While life science data is currently being generated on a huge scale and across domains (sequences, transcriptomics, proteomics, PTMs, etc.), the question becomes more and more apparent how useful this data is in practice.

In order to bring an alternative viewpoint to the current hype of -omics technologies, this informal one-day meeting in Cambridge will start by making a case what currently does NOT work, and hence how limited our current understanding of biology appears to be. We will afterwards switch to somewhat more optimistic scenarios - and present case studies where -omics (and other life science) data has been able to support understanding of biology, decision making and discovery, across chemical biology and drug discovery (including development and clinical) settings. The aim is hence, afterwards, to develop a more realistic attitude towards biological data - with the aim to get a better feeling what we can, and cannot, see and detect in the various biological readouts currently available.

Attendance is free, and registration possible by simple email to Andreas Bender, ab454@cam.ac.uk. The meeting will take place on 23 September, from 10-5pm, at the Centre for Molecular Informatics, Chemistry Department, Lensfield Road, Cambridge, CB2 1EW, United Kingdom. Lunch on the day will be provided to all participants, and the meeting will subsequently conclude with a visit to the local pub.

The programme of the meeting is not yet fixed, and everyone is hence encouraged to contribute, in order to make this an interesting event for everyone! Please supply a title of your talk with your registration email if you would like to present, in particular related to the topics listed below (but also anything else you find of relevance). The format will be short talks of 20 minutes (15 minutes + 5 minutes for questions), intended to present a wide variety of data types and decisions in a focused manner. Talks can be conventional research presentations, but also viewpoints, opinions, etc. The final programme will then be circulated at the end of August to everyone who received this email, and everyone else registering for the meeting in the interim.

Suggested topics are:

1. Generating data: Relevant readouts in humans, and model systems (are cells actually of any use? 2D vs 3D assays, etc.); characterizing biology (from cell lines to patients); how to define reference states/baselines when characterizing biology; handling timepoints, localization, and dose appropriately;...
2. Storing data: Biological (and other) ontologies; storing and searching (modified) antibodies and biologics; generating/handling/extracting relevant data from phenotypic screens; ...
3. Modelling data: The hype of -omics technologies - and where is the signal?; how useful are pathways (and its current definitions)?; how consistent is biology (eg variance between patients, or model systems), and how noisy is our data?; feature selection/biomarker detection in noisy systems; cell sensitivity modelling (and its problems) as a case study; ...
4. From data to therapy: So which protein (or other entity?) do we need to target?; which chemical (or biological) matter can we identify for this purpose, and how (based on which type of data and models)?; ...

This list is certainly not exhaustive by any means - so if you have a case where data was (not) able to solve your problem, please just let me know, and we will be able to accommodate it!