Dear Colleagues,

The submission deadline for our NeurIPS 2020 Workshop, Machine Learning for 
Structural Biology (MLSB) will be October 02, 2020. Could you please forward 
the attached CfP to any mailing lists or people who would be interested?

Best,
The MLSB Organizing Team
mlsb.io <http://mlsb.io/>
Machine Learning in Structural Biology (MLSB), December 11-12th, 2020.
Spurred on by recent advances in neural modeling and wet-lab methods, 
structural biology, the study of the three-dimensional (3D) atomic structure of 
proteins and other macromolecules, has emerged as an area of great promise for 
machine learning. The shape of macromolecules is intrinsically linked to their 
biological function (e.g., much like the shape of a bike is critical to its 
transportation purposes), and thus machine learning algorithms that can better 
predict and reason about these shapes promise to unlock new scientific 
discoveries in human health as well as increase our ability to design novel 
medicines.

Moreover, fundamental challenges in structural biology motivate the development 
of new learning systems that can more effectively capture physical inductive 
biases, respect natural symmetries, and generalize across atomic systems of 
varying sizes and granularities. Through the Machine Learning in Structural 
Biology workshop, we aim to include a diverse range of participants and spark a 
conversation on the required representations and learning algorithms for atomic 
systems, as well as dive deeply into how to integrate these with novel wet-lab 
capabilities.

Invited Speakers:
Michael Levitt - Keynote (Stanford University, Nobel Prize in Chemistry 2013)
David Baker - Keynote (Institute for Protein Design, University of Washington)
Mohammad AlQuraishi (Columbia University)
Charlotte Deane (Oxford University)
Debora Marks (Harvard Medical School)
Frank Noe (Freie Universität Berlin)
Chaok Seok (Seoul National University)
Andrea Thorn (Würzburg University)

Call For Papers (Website: mlsb.io <https://mlsb.io/>)
We welcome submissions of short papers leveraging machine learning to address 
problems in structural biology, including but not limited to:

Structure prediction
Protein and RNA design
Experimental determination of structure
Interaction prediction
Conformational change and ensemble prediction
Molecular dynamics with learned samplers or potential functions
Function or property prediction
Structural systems biology
Model systems, such as lattice proteins or other toy ensembles
Learning representations of structure
We request anonymized PDF submissions by Friday, October 2nd, 2020, 11:59PM in 
the timezone of your choice through our submission website. We will post the 
link at the workshop website, mlsb.io <http://mlsb.io/>, within 2 weeks of the 
submission deadline.

Submissions should be 4-9 pages in PDF format and fully anonymized as per the 
requirements of NeurIPS. We request use of the NeurIPS style files. A maximum 
of 9 pages excluding references and appendices will be considered. The review 
process will be double-blind.

Accepted papers will be invited to present a poster at the virtual workshop, 
with nominations of spotlight talks at the discretion of the organizers.  This 
workshop is considered non-archival and does not publish proceedings, however 
authors of accepted contributions will have the option to make their work 
available through the workshop website. Presentation of work that is 
concurrently in submission is welcome.

Important dates:
Friday, October 02, 2020: Submission deadline at 11:59PM Anywhere on Earth
Friday, October 23, 2020: Notification of Acceptance

Registration:
Register here <https://forms.gle/8jqTjgHVSSczCJL18> to get on our mailing list!

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