activity
20182023
most citedCausal Network Models of SARS-CoV-2 Expression and Aging to Identify Candidates for Drug Repurposing

69 citations · 91 across the 6 of their papers we have counts for

collaborators

6 papers

q-bio.QM2023★ 8 cited

Multimodal LLMs for health grounded in individual-specific data

Anastasiya Belyaeva, Justin Cosentino, Farhad Hormozdiari +6

Foundation large language models (LLMs) have shown an impressive ability to solve tasks across a wide range of fields including health. To effectively solve personalized health tas…

q-bio.GN2022

Knowledge distillation for fast and accurate DNA sequence correction

Anastasiya Belyaeva, Joel Shor, Daniel E. Cook +11

Accurate genome sequencing can improve our understanding of biology and the genetic basis of disease. The standard approach for generating DNA sequences from PacBio instruments rel…

q-bio.GN2021

Identifying 3D Genome Organization in Diploid Organisms via Euclidean Distance Geometry

Anastasiya Belyaeva, Kaie Kubjas, Lawrence J. Sun +1

The spatial organization of the DNA in the cell nucleus plays an important role for gene regulation, DNA replication, and genomic integrity. Through the development of chromosome c…

q-bio.MN2020★ 69 cited

Causal Network Models of SARS-CoV-2 Expression and Aging to Identify Candidates for Drug Repurposing

Anastasiya Belyaeva, Louis Cammarata, Adityanarayanan Radhakrishnan +4

Given the severity of the SARS-CoV-2 pandemic, a major challenge is to rapidly repurpose existing approved drugs for clinical interventions. While a number of data-driven and exper…

stat.ME2019★ 3 cited

Anchored Causal Inference in the Presence of Measurement Error

Basil Saeed, Anastasiya Belyaeva, Yuhao Wang +1

We consider the problem of learning a causal graph in the presence of measurement error. This setting is for example common in genomics, where gene expression is corrupted through…

stat.ME2018★ 11 cited

Direct Estimation of Differences in Causal Graphs

Yuhao Wang, Chandler Squires, Anastasiya Belyaeva +1

We consider the problem of estimating the differences between two causal directed acyclic graph (DAG) models with a shared topological order given i.i.d. samples from each model. T…