Hyebin Song
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View article: A widespread protein misfolding mechanism is differentially rescued in vitro by chaperones based on gene essentiality
A widespread protein misfolding mechanism is differentially rescued in vitro by chaperones based on gene essentiality Open
Protein misfolding involving changes in non-covalent lasso entanglement (NCLE) status has been proposed based on simulations and biochemical assays of a small number of proteins. Here, we detect hallmarks of these misfolded states across h…
View article: A widespread protein misfolding mechanism is differentially rescued by chaperones based on gene essentiality
A widespread protein misfolding mechanism is differentially rescued by chaperones based on gene essentiality Open
Protein misfolding involving changes in non-covalent lasso entanglement (NCLE) status has been proposed based on simulations and biochemical assays of a small number of proteins. Here, we detect hallmarks of these misfolded states across h…
View article: Non-native entanglement protein misfolding observed in all-atom simulations and supported by experimental structural ensembles
Non-native entanglement protein misfolding observed in all-atom simulations and supported by experimental structural ensembles Open
Several mechanisms are known to cause monomeric protein misfolding. Coarse-grained simulations have predicted an additional mechanism exists involving off-pathway, noncovalent lasso entanglements, which are long-lived kinetic traps and str…
View article: Protein misfolding involving entanglements provides a structural explanation for the origin of stretched-exponential refolding kinetics
Protein misfolding involving entanglements provides a structural explanation for the origin of stretched-exponential refolding kinetics Open
Stretched-exponential protein refolding kinetics, first observed decades ago, were attributed to a nonnative ensemble of structures with parallel, non-interconverting folding pathways. However, the structural origin of the large energy bar…
View article: Semi-Parametric Batched Global Multi-Armed Bandits with Covariates
Semi-Parametric Batched Global Multi-Armed Bandits with Covariates Open
The multi-armed bandits (MAB) framework is a widely used approach for sequential decision-making, where a decision-maker selects an arm in each round with the goal of maximizing long-term rewards. Moreover, in many practical applications, …
View article: Genetic modifiers and ascertainment drive variable expressivity of complex disorders
Genetic modifiers and ascertainment drive variable expressivity of complex disorders Open
SUMMARY Variable expressivity of disease-associated variants implies a role for secondary variants that modify clinical features. We assessed the effects of modifier variants towards clinical outcomes of 2,252 individuals with primary vari…
View article: Weighted shape-constrained estimation for the autocovariance sequence from a reversible Markov chain
Weighted shape-constrained estimation for the autocovariance sequence from a reversible Markov chain Open
We present a novel weighted $\ell_2$ projection method for estimating autocovariance sequences and spectral density functions from reversible Markov chains. Berg and Song (2023) introduced a least-squares shape-constrained estimation appro…
View article: Multivariate moment least-squares estimators for reversible Markov chains
Multivariate moment least-squares estimators for reversible Markov chains Open
Markov chain Monte Carlo (MCMC) is a commonly used method for approximating expectations with respect to probability distributions. Uncertainty assessment for MCMC estimators is essential in practical applications. Moreover, for multivaria…
View article: Inferring protein fitness landscapes from laboratory evolution experiments
Inferring protein fitness landscapes from laboratory evolution experiments Open
Directed laboratory evolution applies iterative rounds of mutation and selection to explore the protein fitness landscape and provides rich information regarding the underlying relationships between protein sequence, structure, and functio…
View article: Inferring protein fitness landscapes from laboratory evolution experiments
Inferring protein fitness landscapes from laboratory evolution experiments Open
Directed laboratory evolution applies iterative rounds of mutation and selection to explore the protein fitness landscape and provides rich information regarding the underlying relationships between protein sequence, structure, and functio…
View article: Efficient shape-constrained inference for the autocovariance sequence from a reversible Markov chain
Efficient shape-constrained inference for the autocovariance sequence from a reversible Markov chain Open
In this paper, we study the problem of estimating the autocovariance sequence resulting from a reversible Markov chain. A motivating application for studying this problem is the estimation of the asymptotic variance in central limit theore…
View article: NURD: Negative-Unlabeled Learning for Online Datacenter Straggler Prediction
NURD: Negative-Unlabeled Learning for Online Datacenter Straggler Prediction Open
Datacenters execute large computational jobs, which are composed of smaller tasks. A job completes when all its tasks finish, so stragglers -- rare, yet extremely slow tasks -- are a major impediment to datacenter performance. Accurately p…
View article: Convergence guarantee for the sparse monotone single index model
Convergence guarantee for the sparse monotone single index model Open
We consider a high-dimensional monotone single index model (hdSIM), which is a semiparametric extension of a high-dimensional generalize linear model (hdGLM), where the link function is unknown, but constrained with monotone non-decreasing…
View article: Convergence guarantee for the sparse monotone single index model
Convergence guarantee for the sparse monotone single index model Open
We consider a high-dimensional monotone single index model (hdSIM), which is a semiparametric extension of a high-dimensional generalize linear model (hdGLM), where the link function is unknown, but constrained with monotone and non-decrea…
View article: Prediction in the presence of response-dependent missing labels
Prediction in the presence of response-dependent missing labels Open
In a variety of settings, limitations of sensing technologies or other sampling mechanisms result in missing labels, where the likelihood of a missing label in the training set is an unknown function of the data. For example, satellites us…
View article: Inferring protein sequence-function relationships with large-scale positive-unlabeled learning
Inferring protein sequence-function relationships with large-scale positive-unlabeled learning Open
Summary Machine learning can infer how protein sequence maps to function without requiring a detailed understanding of the underlying physical or biological mechanisms. It’s challenging to apply existing supervised learning frameworks to l…
View article: The bias of isotonic regression
The bias of isotonic regression Open
We study the bias of the isotonic regression estimator. While there is extensive work characterizing the mean squared error of the isotonic regression estimator, relatively little is known about the bias. In this paper, we provide a sharp …
View article: Graph-Based Regularization for Regression Problems with Alignment and Highly Correlated Designs
Graph-Based Regularization for Regression Problems with Alignment and Highly Correlated Designs Open
Sparse models for high-dimensional linear regression and machine learning have received substantial attention over the past two decades. Model selection, or determining which features or covariates are the best explanatory variables, is cr…
View article: Convex and Non-convex Approaches for Statistical Inference with Noisy Labels
Convex and Non-convex Approaches for Statistical Inference with Noisy Labels Open
We study the problem of estimation and testing in logistic regression with class-conditional noise in the observed labels, which has an important implication in the Positive-Unlabeled (PU) learning setting. With the key observation that th…
View article: Convex and Non-convex Approaches for Statistical Inference with Class-Conditional Noisy Labels
Convex and Non-convex Approaches for Statistical Inference with Class-Conditional Noisy Labels Open
We study the problem of estimation and testing in logistic regression with class-conditional noise in the observed labels, which has an important implication in the Positive-Unlabeled (PU) learning setting. With the key observation that th…
View article: The bias of isotonic regression
The bias of isotonic regression Open
We study the bias of the isotonic regression estimator. While there is extensive work characterizing the mean squared error of the isotonic regression estimator, relatively little is known about the bias. In this paper, we provide a sharp …
View article: PUlasso: High-Dimensional Variable Selection With Presence-Only Data
PUlasso: High-Dimensional Variable Selection With Presence-Only Data Open
In various real-world problems, we are presented with classification problems with positive and unlabeled data, referred to as presence-only responses. In this article we study variable selection in the context of presence only responses w…
View article: Graph-based regularization for regression problems with alignment and highly-correlated designs
Graph-based regularization for regression problems with alignment and highly-correlated designs Open
Sparse models for high-dimensional linear regression and machine learning have received substantial attention over the past two decades. Model selection, or determining which features or covariates are the best explanatory variables, is cr…
View article: PULasso: High-dimensional variable selection with presence-only data
PULasso: High-dimensional variable selection with presence-only data Open
In various real-world problems, we are presented with classification problems with positive and unlabeled data, referred to as presence-only responses. In this paper, we study variable selection in the context of presence only responses wh…