Training and Outreach Efforts BD2K-LINCS Webinar for the NIH BD2K Working Group on Training May 29, 2015 Avi Ma’ayan, PhD (Contact PI) Associate Professor.

Training and Outreach Efforts

BD2K-LINCS

Webinar for the NIH BD2K Working Group on Training

May 29, 2015

Avi Ma’ayan, PhD (Contact PI)Associate Professor

Sherry Jenkins, MSProgram Manager

Department of Pharmacology and Systems TherapeuticsIcahn School of Medicine at Mount Sinai

New York, New York

DATA COORDINATION AND INTEGRATION CENTER

AssaysCells

Pert

AssaysCells

PertAssays

Cells

Pert

Assays

Cells

Pert

AssaysCells

Pert

Assays

Cells

Pert

DCIC

High Throughput TranscriptomicsL1000Connectivity Map

NeuroLINCSALSImaging Proteomics Transcriptomics

Microenvironment Effects on Cancer Cells Transcriptomics Imaging Proteomics

High ThroughputProteomics

P100Epigenomics

Drug Combinations Mitigating Side Effects ProteomicsTranscriptomics

HighThroughput Imaging Proteomics Phenotypes Cancer Cells Modeling Cell Signaling

LINCS PHASE IILibrary of Integrated Network-based Cellular Signatures

BD2K-LINCS Data Coordination and Integration Center

DSR IKE CTO CCA

Internal & External Data

Science Research Projects

Metadata,APIs,

Visualization,Integration

ToolsTraining and

OutreachCoordination, Infrastructure

eDSRsiDSRs

Ma’ayan SchurerMedvedovic

lincs-dcic.orglincsproject.orgSummer Research

Training Program

Webinars

Mini-symposium, seminars and workshops

LINCS Working Groups

BD2K-LINCS Data Coordination and Integration Center – Scientific Objectives

- Understand how different layers of human cellular regulatory networks, i.e., transcriptomics and proteomics, correlate and interact.

- Develop methods to benchmark computational and experimental methods to objectively evaluate their quality and extract more knowledge from the data.

- Understand the inherit biases within low- and high content experiments, and develop methods to correct for such biases.

- Map the dimensionality of all possible global molecular states of human cells in normal physiology, disease, and in response to perturbations by small molecules and genetic manipulations.

- Develop methods to connect cellular and organismal phenotypes with molecular cellular signatures.

BD2K-LINCS Data Coordination and Integration Center – Data Science Objectives

- Organize, curate and serve for search and download the largest possible collection of annotated molecular cellular signatures, networks and attribute tables.

- Develop novel data visualization methods for

dynamically interacting with large-genomics and proteomics datasets.

- Develop educational and outreach activities for training and engaging the next generation of data scientists.

- Develop ontologies and other methods for data integration across diverse sets of experimental data collected by different laboratories, centers and large-scale projects utilizing different high content profiling assays.

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Community Training and Outreach (CTO)

• Courses• MOOCs on Coursera:

1. Network Analysis in Systems Biology 2. Big Data Science with the BD2K-LINCS

DCIC• ISMMS Graduate Courses:

1. BD2K-LINCS DCIC - Programming for Big Data Biomedicine

2. BD2K-LINCS DCIC - Data Mining in Systems Biology

• Big Data Biostatistics PhD Program (at the University of Cincinnati College of Medicine)

• Summer Research Training Program in Biomedical Big Data

• Data Science Research Webinars

• Crowdsourcing Projects Portal

• External Data Science Projects

• Mini-symposium, Seminars and Workshops

lincs-dcic.org DCIC Outreach Activities

Funding Opportunities

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Network Analysis in Systems BiologyMOOC on Coursera

A graduate-level course which serves as an introduction to Big Data analysis in systems biology including statistical methods used to identify differentially expressed genes, performing various types of enrichment analyses, and applying clustering algorithms.

https://class.coursera.org/netsysbio-002Description:

• 8 weeks / 7 modules

• 34 Short video lectures

• 24 Auto-graded short quizzes

• Auto-graded final exam

• Crowdsourcing tasks

Course Features:

• Weekly overviews

• Discussion forum

Last session: January 5, 2015 – March 3, 2015

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Network Analysis in Systems BiologyCourse Analytics

Engagement:

Content:

~600 students passed the course to obtain a statement of accomplishment

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Big Data Science with the BD2K-LINCS Data Coordination and Integration Center

MOOC on Courserahttps://www.coursera.org/course/bd2klincs

Session: Sep 15 – Nov 9 2015

• Overview of the NIH Common Fund LINCS Program

• Overview of the Data and Signature Generation Centers (experiments and data)

• Meta-Data and Ontologies• Data Normalization• Unsupervised Learning Methods: Data

Clustering• Supervised Learning Methods• Enrichment Analyses• Bayesian Data Integration• Network Analysis and Network Visualization• Cheminformatics• Serving data through RESTful APIs and

JSON• Interactive Data Visualization of LINCS Data

Syllabus:

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BD2K-LINCS DCIC: Programming for Big Data BiomedicineISMMS Graduate Course

Ten-week mini-course taught by Avi Ma’ayan PhD and members of his research team within the BD2K-LINCS DCIC at the Icahn School of Medicine at Mount Sinai

• Agent Based Modeling with NetLogo• Agent Based Modeling with MATLAB• Python• Python and MatPlotLib• HTML and CSS• JavaScript and PHP• MySQL• MongoDB• Bootstrap Templates• R• Final Project

Topics:

Spring 2015

Course Dates: Feb 24 – May 4 2015

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BD2K-LINCS DCIC: Data Mining in Systems BiologyISMMS Graduate Course

Ten-week mini-course taught by Avi Ma’ayan PhD and members of his research team within the BD2K-LINCS DCIC at the Icahn School of Medicine at Mount Sinai

• Self Organizing Maps• Hierarchical Clustering• PCA• Linear Regression• Decision Trees• Graph Theory Concepts• Support Vector Machines• Final Project

Topics:

Fall 2015Fall 2014 Course Dates:

September 16 – December 2, 2014

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BD2K-LINCS DCIC Summer Research Training Program in Biomedical Big Data Science

Ten-week training program for undergraduate and master’s students interested in research projects aimed at solving data-intensive biomedical problems.

Icahn School of Medicine at Mount Sinai

Dynamic Data VisualizationMachine Learning

Data Harmonization

Ma’ayan Laboratory of Computational Systems Biology

Summer 2015 Program Dates: June 1 – August 7

Summer 2015 | Training Sites

University of WashingtonYeung / Computational Systems Biology Group

Machine LearningData Integration

Network Visualization Plugins

• Carnegie Mellon University, Biological Sciences (Bar-Joseph)• Carnegie Mellon University, Computational Biology (Ma’ayan)• University of Washington, Computer Engineering (Yeung)• University of Washington, Computer Science (Ma’ayan)• The City College of New York, Bioinformatics (Ma’ayan)• Yorktown High School (Ma’ayan)

2015 Cohort Summary• 6 trainees• 2 master’s / 3 undergraduate / 1 high school• 4 women / 2 men• All future plans include STEM graduate degrees

http://lincs-dcic.org/#/srp

Carnegie Mellon University

Machine LearningTime Series Analysis

Transcriptional Regulatory Networks

Bar-Joseph / Systems Biology Group

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Data Science Research WebinarsServe as a general forum to engage data scientists within and outside of the LINCS project to work on problems related to LINCS data analysis and integration.

http://lincs-dcic.org/#/webinars

• Open to data science research community

• Advertised on DCIC website, LINCS portal, Twitter, Google group

• Schedule and connection details posted on the DCIC website and LINCS portal

• Past webinar videos posted on the DCIC’s YouTube channel

Purpose / Target Audience

www.lincsproject.org/community/webinars/BD2K-LINCS DCIC @BD2KLINCSDCIC| | |

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BD2K-LINCS DCIC Crowdsourcing Portal

http://www.maayanlab.net/crowdsourcing/

15http://www.maayanlab.net/crowdsourcing/

Community Science Project: Building a Database of Gene Expression Signatures Extracted from Single Gene

Knockout/Knockdown Studies

16http://www.lincs-dcic.org/#/edsr

Data Science Research Collaborations with the BD2K-LINCS DCIC

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Mini-symposium, Seminars and Workshops

Mini-symposium | January 7, 2015

Symposium was co-sponsored by the BD2K-LINCS DCIC and Mount Sinai’s Knowledge Management Center

for Illuminating the Druggable Genome

Winter 2014 - 2015

Invited Seminar SpeakersDecember 5, 2014Reverse Engineering a more Reliable Translational Pipeline with Patient-Derived iPSC Models of Neurodegenerative Disease, Robotic Longitudinal Single Cell Analysis and Deep LearningSteven Finkbeiner, MD, PhD / NeuroLINCS Center

January 14, 2015The PAGE Study and Coordinating Center (Population Architecture using Genomics and Epidemiology)Tara Matise, PhD / PAGE Coordinating Center

Works in Progress Seminar Series

March 23, 2015BD2K-LINCS Outreach Session:Turning Big Data to Knowledge (BD2K-LINCS): A discussion of the NIH BD2K initiative and how it might advance the practice of Toxicology and Risk AssessmentJohn Reichard PhD, Mario Medvedovic PhD / BD2K-LINCS DCIC

Poster Session: Big Data to Knowledge (BD2K) - A Graphical Approach for Data Coordination and IntegrationJ.F. Reichard, M. Medvedovic, S. Sivagas / BD2K-LINCS DCIC

Outreach Session at the Society of Toxicology’s Annual Meeting

January 15, 2015Enrichr and GEO2Enrichr: Tools to Extract and Analyze SignaturesGregory Gundersen and Matthew Jones / BD2K-LINCS DCIC

Calendar of events on lincs-dcic.org

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Genomic and Computational Approaches for Biomarker and Drug Discovery

Workshop hosted by the NIAAALocation: San Antonio, TX Grand Hyatt, San AntonioRoom: Travis C/DTime: 2:00 – 5:00pm

http://www.lincsproject.org/news/

WORKSHOP | June 19, 2015

EnrichrSearch engine for gene lists and signatureshttp://amp.pharm.mssm.edu/Enrichr/

Hands-on Session: Web Apps and Tools

GEO2EnrichrDifferential Expression Analysis Toolhttp://maayanlab.net/g2e

L1000CDS2

L1000 Characteristic Direction Signature Search Enginehttp://amp.pharm.mssm.edu/L1000CDS2/

PAEAPrinciple Angle Enrichment Analysishttp://amp.pharm.mssm.edu/PAEA/

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Acknowledgements

The BD2K-LINCS DCIC is co-funded by BD2K and the NIH Common Fund

NIH Grant Number: U54HL127624

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