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5th Molecular Machine Learning Conference

Tuesday, November 5, 2024

Our Mission

The Molecular Machine Learning Conference is a biannual gathering of researchers across academia and industry who share the goal of advancing how machine learning methods can address key scientific goals related to molecular modeling, molecular interactions, and more broadly therapeutic design. Through a combination of engaging talks and poster presentations, conference provides an open and lively place to discuss, learn, and innovate, for students and experts alike.

Areas of Focus

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Generative AI for biology

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Molecular ML for drug discovery

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Molecule/Protein 3D structure prediction

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Modeling molecular interactions

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Molecular dynamics

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Machine learning for quantum chemistry

2024 Speakers

Agenda

8:45 am — 9:30 am

Check-In

9:30 am — 9:35 am

Opening Remarks

9:35 am — 10:00 am

Session I: State of the discipline of therapeutic antibody engineering 

10:00 am — 10:30 am

Session II: Language models generate functional genome editors and expand the CRISPR-Cas universe

10:30 am — 11:00am

Selected paper authors​

11:00 am — 12:00 pm

Accepted paper authors

12:00 pm — 1:00 pm

Lunch break

1:00 pm — 1:30 pm

Panel: How far can Evolutionary Information go?

1:30 pm — 2:00 pm

Session III: Uncharted Territory - Conquering Impossible Targets with Helicon Peptides

2:00 pm — 2:30 pm

Session IV: Ligand-aware protein design using reinforcement learning

2:30 pm — 3:30 pm

Poster Session II

Accepted paper authors

3:30 pm — 4:00 pm

Top 4 Papers + Best Paper Announcement

Portrait of Octavian-Eugen Ganea

In Memoriam

 1987 - 2022 

The MoML Conference is organized in the name of Octavian-Eugen Ganea, whose scientific work and drive to help others closely exemplified the goals of this conference. To honor his life and his work, we award the Octavian-Eugen Ganea Prize for Best Paper every year.

Diamond Sponsor

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Venue

Koch Institute for Integrative Cancer Research — Luria Auditorium

MIT

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MIT Building 76

500 Main Street

Cambridge, MA 02142

 

Contact Details

Email: jclinic-info@mit.edu

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