Multimodal Deep Learning for Protein Engineering | Kevin K. Yang
Molecular Modelling and Drug Discovery7 Kesä 2023

Multimodal Deep Learning for Protein Engineering | Kevin K. Yang

[DISCLAIMER] - For the full visual experience, we recommend you tune in through our ⁠⁠⁠⁠⁠⁠⁠⁠YouTube channel ⁠⁠⁠⁠⁠⁠⁠⁠to see the presented slides.

Try datamol.io - the open source toolkit that simplifies molecular processing and featurization workflows for machine learning scientists working in drug discovery: ⁠⁠⁠⁠⁠https://datamol.io/⁠⁠⁠⁠⁠

If you enjoyed this talk, consider joining the ⁠⁠⁠⁠⁠⁠⁠⁠Molecular Modeling and Drug Discovery (M2D2) talks⁠⁠⁠⁠⁠⁠⁠⁠ live.

Also, consider joining the ⁠⁠⁠⁠⁠⁠⁠⁠M2D2 Slack⁠⁠⁠⁠⁠⁠⁠⁠.

Abstract: Engineered proteins play increasingly essential roles in industries and applications spanning pharmaceuticals, agriculture, specialty chemicals, and fuel. Machine learning could enable an unprecedented level of control in protein engineering for therapeutic and industrial applications. Large self-supervised models pretrained on millions of protein sequences have recently gained popularity in generating embeddings of protein sequences for protein property prediction. However, protein datasets contain information in addition to sequence that can improve model performance. This talk will cover models that use sequences, structures, and biophysical features to predict protein function or to generate functional proteins.

Speaker: Kevin K. Yang

Twitter - ⁠⁠⁠⁠⁠⁠⁠⁠Prudencio⁠⁠⁠⁠⁠⁠⁠⁠

Twitter - ⁠⁠⁠⁠⁠⁠⁠⁠Jonny⁠⁠⁠⁠⁠⁠⁠⁠

Twitter - ⁠⁠⁠⁠⁠⁠⁠⁠datamol.io

Tämä jakso on lisätty Podme-palveluun avoimen RSS-syötteen kautta eikä se ole Podmen omaa tuotantoa. Siksi jakso saattaa sisältää mainontaa.

Jaksot(60)

Structure-Independent Peptide Binder Design via Generative Language Models | Pranam Chatterjee

Structure-Independent Peptide Binder Design via Generative Language Models | Pranam Chatterjee

[DISCLAIMER] - For the full visual experience, we recommend you tune in through our ⁠⁠⁠⁠⁠⁠⁠⁠YouTube channel ⁠⁠⁠⁠⁠⁠⁠⁠to see the presented slides. Try datamol.io - the open source toolkit that simplifie...

20 Kesä 20231h

Learning Local Equivariant Representations for Large-Scale Atomistic Dynamics | Albert Musaelian

Learning Local Equivariant Representations for Large-Scale Atomistic Dynamics | Albert Musaelian

[DISCLAIMER] - For the full visual experience, we recommend you tune in through our ⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube channel ⁠⁠⁠⁠⁠⁠⁠⁠⁠to see the presented slides. Try datamol.io - the open source toolkit that simplif...

13 Kesä 20231h 9min

Systematic Analysis of Biomolecular Conformational Ensembles with PENSA | Martin Vögele

Systematic Analysis of Biomolecular Conformational Ensembles with PENSA | Martin Vögele

[DISCLAIMER] - For the full visual experience, we recommend you tune in through our ⁠⁠⁠⁠⁠⁠⁠YouTube channel ⁠⁠⁠⁠⁠⁠⁠to see the presented slides. Try datamol.io - the open source toolkit that simplifies ...

30 Touko 202350min

Training Neural Network Potentials: Bayesian and Simulation-based Approaches | Stephan Thaler

Training Neural Network Potentials: Bayesian and Simulation-based Approaches | Stephan Thaler

[DISCLAIMER] - For the full visual experience, we recommend you tune in through our ⁠⁠⁠⁠⁠⁠YouTube channel ⁠⁠⁠⁠⁠⁠to see the presented slides. Try datamol.io - the open source toolkit that simplifies mo...

16 Touko 20231h 3min

Accelerating Cryptic Pocket Discovery Using Alphafold and Markov State Modelling | Soumendranath Bhakat

Accelerating Cryptic Pocket Discovery Using Alphafold and Markov State Modelling | Soumendranath Bhakat

[DISCLAIMER] - For the full visual experience, we recommend you tune in through our ⁠⁠⁠⁠⁠YouTube channel ⁠⁠⁠⁠⁠to see the presented slides. Try datamol.io - the open source toolkit that simplifies mole...

9 Touko 202331min

Machine Learning Molecules | Gianni De Fabritiis

Machine Learning Molecules | Gianni De Fabritiis

[DISCLAIMER] - For the full visual experience, we recommend you tune in through our ⁠⁠⁠⁠⁠YouTube channel ⁠⁠⁠⁠⁠to see the presented slides. Try datamol.io - the open source toolkit that simplifies mole...

25 Huhti 202357min

Protein Representation Learning by Geometric Structure Pretraining | Zuobai Zhang

Protein Representation Learning by Geometric Structure Pretraining | Zuobai Zhang

[DISCLAIMER] - For the full visual experience, we recommend you tune in through our ⁠⁠⁠⁠YouTube channel ⁠⁠⁠⁠to see the presented slides. Try datamol.io - the open source toolkit that simplifies molecu...

19 Huhti 202353min

Suosittua kategoriassa Tiede

rss-mita-tulisi-tietaa
rss-hereilla
utelias-mieli
rss-duodecim-lehti
rss-totuuden-liepeilla
tiedekulma-podcast
rss-radplus
docemilia
filocast-filosofian-perusteet
rss-laakaripodi
rss-tiedetta-vai-tarinaa
university-of-eastern-finland
sotataidon-ytimessa
radio-antro
rss-bios-podcast
rss-poliisin-mieli
rss-ilmasto-kriisissa
rss-ylistys-elaimille
rss-kasvikutsut