Search Results for author: Bonnie Berger

Found 17 papers, 11 papers with code

Dirichlet Flow Matching with Applications to DNA Sequence Design

1 code implementation8 Feb 2024 Hannes Stark, Bowen Jing, Chenyu Wang, Gabriele Corso, Bonnie Berger, Regina Barzilay, Tommi Jaakkola

Further, we provide distilled Dirichlet flow matching, which enables one-step sequence generation with minimal performance hits, resulting in $O(L)$ speedups compared to autoregressive models.

AlphaFold Meets Flow Matching for Generating Protein Ensembles

1 code implementation7 Feb 2024 Bowen Jing, Bonnie Berger, Tommi Jaakkola

When trained and evaluated on the PDB, our method provides a superior combination of precision and diversity compared to AlphaFold with MSA subsampling.

Equivariant Scalar Fields for Molecular Docking with Fast Fourier Transforms

1 code implementation7 Dec 2023 Bowen Jing, Tommi Jaakkola, Bonnie Berger

The runtime of our approach can be amortized at several levels of abstraction, and is particularly favorable for virtual screening settings with a common binding pocket.

Molecular Docking

EigenFold: Generative Protein Structure Prediction with Diffusion Models

1 code implementation5 Apr 2023 Bowen Jing, Ezra Erives, Peter Pao-Huang, Gabriele Corso, Bonnie Berger, Tommi Jaakkola

Protein structure prediction has reached revolutionary levels of accuracy on single structures, yet distributional modeling paradigms are needed to capture the conformational ensembles and flexibility that underlie biological function.

Protein Structure Prediction

Causally-guided Regularization of Graph Attention Improves Generalizability

no code implementations20 Oct 2022 Alexander P. Wu, Thomas Markovich, Bonnie Berger, Nils Hammerla, Rohit Singh

Graph attention networks estimate the relational importance of node neighbors to aggregate relevant information over local neighborhoods for a prediction task.

Causal Inference Graph Attention +1

Granger causal inference on DAGs identifies genomic loci regulating transcription

1 code implementation ICLR 2022 Rohit Singh, Alexander P. Wu, Bonnie Berger

When a dynamical system can be modeled as a sequence of observations, Granger causality is a powerful approach for detecting predictive interactions between its variables.

Causal Inference

Enriching and Characterizing T-Cell Repertoires from 3' Barcoded Single-Cell Whole Transcriptome Amplification Products

no code implementations21 Mar 2022 Tasneem Jivanjee, Samira Ibrahim, Sarah K. Nyquist, G. James Gatter, Joshua D. Bromley, Swati Jaiswal, Bonnie Berger, Samuel M. Behar, J. Christopher Love, Alex K. Shalek

In short, a fraction of the 3' barcoded whole transcriptome amplification (WTA) product typically used to generate a massively parallel 3' scRNA-seq library is enriched for TCR transcripts using biotinylated probes, and further amplified using the same universal primer sequence from WTA.


Exploring generative atomic models in cryo-EM reconstruction

no code implementations3 Jul 2021 Ellen D. Zhong, Adam Lerer, Joseph H. Davis, Bonnie Berger

Although reconstruction algorithms typically model the 3D volume as a generic function parameterized as a voxel array or neural network, the underlying atomic structure of the protein of interest places well-defined physical constraints on the reconstructed structure.

Protein Folding

CryoDRGN2: Ab Initio Neural Reconstruction of 3D Protein Structures From Real Cryo-EM Images

no code implementations ICCV 2021 Ellen D. Zhong, Adam Lerer, Joseph H. Davis, Bonnie Berger

In this work we describe cryoDRGN2, an ab initio reconstruction algorithm, which can jointly estimate image poses and learn a neural model of a distribution of 3D structures on real heterogeneous cryo-EM data.

Learning Mutational Semantics

1 code implementation NeurIPS 2020 Brian Hie, Ellen Zhong, Bryan Bryson, Bonnie Berger

In many natural domains, changing a small part of an entity can transform its semantics; for example, a single word change can alter the meaning of a sentence, or a single amino acid change can mutate a viral protein to escape antiviral treatment or immunity.

Sentence valid

Explicitly disentangling image content from translation and rotation with spatial-VAE

1 code implementation NeurIPS 2019 Tristan Bepler, Ellen D. Zhong, Kotaro Kelley, Edward Brignole, Bonnie Berger

Given an image dataset, we are often interested in finding data generative factors that encode semantic content independently from pose variables such as rotation and translation.

Disentanglement Translation

Reconstructing continuous distributions of 3D protein structure from cryo-EM images

2 code implementations ICLR 2020 Ellen D. Zhong, Tristan Bepler, Joseph H. Davis, Bonnie Berger

Cryo-electron microscopy (cryo-EM) is a powerful technique for determining the structure of proteins and other macromolecular complexes at near-atomic resolution.

3D Volumetric Reconstruction Clustering +2

Learning protein sequence embeddings using information from structure

1 code implementation ICLR 2019 Tristan Bepler, Bonnie Berger

We introduce a framework that maps any protein sequence to a sequence of vector embeddings --- one per amino acid position --- that encode structural information.

Position Representation Learning

Large-Margin Classification in Hyperbolic Space

2 code implementations1 Jun 2018 Hyunghoon Cho, Benjamin DeMeo, Jian Peng, Bonnie Berger

Representing data in hyperbolic space can effectively capture latent hierarchical relationships.

Classification General Classification

Diffusion Component Analysis: Unraveling Functional Topology in Biological Networks

no code implementations10 Apr 2015 Hyunghoon Cho, Bonnie Berger, Jian Peng

In this paper, we introduce diffusion component analysis (DCA), a framework that plugs in a diffusion model and learns a low-dimensional vector representation of each node to encode the topological properties of a network.

Dimensionality Reduction

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