S P L C C E N B S P L C C E N B S P L C C E N B S P L C C E N B H U E O O X E E H U E O O X E E H U E O O X E E H U E O O X E E A B A N L P T N A B A N L P T N A B A N L P T N A B A N L P T N R L R T L L W C R L R T L L W C R L R T L L W C R L R T L L W C E I N R A O O H E I N R A O O H E I N R A O O H E I N R A O O H S I B R R M S I B R R M S I B R R M S I B R R M H B O E K A H C B O E K A H B O E K A H B O E K A B C B S C C U R R O U R R H U R C R O U R R E T A C K O C L T A C K E N T A K O C T A C K Why should you be part of N N P O L P O N E A P O L L P O E E T sbvU O IMPROVERL E T R E T U N O L E T C E L L N A E U N S C T E L N E U N S H T L B L B A B T H W E L B T B A A B T W B E E T B H E E T H M L A B N L R A M O L R B B N L R A O E A E I N R O A E I I N R O sbv IMPROVER? A B O I R E E I I R A R N O I E E I I R R N R X S C R X S B C R R O R B A X T S B E R K E R B X T S B E K K C N P H R H A P H U K T N P H U H A A P H U H U T W U W L A M T L O T W L T M T T L O T Verification of Systems Biology Research M EpigenomicsC A T E C C E A T B C O T E O R B E O C O E E O R E N A R O R E E O R O R E E in the age of Collaborative Competition E O E R K E N R O R K E R E N K N E X E N K N E N T X L T B N T K L T B sbv IMPROVER stands for Systems Biology Verification combined with P K L E C P L E C W R E T L R R E T C H L A L N E H I A L N O Industrial Methodology for Process Verification in Research. I W O I W O M R O B B E C X M B B B E C N R O ChallengeA O P A R O A O A K The sbv IMPROVER project is designed to enable scientists to learn Present the method applied in your U H U U H T E R R R L R E R R R R T M K T T M K R K about and contribute to the development of a new crowd sourcing SHARE submission at the Symposium. P A E N A O K E N A E N A I T R L E T P method, combined with Industrial Methodology, for verification of U R R C B U B E E K E E T E K O U C A W E C B scientific data and results. L S X O X O N T L P P R O S T I H L L H P L L E I S L U N R R A L E B K A L L E S H R O A A O A A I H R L R B Win a gift card of up to USD 1,500 E B R I E R B R E O N N E O N U Key publications WIN E S T per team. R H N R E A T E A T W T T sbv IMPROVER Project E O W E R O • Meyer et al. Industrial methodology for process verification in research K R (IMPROVER): toward systems biology verification. Bioinformatics. 2012 K Receive an independent • Meyer et al. Verification of systems biology research in the age of LEARN collaborative competition. Nat Biotechnol. 2011 assessment of your methods. Diagnostic Signature Challenge • Tarca et al. Strengths and limitations of microarray-based phenotype prediction: lessons learned from the IMPROVER Diagnostic Signature Network with your peers and grow Challenge. Bioinformatics. 2013 NETWORK your professional network. Species Translation Challenge • Hoeng et al. Where are we at regarding species translation? A review of the sbv IMPROVER challenge. Bioinformatics. 2015 Present your own research during a • Rhrissorrakrai et al. Understanding the limits of animal models as PRESENT predictors of human biology: lessons learned from the sbv IMPROVER poster session at the Symposium. Species Translation Challenge. Bioinformatics. 2015 • Poussin et al. The species translation challenge - A systems biology perspective on human and rat bronchial epithelial cells. Scientific Data. 2014 Have fun working with others. Network Verification Challenge COLLABORATE • sbv IMPROVER team et al. Enhancement of COPD biological networks using a web-based collaboration interface. F1000Res. 2015 • sbv IMPROVER team and NVC best performers. Community-reviewed biological network models for toxicology and drug discovery applications. Gene Regulation and Systems Biology. 2016 MEET Meet with worldwide experts. Symposium: May 4th, 2017 Systems Toxicology Challenge • Poussin et al. Crowd-sourced verification of computational methods and data in systems toxicology: a case study with a heat-not-burn Tel Aviv, Israel candidate modified risk tobacco product. Chem Res Toxicol. 2017 cvent.com/d/0vq5g5

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The current challenges, website and biological network models were developed and are maintained as part of a collaboration among Philip Morris International, Douglas Connect, OrangeBus, and ADS. The project is led and funded by Philip Morris International. Further information at www.pmiscience.com sbv IMPROVER Challenges The Challenge in a Nutshell

2012 Diagnostic Signature Challenge Scientific Questions Designed to determine whether computational approaches and transcriptomics data could be used • Can a smoke exposure signature be extracted from DNA methylation levels of DNA cis-regulatory elements for phenotype prediction. (CRE)? 2013 Species Translation Challenge • Can a smoke exposure signature be extracted from expression data of genes controlled by differentially methylated Designed to address whether biological events DNA cis-regulatory elements? observed in rodents were translatable to humans. a Classification performance 2014 assessment Network Verification Challenge Molecular markers for 2015 c Designed to verify previously built biological network exposure response models and ensure their relevance to lung biology Lungs and COPD. cis-regulatory elements Enhancer Promoter TF TSS TF TF TF Gene 2015 Systems Toxicology Computational 2016 Challenge Designed to verify that a robust predictive signature Non-exposed group can be extracted from gene expression data that differentiates smokers, former smokers, and never non-exposed smoker subjects. Classification approaches: b 1. Based on DNA methylation only 2016 exposed Datathon 2. Based on gene expression of Designed to predict class labels of different exposed genes related to differentially groups. methylated regions

me 2017 Epigenomics Challenge Exposed group DNA methylation Gene expression (sequencing) (microarray) a. Samples of lung tissue are collected from mice belonging to the exposed or non-exposed groups. The data b. Gene expression profiles (GEX) and DNA methylation are measured using microarray based technology and Illumina sequencing by synthesis technology, respectively. STUDY 1 Months 1 2 3 6 8 c. Participants are provided with GEX and DNA-Methylation and asked to develop a classification approach capable of Apoe-/- Fresh air (Sham) Mice Cigarette smoke (3R4F) associating subjects to the correct exposure group. T R A I N G STUDY 2 STUDY 3 Timeline Months 2 7 Month 1 Sham A/J Sham

+ Mice 3R4F wt 3R4F T I O N Mice pMRTP* STUDY 1 R A Cess* Months 1 2 3 6 8 Switch* THS2.2* -/- T E S I N G Apoe Cess* Mice

E X P L O * Exploration datasets pMRTP: prototype modified risk tobacco product Switch* THS2.2: tobacco heating system version 2.2 Cess: cessation