Biological networks play a fundamental role in today’s systems-based biology, pharmacology, and toxicolog as they create the link between experimental measurements and a priori knowledge.
Network models consist of qualitative causal relationships between biological entities to represent current scientific knowledg.
They are represented in a human-readable and computable language (BEL) used for representing scientific knowledge in a standard way.
The purpose of the Network Verification Challenges is to engage the scientific community to review, challenge as well as make corrections to the conventional wisdom on various molecular mechanisms.
BACKGROUND ↑
Biological expression language (BEL)
BEL represents scientific knowledge in human readable and computable format as semantic triples (subject, a predicate, and an object).
Xenobiotic metabolism
Xenobiotic metabolism is activated in response to any chemical substance foreign to the body (e.g., toxic compounds, drugs). Very briefly, enzymes involved in this process convert xenobiotics into hydrophilic derivatives that can be eliminated through excretion into the aqueous compartments of the tissues.
Philip Morris International (PMI) has invested a great effort to develop computational methodology to predict early toxicity using Causal Biological Network Models and high throughput molecular data.
Previously developed network models were scripted in BEL and focused on pulmonary and vascular biology. Since the liver is the main site of xenobiotic metabolism in mammals, we have developed a new suite of network models that represent biotransformation and chemical elimination involved in Phase I, Phase II and Phase III xenobiotic metabolism in the liver.
Applications of network models
In addition to providing a valuable repository for literature knowledge of various biological processes, the causal biological network models can be scored with transcriptomics data, which opens a myriad of opportunities to gain genome-wide insights in defined biological context.
The network models can also be used to generate hypotheses and to identify the components responsible for biological phenomena in an unbiased way. This allows researchers to design targeted experiments to verify further and extend the insights obtained using high-throughput approaches.
Compound-specific network signatures provide mechanistic insights into the similarities and differences by which toxicants impact biological systems, allowing the toxicity prediction of uncharacterized compounds.
Finally, network model scoring can facilitate biomarker discovery, predict adverse drug reactions, and support personalized medicine by mechanistically explaining patients’ differences concerning disease prevention, diagnosis, and therapy outcome.
The leaderboard: gamifying principle to encourage participation
Gamification principles are widely used to support user engagement and enhance positive patterns in service use. It results in increased motivation and engagement in the learning and enjoyment over the tasks.
The challenge ↑
Components of a network verification challenge
The organization of a network verification challenge entails:
- A number of network models available for review;
- A web platform to visualize, verify, and collaboratively refine the networks: ( the Bionet platform;
- A leaderboard to keep track of the competition;
- A conference/jamboree to meet and collaborate around the networks.
The overall process is illustrated below:
Challenge overview
NVC3: Liver xenobiotic metabolism networks
NVC2: Lung biology
A summary of the challenge outcome is given in the below picture.
NVC1: Lung biology
A summary of the challenge outcome is given in the below picture.
Rules and awards
Description
Challenge participants ↑
Leaderboard: best performers ↑
Best performers
NVC3: Liver xenobiotic metabolism networks
The top 3 best performers in the NVC3 are:
- Aravind Tallam from the Charité Berlin-Brandenburg Center for Regenerative Therapies, Berlin, Germany;
- Sphoorthy Pravas University of Bonn, Germany, Germany; and
- Trinidad Martin from the SIB (Swiss Institute of Bioinformatics), Geneva, Switzerland.
NVC2: Lung biology
The best performers were announced at the sbv IMPROVER Jamboree 2015 in Barcelona, Spain and the identity of the Best Performers was published in Nature (Volume 523 Number 7562, 30 July 2015, page 495).
NVC1: Lung biology
The best performers were announced at the sbv IMPROVER Jamboree 2014 in Montreux, Switzerland and the identity of the best performers was published in Nature (Volume 509 Number 7499, 8 May 2014, page 127).
Challenge symposia ↑
In order to congratulate the best performers and share the learnings of the challenges, different symposia have been organized, alongside larger conferences, or as standalone events.
Network Verification Challenge 3: Liver xenobiotic metabolism networks
The sbv IMPROVER NVC3 workshop 2018 was successfully conducted the PMI R&D facilities in Neuchatel, Switzerland on June 27th 2018. The symposium included:
- The results and presentation of awards for the Network Verification Challenge III
- Keynote presentations on biological networks
- Discussions on the 3D liver microtissues study design
Network Verification Challenge 2: Lung biology
The sbv IMPROVER Jamboree 2015 was successfully conducted at the Rey Juan Carlos I Hotel, Barcelona, Spain, on 15 - 18 June 2015. The event included lectures, biological network review sessions (jamboree), and social events and networking.
On Wednesday 17th June 2015, the conference was open to the scientific community.
The meeting had two main objectives:
- Review and agree on the existence of a selection of edges and evidences that were disputed by challenge participants during the online verification process.
- Gather lessons learned from the Network Verification Challenge.
The Jamboree brought together:
- The “best performing” participants in the Network Verification Challenge, as determined by reputation points;
- Subject matter experts;
- The team of scientists who generated the initial networks models.
Network Verification Challenge 1: Lung biology
The sbv IMPROVER Jamboree 2014 was successfully conducted at Le Montreux Palace, Montreux, Switzerland, on 18 - 20 March 2014. The event included lectures, biological network review sessions (jamboree), and social events and networking.
Media library ↑
Scientific publications
- The sbv IMPROVER project team and challenge best performers Community-Reviewed Biological Network Models for Toxicology and Drug Discovery Applications. Gene regulation and systems biology 10, 51–66 (2016).
- Boue, S. et al. Causal biological network database: a comprehensive platform of causal biological network models focused on the pulmonary and vascular systems. Database: the journal of biological databases and curation 2015, bav030 (2015).
- Boue, S. et al. Enhancement of COPD biological networks using a web-based collaboration interface. F1000Research 4, 32 (2015).
- Ansari, S. et al. On crowd-verification of biological networks. Bioinformatics and biology insights 7, 307–25 (2013).
The challenge in the news
| Drug Discovery News | Sep 2016 | Crowdsourcing lung biology |  |  |
| Drug Discovery Today | Aug 2016 | Philip Morris International, IBM Launch Industry-Focused Systems Biology Verification Challenge | | |
| American Laboratory | Aug 2016 | Community-Verified Biological Network Models Show Promise for Toxicology, Drug Discovery | | |
| Libertas Academica | Aug 2016 | Public Science Insights: Community verified biological network models | | |
| News Medical | Jul 2016 | Novel community-produced biological network models hold potential in drug discovery and toxicology | | |
| Asia Pacific Biotech News | Nov 2015 | A New Look into Toxicology Risk Assessment and Environmental Safety | | |
| BioSpectrum Asia | Jul 2015 | Network Verification Challenge gains momentum | | |
| American Laboratory | Nov 2014 | Success of the Third sbv IMPROVER Network Verification Challenge | | |
| Asia Pacific Biotech | Oct 2014 | Network Verification Challenge generates COPD network models | | |
| BioSpectrum Asia | Aug 2014 | Hope for COPD: Network Verification Challenge | | |
| Science 2.0 | Feb 2014 | Systems Biology Post-Docs May Have A New Best Friend In...Philip Morris? | | |
| Asia Biotech | Dec 2013 | Challenged TO Improve | | |
| Science Reporter | Dec 2013 | Network Verification Challenge open for Scientists | | |
| Drug Discovery News | Nov 2013 | All together now... | | |
| American Laboratory | Oct 2013 | Network Verification Challenge opens a new chapter for sbv IMPROVER | | |
| BioSpectrum Asia | Oct 2013 | Network verification challenge to map bio networks | | |
| GenomeWeb | Oct 2013 | Philips Morris International and IBM Launch Third 'Improver' Challenge | | |
| PharmaManufacturing | Oct 2013 | The Scientific Data Crowdsourcing Challenge | | |
| BioITWorld | Oct 2013 | Network Verification Challenge Opens to All | | |
