomics & Human Genetics, and serves on the boards of numerous private Institutes and charities, international journals, academic societies, the NIH and biotechnology companies.

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Peter Kharchenko, PhDPeter Kharchenko, PhD
Assistant Professor of Biomedical Informatics, Harvard University, USA

Peter Kharchenko received a PhD in biophysics at Harvard University, studying gene regulation and metabolic networks under the advisement of George Church. He then completed a four-year postdoctoral fellowship in computational biology and genomics in the laboratory of Peter Park. His lab specializes in development of statistical and computational methods for analysis of genomic data, including single-cell genomics,  as well as application of these approaches to studies of normal and cancer tissue organization.

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Daphne Koller, PhD

Daphne Koller, PhD
Stanford University, USA

Daphne Koller (PhD) is the CEO and Founder of insitro, a startup company that aims to rethink drug development using machine learning. She also co-founded and led Coursera, the largest platform for massive open online courses (MOOCs). Daphne was the Rajeev Motwani Professor of Computer Science at Stanford University, where she served on the faculty for 18 years. She has also been the Chief Computing Officer of Calico, an Alphabet company in the healthcare space. She is the author of over 200-refereed publications appearing in venues such as Science, Cell, and Nature Genetics. Daphne was recognized as one of TIME Magazine’s 100 most influential people in 2012 and Newsweek’s 10 most important people in 2010. She has been honored with multiple awards and fellowships during her career including the Sloan Foundation Faculty Fellowship in 1996, the ONR Young Investigator Award in 1998, the Presidential Early Career Award for Scientists and Engineers (PECASE) in 1999, the IJCAI Computers and Thought Award in 2001, the MacArthur Foundation Fellowship in 2004, and the ACM Prize in Computing in 2008. Daphne was inducted into the National Academy of Engineering in 2011 and elected a fellow of the American Academy of Arts and Sciences in 2014 and of the International Society of Computational Biology in 2017. Her teaching was recognized via the Stanford Medal for Excellence in Fostering Undergraduate Research, and as a Bass University Fellow in Undergraduate Education.

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Xiaole Shirley Liu, PhDXiaole Shirley Liu
Professor of Statistics, Biostatistics, and Computational Biology, Harvard University, Dana-Farber Cancer Institute, USA

Xiaole Shirley Liu received PhD in Biomedical Informatics and PhD minor in Computer Science from Stanford University in 2002. She is now Professor of Statistics, Biostatistics and Computational Biology at Harvard University, Director of the Center of Functional Cancer Epigenetics at Dana-Farber Cancer Institute, associate member of the Broad Institute, and Visiting Professor of Bioinformatics at Tongji Univ. She is a member of the ENCODE consortium and the lead investigator for the Cancer Immune Data Common from National Cancer Institute. Her research focuses on algorithm development and integrative modeling of high throughput genomic data to understand the specificity and function of regulator genes in tumor development, progression, drug response and resistance. She is especially interested in genomics and bioinformatics approaches in cancer epigenetics, cancer immunology, and CRISPR screens for translational cancer research. Her lab developed widely used analysis algorithms for transcription factor motif discovery, ChIP-chip/seq, CRISPR screen, and tumor immune repertoire data analysis. Her computational modeling helped the understanding of ER, AR, FoxA1, XBP1, JARID1B, PBAF regulation as well as BET bromodomain inhibitor, gamma secretase inhibitor, CDK4/6 inhibitor, and immune checkpoint inhibitor function in different cancers in different cancers. Dr. Liu has an H-index of 79 according to Google Scholar statistics and has published over 50 papers in Nature, Science or Cell series journals. She is the recipient of the Sloan Research Fellowship, the Richard E. Weitzman Outstanding Early Career Investigator Award from the Endocrine Society, the Claire W. and Richard P. Morse Research Award, the Breast Cancer Research Foundation Investigator, the Yangtze River Scholar and 1000 Talent Scholar in China. She has successfully mentored sixteen trainees to start tenure track faculty positions.

Hidden immunology signals in tumor RNA-seq
Tumor RNA-seq data contain rich information about the tumor immune microenvironment. I will discuss two computational algorithms TIDE and TRUST developed in our lab.

Cancer treatment by immune checkpoint blockade (ICB) can bring long-lasting clinical benefits, but only a fraction of patients respond to treatment. To predict ICB response, we developed TIDE, a computational method to model two primary mechanisms of tumor immune evasion: the induction of T cell dysfunction in tumors with high infiltration of cytotoxic T lymphocytes (CTL) and the prevention of T cell infiltration in tumors with low CTL level. We identified signatures of T cell dysfunction from large tumor cohorts by testing how the expression of each gene in tumors interacts with the CTL infiltration level to influence patient survival. We also modeled factors that exclude T cell infiltration into tumors using expression signatures from immunosup- pressive cells. Using this framework and pre-treatment RNA-Seq or NanoString tumor expression profiles, TIDE predicted the outcome of melanoma patients treated with first-line anti-PD1 or anti-CTLA4 more accurately than other biomarkers such as PD-L1 level and mutation load. TIDE also revealed new candidate ICB resistance regulators, such as SERPINB9, demonstrating utility for immunotherapy research.

Tumor-infiltrating B cell is an important component in the microenvironment with unclear anti-tumor impacts. We enhanced our previous computational algorithm TRUST to extract the B cell immunoglobulin (Ig) hypervariable regions from bulk tumor RNA-seq data. TRUST assembled over 30 million complementarity-determining region 3 (CDR3s) of the B cell heavy chain (IgH) from The Cancer Genome Atlas (TCGA). Widespread B cell clonal expansions and Ig subclass switch events were observed in diverse human cancers. Prevalent somatic copy number alterations (SCNA) in MICA/B genes related to antibody-dependent cell mediated cytotoxicity (ADCC) were identified in tumors with elevated B cell activity. IgG3-1 subclass switch interacts with the B cell receptor affinity maturation and defects in the ADCC pathway. The comprehensive pan-cancer analyses of tumor-infiltrating B cell receptor repertoires revealed novel tumor immune evasion mechanism through genetic alterations. The IgH sequences identified in this work are potentially useful resources for future development of immunotherapies.

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Miriam Merad, PhDMiriam Merad, PhD
Icahn School of Medicine at Mount Sinai, USA

Miriam Merad, M.D.; Ph.D. is the Mount Sinai Chair professor in Cancer Immunology and the Director of the Precision Immunology Institute at Mount Sinai School of Medicine in New York.
Dr. Merad obtained her MD at the University of Algiers, Algeria. She did her residency in Hematology and Oncology in Paris, France and obtained her PhD in immunology in collaboration between Stanford University and University of Paris VII. She was recruited to Mount Sinai in 2004 and was promoted to the rank of Associate Professor with Tenure in 2007 and to Full Professor in 2010 and in 2014, she obtained an Endowed Chair Professor in Cancer Immunology.

Dr. Merad’s laboratory studies the contribution of macrophages and dendritic cells to Cancer and Inflammatory disease in mice and Human. Dr. Merad’s pioneering work mapping the regulatory network of dendritic cells (DCs) resulted in identification of a lineage of DC, the CD103+ DC, that is now considered a key target to improve antiviral and antitumor immunity.   Another of her key discoveries is that, contrary to the previously-held beliefs that monocytes are precursors of macrophages, she found that tissue-resident macrophages in fact arise from embryonic precursors that take residence in tissues prior to birth and are maintained independently of adult hematopoiesis. These insights are now being used to develop novel macrophage and dendritic cell-specific targets for the treatment of Cancer and Inflammatory diseases.  Dr. Merad has authored more than 160 primary papers and reviews in high profile journals. Dr. Merad receives generous funding from the National Institutes of Health (NIH) for her research on innate immunity and their contribution to human disease, and belongs to several NIH consortia. She is an elected member of the American Society of Clinical Investigation, and lectures around the world on her work.

Single Cell Approaches To Guide Novel Diagnostics And Precise Therapies
Immunological diseases arise from a complex interplay of genetic and environmental factors favoring tissue-damaging responses. Although many genetic susceptibility loci have been linked to these diseases, genetic information have failed to predict disease course or disease response to treatment.
Here I will discuss how single cell approaches are helping dissect disease heterogeneity, identify prominent pathophysiological processes and novel therapeutic avenues. I will also discuss novel single cell approaches that combine proteomics and RNAseq at the single cell level and how these approaches are strongly enhancing genomic data and our understanding of disease pathophysiology.

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Ana Pombo, PhDAna Pombo, PhD
Berlin Institute for Medical Systems Biology, at the Max Delbrueck Center, Germany

Ana Pombo investigates how the 3D folding of chromosomes influences gene expression in mammalian development and disease, and epigenetic mechanisms that prime genes for future activation. She received her DPhil from University of Oxford (1998, UK) where she identified transcription factories in mammalian nuclei. She was awarded a Royal Society Dorothy Hodgkin Fellowship (UK; 1998-2002), and started leading her research group in 2000 at the MRC London Institute for Medical Sciences, Imperial College London (UK). Her laboratory moved to the Berlin Institute for Medical Systems Biology, at the Max Delbrueck Center (Berlin, Germany) in 2013, and she was appointed Professor (W3) at Humboldt University of Berlin. Her lab has developed Genome Architecture Mapping (GAM), an exquisite technology to map the 3D structure of chromosomes genome-wide. GAM is uniquely powerful to quantify the higher-order complexity of 3D genome and the study of rare cell types directly from tissue, avoiding dissociation, including from precious human biopsies. These developments open a huge field of potential applications to identify the
genes affected by disease-associated genetic variants present in non-coding parts of the genome, through long-range chromatin contacts.

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Bing Ren, PhDBing Ren, PhD
Professor of Cellular and Molecular Medicine, UC San Diego, USA

Dr. Ren is Member of the Ludwig Cancer Research (LCR), Professor of Cellular and Molecular Medicine at the University of California, San Diego (UCSD), and Director of the UCSD Center for Epigenomics. Dr. Ren obtained his Ph.D. from Harvard University in 1998, and subsequently conducted postdoc research at the Whitehead Institute. He joined the faculty at LCR and UCSD in 2001, and was promoted to Associate Professor in 2007 and to Full Professor in 2009.  Dr. Ren is studying how gene expression is regulated in mammalian cells, and how its dysregulation leads to cancer and other human disease. His lab has developed transformative tools and concepts for global analysis of transcriptional control elements and chromatin organization.  He is a recipient of the Chen Award for Distinguished Academic Achievement in Human Genetic and Genomic Research, and an elected fellow of the American Association for the Advancement of Science.

Functional Organization of the Human Genome
The 3-dimentional architecture of chromosomes in eukaryotic cells enables long-range communication between enhancers and promoters, and contributes to spatiotemporal gene expression programs in multicellular species. Detailed knowledge of how chromatin architecture dynamically reorganizes during development and in different cell types is critical for studying the gene regulatory programs controlling cell fate specification and elucidating the molecular basis of human diseases. We have delineated the dynamic chromatin architecture at high resolution during key developmental stages of human cardiomyocyte differentiation from embryonic stem cells. We observed dramatic changes in chromatin compartments, topological domains and enhancer/promoter interactions, which was correlated with dynamic gene expression patterns. The chromatin loop interactions help us to predict target genes of non-coding genetic variants associated with cardiac-related traits/diseases. We also generate maps of long-range chromatin interactions centered on human promoters in a large panel of human cell/tissue types. We use this information to infer the target genes of candidate regulatory elements, and suggest potential regulatory function for non-coding sequence variants associated with a large number of physiological traits and diseases. Integrative analysis of these promoter-centered interactome maps reveals widespread enhancer-like promoters involved in gene regulation and common molecular pathways underlying distinct groups of human traits and diseases.

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Adam Siepel, PhDAdam Siepel, PhD
Professor, Watson School of Biological Sciences
Chair, Simons Center for Quantitative Biology
Cold Spring Harbor Laboratory, USA

Adam Siepel is a Professor in the Watson School of Biological Sciences and Chair of the Simons Center for Quantitative Biology at Cold Spring Harbor Laboratory, with adjunct appointments at Cornell University and Stony Brook University. Originally trained as a computer scientist, Siepel has done influential work in molecular evolution, human population genetics, and transcriptional regulation. He was a member of the faculty of the department of Biological Statistics and Computational Biology at Cornell University from 2006-2014 and has been at Cold Spring Harbor Laboratory since 2014.  Siepel is a winner of a Guggenheim Fellowship, a Microsoft Research Faculty Fellowship, a Packard Fellowship, a National Science Foundation CAREER Award, and a Sloan Research Fellowship.

An evolutionary framework for measuring epigenomic information and estimating cell-type specific fitness consequences
How much information do epigenomic data sets provide about human genomic function? We have addressed this question by considering nine epigenomic features across 115 cell types from the Roadmap Epigenomics project. We measure information about function as a reduction in entropy under a probabilistic evolutionary model fitted to human and nonhuman primate genomes. We find that several epigenomic features yield more information in combination than they do individually, and that the entropy in human genetic variation predominantly reflects a balance between mutation and neutral drift. Our cell-type specific FitCons scores reveal relationships among cell types and suggest that ~8% of nucleotide sites are constrained by natural selection.

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Itai Yanai, PhDItai Yanai, PhD
Director, Institute for Computational Medicine
Professor, Biochemistry and Molecular Pharmacology
New York University, School of Medicine, USA

Dr. Itai Yanai joined the faculty at New York University’s School of Medicine in May 2016 as a professor in the Department of Biochemistry and Molecular Pharmacology. He serves as the inaugural director of the Institute for Computational Medicine (ICM), whose goal is to harness computational approaches for fundamental and medically-relevant discoveries. Through the development of novel tools, the nurturing of young investigators, and translational applications, ICM aims to create a culture that promotes scientific advancements.

Dr. Yanai’s research focuses on the interface of gene expression, development, and evolution. Using his training as an experimental embryologist, a molecular biologist, and a computational biologist, his interest is exploring how developmental pathways evolve at the molecular level. Members of his lab carry out intricate embryological experiments at the level of individual cells and apply computational approaches to explore the resulting data. As a model system, they use the best understood animal, the nematode C. elegans. His lab developed the popular CEL-Seq method for single-cell RNA-Seq and they have used it to study stages, germ-layers, and body-plans in animal embryos. More recently, his lab is applying single-cell RNA-Seq to the study of tumorigenesis and bacterial infection.

Dr. Yanai received his undergraduate degrees in Computer Engineering and the Philosophy of Science and his PhD in Bioinformatics from Boston University in 1997 and 2002, respectively. He completed a postdoctoral fellowship in Molecular Genetics in 2004 at the Weizmann Institute of Science in Israel and a postdoctoral fellowship in Developmental Genetics at Harvard University in 2008. At the Technion–Israel Institute of Technology, he served as an Assistant Professor in the Department of Biology from 2008-2013 and Associate Professor from 2014-2016. He was a Radcliffe Fellow, Radcliffe Institute for Advanced Study, Harvard University, and a visiting professor, Broad Institute of Harvard and MIT, from 2014-2015.

In addition to his research goals, Dr. Yanai firmly believes that the communication of knowledge is a major component of science and is involved in mentoring students, giving presentations, participating in outreach programs and in the dissemination of science to a popular audience. Towards this end, Dr. Yanai has also co-authored a popular science book, entitled “The Society of Genes”, along with Dr. Martin Lercher from Heinrich-Heine University in Düsseldorf. 

Single-cell and spatial gene expression analysis of tumorigenesis

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