Structural biology, the study of the 3D structure or shape of proteins and other biomolecules, has been transformed by breakthroughs from machine learning algorithms. Machine learning models are now routinely used by experimentalists to predict structures to aid in hypothesis generation and experimental design, accelerate the experimental process of structure determination (e.g. computer vision algorithms for cryo-electron microscopy), and have become a new industry standard for bioengineering new protein therapeutics (e.g. large language models for protein design). Despite all of this progress, there are still many active and open challenges for the field, such as modeling protein dynamics, predicting the structure of other classes of biomolecules such as RNA, learning and generalizing the underlying physics driving protein folding, and relating the structure of isolated proteins to the in vivo and contextual nature of their underlying function. These challenges are diverse and interdisciplinary, motivating new kinds of machine learning methods and requiring the development and maturation of standard benchmarks and datasets.
Machine Learning in Structural Biology (MLSB), seeks to bring together field experts, practitioners, and students from across academia, industry research groups, and pharmaceutical companies to focus on these new challenges and opportunities. This year, MLSB aims to bridge the theoretical and practical by addressing the outstanding computational and experimental problems at the forefront of our field. The intersection of artificial intelligence and structural biology promises to unlock new scientific discoveries and develop powerful design tools.
MLSB will be an in-person workshop on December 15th at NeurIPS.
Please contact the organizers at workshopmlsb@gmail.com with any questions.
Stay updated on changes and workshop news by joining our mailing list.
Congratulations to all accepted presenters! Please find some information on deadlines and expectations leading up to the MLSB Workshop!
We expect all authors to prepare a poster that can be presented as part of our workshop. Posters must be 24W x 36H inches and will be taped to the wall. Poster boards will not be provided at the workshop. Posters should be on lightweight paper, and not laminated.
Additionally, a virtual copy of each poster must be uploaded to the NeurIPS poster upload portal by Thursday, December 14. Posters must be PNG with no more than 5120 width x 2880 height (no more than 10 MB). Thumbnail images should be 320 width x 256 height PNG and no more than 5 MB. Users should log in using the neurips.cc account associated with their CMT email address. If they did not already have a neurips.cc account, then it should have automatically been created and can be accessed by resetting the password.
De-anonymized, camera-ready versions of the workshop paper will be due on Microsoft CMT by Monday, Dec 4. Papers must indicate that they are NeurIPS MLSB workshop papers by using the modified NeurIPS style file here. Papers should be compiled with the 'final' argument, e.g. \usepackage[final]{neurips_mlsb_2023}
We plan to make all submitted papers available on the workshop website (https://www.mlsb.io/). If you would prefer that your work not be shared, please email the organizers by responding to this email as soon as possible. Additionally, please let us know if there is an arXiv/biorXiv link for the paper that should be linked as well.
This year we will try to cover as many workshop registrations as possible for student/academic attendees with oral presentations or posters who need financial assistance. If you would like to be considered, please fill out the following form by Friday, Nov 17th. If you have any questions, please don't hesitate to contact us at workshopmlsb@gmail.com.
Application for Registration Reimbursement: Friday, November 17th, 2023, at 11:59PM, Anywhere on Earth.
Camera-Ready PDF due on Microsoft CMT: Monday, December 4th, 2023.
Poster due: Thursday, December 14th, 2023.
Founding Technical Director of the Chan-Zuckerberg Imaging Institute.
Show/Hide BioAssociate Professor at NYU
Senior Director of Frontier Research at Prescient Design.
HHMI Investigator, Associate Professor of Biochemistry at Stanford University.
Show/Hide BioAssociate Professor of Genetics and
Bioengineering at Stanford University.
Professor of Bioengineering at University of California, San Francisco.
Show/Hide BioCo-Founder and CTO of Generate Biomedicines.
Associate Professor at Dartmouth College.
08:30 | Opening Remarks | |||
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08:35 | Invited Speaker - Kyunghyun Cho Health system scale language models for clinical and operational decision making |
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09:00 | Contributed Talk
Validation of de novo designed water-soluble and membrane proteins by in silico folding and melting |
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09:15 | Invited Speaker - Tanja Kortemme Accurate and tunable de novo protein shapes for new functions |
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09:40 | Break | |||
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10:00 | Invited Speaker - Bridget Carragher A CryoET Data Portal to Foster a Collaboration between the Machine Learning and CryoET Communities |
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10:25 | Contributed Talk
AlphaFold Meets Flow Matching for Generating Protein Ensembles |
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10:40 | Contributed Talk
DSMBind: an unsupervised generative modeling framework for binding energy prediction |
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10:55 | Invited Speaker - Polly Fordyce Leveraging microfluidics for high-throughput and quantitative biochemistry and biophysics |
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11:20 | Poster Session/Lunch | |||
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12:40 | Invited Speaker - Gevorg Grigoryan Illuminating protein space with a programmable generative model |
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01:00 |
01:05 | Contributed Talk
Protein generation with evolutionary diffusion: sequence is all you need |
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01:20 | Invited Speaker - Jason Yim / Brian Trippe De novo design of protein structure and function with RFdiffusion |
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01:45 | Break | |||
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02:00 | Contributed Talk
DiffDock-Pocket: Diffusion for Pocket-Level Docking with Sidechain Flexibility |
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02:15 | Contributed Talk
PoseCheck: Generative Models for 3D Structure-based Drug Design Produce Unrealistic Poses |
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02:30 | Invited Speaker - Rhiju Das World-wide competitions and the RNA folding problem |
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02:55 | Break | |||
03:00 | Panel Discussion | |||
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04:00 | Poster Session / Happy Hour | |||
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05:00 | Closing Remarks |