De novo design of protein structure and function with RFdiffusion.

Autor: Watson JL; Department of Biochemistry, University of Washington, Seattle, WA, USA.; Institute for Protein Design, University of Washington, Seattle, WA, USA., Juergens D; Department of Biochemistry, University of Washington, Seattle, WA, USA.; Institute for Protein Design, University of Washington, Seattle, WA, USA.; Graduate Program in Molecular Engineering, University of Washington, Seattle, WA, USA., Bennett NR; Department of Biochemistry, University of Washington, Seattle, WA, USA.; Institute for Protein Design, University of Washington, Seattle, WA, USA.; Graduate Program in Molecular Engineering, University of Washington, Seattle, WA, USA., Trippe BL; Institute for Protein Design, University of Washington, Seattle, WA, USA.; Columbia University, Department of Statistics, New York, NY, USA.; Irving Institute for Cancer Dynamics, Columbia University, New York, NY, USA., Yim J; Institute for Protein Design, University of Washington, Seattle, WA, USA.; Massachusetts Institute of Technology, Cambridge, MA, USA., Eisenach HE; Department of Biochemistry, University of Washington, Seattle, WA, USA.; Institute for Protein Design, University of Washington, Seattle, WA, USA., Ahern W; Department of Biochemistry, University of Washington, Seattle, WA, USA.; Institute for Protein Design, University of Washington, Seattle, WA, USA.; Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, USA., Borst AJ; Department of Biochemistry, University of Washington, Seattle, WA, USA.; Institute for Protein Design, University of Washington, Seattle, WA, USA., Ragotte RJ; Department of Biochemistry, University of Washington, Seattle, WA, USA.; Institute for Protein Design, University of Washington, Seattle, WA, USA., Milles LF; Department of Biochemistry, University of Washington, Seattle, WA, USA.; Institute for Protein Design, University of Washington, Seattle, WA, USA., Wicky BIM; Department of Biochemistry, University of Washington, Seattle, WA, USA.; Institute for Protein Design, University of Washington, Seattle, WA, USA., Hanikel N; Department of Biochemistry, University of Washington, Seattle, WA, USA.; Institute for Protein Design, University of Washington, Seattle, WA, USA., Pellock SJ; Department of Biochemistry, University of Washington, Seattle, WA, USA.; Institute for Protein Design, University of Washington, Seattle, WA, USA., Courbet A; Department of Biochemistry, University of Washington, Seattle, WA, USA.; Institute for Protein Design, University of Washington, Seattle, WA, USA.; National Centre for Scientific Research, École Normale Supérieure rue d'Ulm, Paris, France., Sheffler W; Department of Biochemistry, University of Washington, Seattle, WA, USA.; Institute for Protein Design, University of Washington, Seattle, WA, USA., Wang J; Department of Biochemistry, University of Washington, Seattle, WA, USA.; Institute for Protein Design, University of Washington, Seattle, WA, USA., Venkatesh P; Department of Biochemistry, University of Washington, Seattle, WA, USA.; Institute for Protein Design, University of Washington, Seattle, WA, USA.; Graduate Program in Biological Physics, Structure and Design, University of Washington, Seattle, WA, USA., Sappington I; Department of Biochemistry, University of Washington, Seattle, WA, USA.; Institute for Protein Design, University of Washington, Seattle, WA, USA.; Graduate Program in Biological Physics, Structure and Design, University of Washington, Seattle, WA, USA., Torres SV; Department of Biochemistry, University of Washington, Seattle, WA, USA.; Institute for Protein Design, University of Washington, Seattle, WA, USA.; Graduate Program in Biological Physics, Structure and Design, University of Washington, Seattle, WA, USA., Lauko A; Department of Biochemistry, University of Washington, Seattle, WA, USA.; Institute for Protein Design, University of Washington, Seattle, WA, USA.; Graduate Program in Biological Physics, Structure and Design, University of Washington, Seattle, WA, USA., De Bortoli V; National Centre for Scientific Research, École Normale Supérieure rue d'Ulm, Paris, France., Mathieu E; Department of Engineering, University of Cambridge, Cambridge, UK., Ovchinnikov S; Faculty of Applied Sciences, Harvard University, Cambridge, MA, USA.; John Harvard Distinguished Science Fellowship, Harvard University, Cambridge, MA, USA., Barzilay R; Massachusetts Institute of Technology, Cambridge, MA, USA., Jaakkola TS; Massachusetts Institute of Technology, Cambridge, MA, USA., DiMaio F; Department of Biochemistry, University of Washington, Seattle, WA, USA.; Institute for Protein Design, University of Washington, Seattle, WA, USA., Baek M; School of Biological Sciences, Seoul National University, Seoul, Republic of Korea., Baker D; Department of Biochemistry, University of Washington, Seattle, WA, USA. dabaker@uw.edu.; Institute for Protein Design, University of Washington, Seattle, WA, USA. dabaker@uw.edu.; Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA. dabaker@uw.edu.

Publikováno v: Nature [Nature] 2023 Aug; Vol. 620 (7976), pp. 1089-1100. Date of Electronic Publication: 2023 Jul 11.

Riemannian Score-Based Generative Modelling

Autor: De Bortoli, V, Mathieu, E, Hutchinson, M, Thornton, J, Teh, YW, Doucet, A

Score-based generative models (SGMs) are a powerful class of generative models that exhibit remarkable empirical performance. Score-based generative modelling (SGM) consists of a ``noising'' stage, whereby a diffusion is used to gradually add Gaussia

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::600147ab3c626478e25d2b8c8989388f
http://arxiv.org/abs/2202.02763

Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling

Autor: De Bortoli, V, Thornton, J, Heng, J, Doucet, A

Progressively applying Gaussian noise transforms complex data distributions to approximately Gaussian. Reversing this dynamic defines a generative model. When the forward noising process is given by a Stochastic Differential Equation (SDE), Song et a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::44706311053e8496fa349433b26a982f

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MapGen-Diff: An End-to-End Remote Sensing Image to Map Generator via Denoising Diffusion Bridge Model.

Autor: Tian, Jilong¹ (AUTHOR) tianjilong19@nudt.edu.cn, Wu, Jiangjiang¹ (AUTHOR), Chen, Hao¹ (AUTHOR) hchen@nudt.edu.cn, Ma, Mengyu¹ (AUTHOR)

Publikováno v: Remote Sensing. Oct2024, Vol. 16 Issue 19, p3716. 23p.